Coupling WRF double-moment 6-class microphysics schemes to RRTMG radiation scheme in weather research forecasting model

DOE PAGES

Bae, Soo Ya; Hong, Song -You; Lim, Kyo-Sun Sunny

2016-01-01

A method to explicitly calculate the effective radius of hydrometeors in the Weather Research Forecasting (WRF) double-moment 6-class (WDM6) microphysics scheme is designed to tackle the physical inconsistency in cloud properties between the microphysics and radiation processes. At each model time step, the calculated effective radii of hydrometeors from the WDM6 scheme are linked to the Rapid Radiative Transfer Model for GCMs (RRTMG) scheme to consider the cloud effects in radiative flux calculation. This coupling effect of cloud properties between the WDM6 and RRTMG algorithms is examined for a heavy rainfall event in Korea during 25–27 July 2011, and itmore » is compared to the results from the control simulation in which the effective radius is prescribed as a constant value. It is found that the derived radii of hydrometeors in the WDM6 scheme are generally larger than the prescribed values in the RRTMG scheme. Consequently, shortwave fluxes reaching the ground (SWDOWN) are increased over less cloudy regions, showing a better agreement with a satellite image. The overall distribution of the 24-hour accumulated rainfall is not affected but its amount is changed. In conclusion, a spurious rainfall peak over the Yellow Sea is alleviated, whereas the local maximum in the central part of the peninsula is increased.« less

Coupling WRF double-moment 6-class microphysics schemes to RRTMG radiation scheme in weather research forecasting model

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

Bae, Soo Ya; Hong, Song -You; Lim, Kyo-Sun Sunny

A method to explicitly calculate the effective radius of hydrometeors in the Weather Research Forecasting (WRF) double-moment 6-class (WDM6) microphysics scheme is designed to tackle the physical inconsistency in cloud properties between the microphysics and radiation processes. At each model time step, the calculated effective radii of hydrometeors from the WDM6 scheme are linked to the Rapid Radiative Transfer Model for GCMs (RRTMG) scheme to consider the cloud effects in radiative flux calculation. This coupling effect of cloud properties between the WDM6 and RRTMG algorithms is examined for a heavy rainfall event in Korea during 25–27 July 2011, and itmore » is compared to the results from the control simulation in which the effective radius is prescribed as a constant value. It is found that the derived radii of hydrometeors in the WDM6 scheme are generally larger than the prescribed values in the RRTMG scheme. Consequently, shortwave fluxes reaching the ground (SWDOWN) are increased over less cloudy regions, showing a better agreement with a satellite image. The overall distribution of the 24-hour accumulated rainfall is not affected but its amount is changed. In conclusion, a spurious rainfall peak over the Yellow Sea is alleviated, whereas the local maximum in the central part of the peninsula is increased.« less

Coupling WRF Double-Moment 6-Class Microphysics Schemes to RRTMG Radiation Scheme in Weather Research Forecasting Model

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

Bae, Soo Ya; Hong, Song-You; Lim, Kyo-Sun Sunny

A method to explicitly calculate the effective radius of hydrometeors in the Weather Research Forecasting (WRF) double-moment 6-class (WDM6) microphysics scheme is designed to tackle the physical inconsistency in cloud properties between the microphysics and radiation processes. At each model time step, the calculated effective radii of hydrometeors from the WDM6 scheme are linked to the Rapid Radiative Transfer Model for GCMs (RRTMG) scheme to consider the cloud effects in radiative flux calculation. This coupling effect of cloud properties between the WDM6 and RRTMG algorithms is examined for a heavy rainfall event in Korea during 25–27 July 2011, and itmore » is compared to the results from the control simulation in which the effective radius is prescribed as a constant value. It is found that the derived radii of hydrometeors in the WDM6 scheme are generally larger than the prescribed values in the RRTMG scheme. Consequently, shortwave fluxes reaching the ground (SWDOWN) are increased over less cloudy regions, showing a better agreement with a satellite image. The overall distribution of the 24-hour accumulated rainfall is not affected but its amount is changed. A spurious rainfall peak over the Yellow Sea is alleviated, whereas the local maximum in the central part of the peninsula is increased.« less

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.

Seasonal forecasts of groundwater levels in Lanyang Plain in Taiwan

NASA Astrophysics Data System (ADS)

Chang, Ya-Chi; Lin, Yi-Chiu

2017-04-01

Groundwater plays a critical and important role in world's freshwater resources and it is also an important part of Taiwan's water supply for domestic, agricultural and industrial use. Prolonged dry climatic conditions can induce groundwater drought and may have huge impact on water resources. Therefore, this study utilizes seasonal rainfall forecasts from the Model for Prediction Across Scales (MPAS) to simulate groundwater levels in Lanyang Plain in Taiwan up to three months into future. The MPAS is setup with 120 km uniform grid and the physics schemes including WSM6 micorphysics scheme, Kain-Fritsch cumulus scheme, RRTMG radiation scheme, and YSU planetary boundary layer scheme are used to provide the rainfall forecasts. Results of this study can provide a reference for water resources management to ensure the sustainability of groundwater resources in Lanyang Plain.

Diversity of Rainfall Thresholds for early warning of hydro-geological disasters

NASA Astrophysics Data System (ADS)

De Luca, Davide L.; Versace, Pasquale

2017-06-01

For early warning of disasters induced by precipitation (such as floods and landslides), different kinds of rainfall thresholds are adopted, which vary from each other, on the basis on adopted hypotheses. In some cases, they represent the occurrence probability of an event (landslide or flood), in other cases the exceedance probability of a critical value for an assigned indicator I (a function of rainfall heights), and in further cases they only indicate the exceeding of a prefixed percentage a critical value for I, indicated as Icr. For each scheme, it is usual to define three different criticality levels (ordinary, moderate and severe), which are associated to warning levels, according to emergency plans. This work briefly discusses different schemes of rainfall thresholds, focusing attention on landslide prediction, with some applications to a real case study in Calabria region (southern Italy).

Introducing the MIT Regional Climate Model (MRCM)

NASA Astrophysics Data System (ADS)

Eltahir, Elfatih A. B.; Winter, Jonathn M.; Marcella, Marc P.; Gianotti, Rebecca L.; Im, Eun-Soon

2013-04-01

During the last decade researchers at MIT have worked on improving the skill of Regional Climate Model version 3 (RegCM3) in simulating climate over different regions through the incorporation of new physical schemes or modification of original schemes. The MIT Regional Climate Model (MRCM) features several modifications over RegCM3 including coupling of Integrated Biosphere Simulator (IBIS), a new surface albedo assignment method, a new convective cloud and rainfall auto-conversion scheme, and a modified boundary layer height and cloud scheme. Here, we introduce the MRCM and briefly describe the major model modifications relative to RegCM3 and their impact on the model performance. The most significant difference relative to the RegCM3 original configuration is coupling the Integrated Biosphere Simulator (IBIS) land-surface scheme (Winter et al., 2009). Based on the simulations using IBIS over the North America, the Maritime Continent, Southwest Asia and West Africa, we demonstrate that the use of IBIS as the land surface scheme results in better representation of surface energy and water budgets in comparison to BATS. Furthermore, the addition of a new irrigation scheme to IBIS makes it possible to investigate the effects of irrigation over any region. Also a new surface albedo assignment method used together with IBIS brings further improvement in simulations of surface radiation (Marcella and Eltahir, 2013). Another important feature of the MRCM is the introduction of a new convective cloud and rainfall auto-conversion scheme (Gianotti and Eltahir, 2013). This modification brings more physical realism into an important component of the model, and succeeds in simulating convective-radiative feedback improving model performance across several radiation fields and rainfall characteristics. Other features of MRCM such as the modified boundary layer height and cloud scheme, and the improvements in the dust emission and transport representations will be discussed.

Lattice Boltzmann method for rain-induced overland flow

NASA Astrophysics Data System (ADS)

Ding, Yu; Liu, Haifei; Peng, Yong; Xing, Liming

2018-07-01

Complex rainfall situations can generate overland flow with complex hydrodynamic characteristics, affecting the surface configuration (i.e. sheet erosion) and environment to varying degrees. Reliable numerical simulations can provide a scientific method for the optimization of environmental management. A mesoscopic numerical method, the lattice Boltzmann method, was employed to simulate overland flows. To deal with complex rainfall, two schemes were introduced to improve the lattice Boltzmann equation and the local equilibrium function, respectively. Four typical cases with differences in rainfall, bed roughness, and slopes were selected to test the accuracy and applicability of the proposed schemes. It was found that the simulated results were in good agreement with the experimental data, analytical values, and the results produced by other models.

Calibration of a convective parameterization scheme in the WRF model and its impact on the simulation of East Asian summer monsoon precipitation

DOE PAGES

Yang, Ben; Zhang, Yaocun; Qian, Yun; ...

2014-03-26

Reasonably modeling the magnitude, south-north gradient and seasonal propagation of precipitation associated with the East Asian Summer Monsoon (EASM) is a challenging task in the climate community. In this study we calibrate five key parameters in the Kain-Fritsch convection scheme in the WRF model using an efficient importance-sampling algorithm to improve the EASM simulation. We also examine the impacts of the improved EASM precipitation on other physical process. Our results suggest similar model sensitivity and values of optimized parameters across years with different EASM intensities. By applying the optimal parameters, the simulated precipitation and surface energy features are generally improved.more » The parameters related to downdraft, entrainment coefficients and CAPE consumption time (CCT) can most sensitively affect the precipitation and atmospheric features. Larger downdraft coefficient or CCT decrease the heavy rainfall frequency, while larger entrainment coefficient delays the convection development but build up more potential for heavy rainfall events, causing a possible northward shift of rainfall distribution. The CCT is the most sensitive parameter over wet region and the downdraft parameter plays more important roles over drier northern region. Long-term simulations confirm that by using the optimized parameters the precipitation distributions are better simulated in both weak and strong EASM years. Due to more reasonable simulated precipitation condensational heating, the monsoon circulations are also improved. Lastly, by using the optimized parameters the biases in the retreating (beginning) of Mei-yu (northern China rainfall) simulated by the standard WRF model are evidently reduced and the seasonal and sub-seasonal variations of the monsoon precipitation are remarkably improved.« less

An improved rainfall disaggregation technique for GCMs

NASA Astrophysics Data System (ADS)

Onof, C.; Mackay, N. G.; Oh, L.; Wheater, H. S.

1998-08-01

Meteorological models represent rainfall as a mean value for a grid square so that when the latter is large, a disaggregation scheme is required to represent the spatial variability of rainfall. In general circulation models (GCMs) this is based on an assumption of exponentiality of rainfall intensities and a fixed value of areal rainfall coverage, dependent on rainfall type. This paper examines these two assumptions on the basis of U.K. and U.S. radar data. Firstly, the coverage of an area is strongly dependent on its size, and this dependence exhibits a scaling law over a range of sizes. Secondly, the coverage is, of course, dependent on the resolution at which it is measured, although this dependence is weak at high resolutions. Thirdly, the time series of rainfall coverages has a long-tailed autocorrelation function which is comparable to that of the mean areal rainfalls. It is therefore possible to reproduce much of the temporal dependence of coverages by using a regression of the log of the mean rainfall on the log of the coverage. The exponential assumption is satisfactory in many cases but not able to reproduce some of the long-tailed dependence of some intensity distributions. Gamma and lognormal distributions provide a better fit in these cases, but they have their shortcomings and require a second parameter. An improved disaggregation scheme for GCMs is proposed which incorporates the previous findings to allow the coverage to be obtained for any area and any mean rainfall intensity. The parameters required are given and some of their seasonal behavior is analyzed.

The concurrent multiplicative-additive approach for gauge-radar/satellite multisensor precipitation estimates

NASA Astrophysics Data System (ADS)

Garcia-Pintado, J.; Barberá, G. G.; Erena Arrabal, M.; Castillo, V. M.

2010-12-01

Objective analysis schemes (OAS), also called ``succesive correction methods'' or ``observation nudging'', have been proposed for multisensor precipitation estimation combining remote sensing data (meteorological radar or satellite) with data from ground-based raingauge networks. However, opposite to the more complex geostatistical approaches, the OAS techniques for this use are not optimized. On the other hand, geostatistical techniques ideally require, at the least, modelling the covariance from the rain gauge data at every time step evaluated, which commonly cannot be soundly done. Here, we propose a new procedure (concurrent multiplicative-additive objective analysis scheme [CMA-OAS]) for operational rainfall estimation using rain gauges and meteorological radar, which does not require explicit modelling of spatial covariances. On the basis of a concurrent multiplicative-additive (CMA) decomposition of the spatially nonuniform radar bias, within-storm variability of rainfall and fractional coverage of rainfall are taken into account. Thus both spatially nonuniform radar bias, given that rainfall is detected, and bias in radar detection of rainfall are handled. The interpolation procedure of CMA-OAS is built on the OAS, whose purpose is to estimate a filtered spatial field of the variable of interest through a successive correction of residuals resulting from a Gaussian kernel smoother applied on spatial samples. The CMA-OAS, first, poses an optimization problem at each gauge-radar support point to obtain both a local multiplicative-additive radar bias decomposition and a regionalization parameter. Second, local biases and regionalization parameters are integrated into an OAS to estimate the multisensor rainfall at the ground level. The approach considers radar estimates as background a priori information (first guess), so that nudging to observations (gauges) may be relaxed smoothly to the first guess, and the relaxation shape is obtained from the sequential optimization. The procedure is suited to relatively sparse rain gauge networks. To show the procedure, six storms are analyzed at hourly steps over 10,663 km2. Results generally indicated an improved quality with respect to other methods evaluated: a standard mean-field bias adjustment, an OAS spatially variable adjustment with multiplicative factors, ordinary cokriging, and kriging with external drift. In theory, it could be equally applicable to gauge-satellite estimates and other hydrometeorological variables.

Multi-ensemble regional simulation of Indian monsoon during contrasting rainfall years: role of convective schemes and nested domain

NASA Astrophysics Data System (ADS)

Devanand, Anjana; Ghosh, Subimal; Paul, Supantha; Karmakar, Subhankar; Niyogi, Dev

2018-06-01

Regional simulations of the seasonal Indian summer monsoon rainfall (ISMR) require an understanding of the model sensitivities to physics and resolution, and its effect on the model uncertainties. It is also important to quantify the added value in the simulated sub-regional precipitation characteristics by a regional climate model (RCM), when compared to coarse resolution rainfall products. This study presents regional model simulations of ISMR at seasonal scale using the Weather Research and Forecasting (WRF) model with the synoptic scale forcing from ERA-interim reanalysis, for three contrasting monsoon seasons, 1994 (excess), 2002 (deficit) and 2010 (normal). Impact of four cumulus schemes, viz., Kain-Fritsch (KF), Betts-Janjić-Miller, Grell 3D and modified Kain-Fritsch (KFm), and two micro physical parameterization schemes, viz., WRF Single Moment Class 5 scheme and Lin et al. scheme (LIN), with eight different possible combinations are analyzed. The impact of spectral nudging on model sensitivity is also studied. In WRF simulations using spectral nudging, improvement in model rainfall appears to be consistent in regions with topographic variability such as Central Northeast and Konkan Western Ghat sub-regions. However the results are also dependent on choice of cumulus scheme used, with KF and KFm providing relatively good performance and the eight member ensemble mean showing better results for these sub-regions. There is no consistent improvement noted in Northeast and Peninsular Indian monsoon regions. Results indicate that the regional simulations using nested domains can provide some improvements on ISMR simulations. Spectral nudging is found to improve upon the model simulations in terms of reducing the intra ensemble spread and hence the uncertainty in the model simulated precipitation. The results provide important insights regarding the need for further improvements in the regional climate simulations of ISMR for various sub-regions and contribute to the understanding of the added value in seasonal simulations by RCMs.

Multi-ensemble regional simulation of Indian monsoon during contrasting rainfall years: role of convective schemes and nested domain

NASA Astrophysics Data System (ADS)

Devanand, Anjana; Ghosh, Subimal; Paul, Supantha; Karmakar, Subhankar; Niyogi, Dev

2017-08-01

Regional simulations of the seasonal Indian summer monsoon rainfall (ISMR) require an understanding of the model sensitivities to physics and resolution, and its effect on the model uncertainties. It is also important to quantify the added value in the simulated sub-regional precipitation characteristics by a regional climate model (RCM), when compared to coarse resolution rainfall products. This study presents regional model simulations of ISMR at seasonal scale using the Weather Research and Forecasting (WRF) model with the synoptic scale forcing from ERA-interim reanalysis, for three contrasting monsoon seasons, 1994 (excess), 2002 (deficit) and 2010 (normal). Impact of four cumulus schemes, viz., Kain-Fritsch (KF), Betts-Janjić-Miller, Grell 3D and modified Kain-Fritsch (KFm), and two micro physical parameterization schemes, viz., WRF Single Moment Class 5 scheme and Lin et al. scheme (LIN), with eight different possible combinations are analyzed. The impact of spectral nudging on model sensitivity is also studied. In WRF simulations using spectral nudging, improvement in model rainfall appears to be consistent in regions with topographic variability such as Central Northeast and Konkan Western Ghat sub-regions. However the results are also dependent on choice of cumulus scheme used, with KF and KFm providing relatively good performance and the eight member ensemble mean showing better results for these sub-regions. There is no consistent improvement noted in Northeast and Peninsular Indian monsoon regions. Results indicate that the regional simulations using nested domains can provide some improvements on ISMR simulations. Spectral nudging is found to improve upon the model simulations in terms of reducing the intra ensemble spread and hence the uncertainty in the model simulated precipitation. The results provide important insights regarding the need for further improvements in the regional climate simulations of ISMR for various sub-regions and contribute to the understanding of the added value in seasonal simulations by RCMs.

Validation of satellite-based rainfall in Kalahari

NASA Astrophysics Data System (ADS)

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

2018-06-01

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

Assessment of the Weather Research and Forecasting (WRF) model for simulation of extreme rainfall events in the upper Ganga Basin

NASA Astrophysics Data System (ADS)

Chawla, Ila; Osuri, Krishna K.; Mujumdar, Pradeep P.; Niyogi, Dev

2018-02-01

Reliable estimates of extreme rainfall events are necessary for an accurate prediction of floods. Most of the global rainfall products are available at a coarse resolution, rendering them less desirable for extreme rainfall analysis. Therefore, regional mesoscale models such as the advanced research version of the Weather Research and Forecasting (WRF) model are often used to provide rainfall estimates at fine grid spacing. Modelling heavy rainfall events is an enduring challenge, as such events depend on multi-scale interactions, and the model configurations such as grid spacing, physical parameterization and initialization. With this background, the WRF model is implemented in this study to investigate the impact of different processes on extreme rainfall simulation, by considering a representative event that occurred during 15-18 June 2013 over the Ganga Basin in India, which is located at the foothills of the Himalayas. This event is simulated with ensembles involving four different microphysics (MP), two cumulus (CU) parameterizations, two planetary boundary layers (PBLs) and two land surface physics options, as well as different resolutions (grid spacing) within the WRF model. The simulated rainfall is evaluated against the observations from 18 rain gauges and the Tropical Rainfall Measuring Mission Multi-Satellite Precipitation Analysis (TMPA) 3B42RT version 7 data. From the analysis, it should be noted that the choice of MP scheme influences the spatial pattern of rainfall, while the choice of PBL and CU parameterizations influences the magnitude of rainfall in the model simulations. Further, the WRF run with Goddard MP, Mellor-Yamada-Janjic PBL and Betts-Miller-Janjic CU scheme is found to perform best in simulating this heavy rain event. The selected configuration is evaluated for several heavy to extremely heavy rainfall events that occurred across different months of the monsoon season in the region. The model performance improved through incorporation of detailed land surface processes involving prognostic soil moisture evolution in Noah scheme compared to the simple Slab model. To analyse the effect of model grid spacing, two sets of downscaling ratios - (i) 1 : 3, global to regional (G2R) scale and (ii) 1 : 9, global to convection-permitting scale (G2C) - are employed. Results indicate that a higher downscaling ratio (G2C) causes higher variability and consequently large errors in the simulations. Therefore, G2R is adopted as a suitable choice for simulating heavy rainfall event in the present case study. Further, the WRF-simulated rainfall is found to exhibit less bias when compared with the NCEP FiNaL (FNL) reanalysis data.

New, Improved Goddard Bulk-Microphysical Schemes for Studying Precipitation Processes in WRF

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo

2007-01-01

An improved bulk microphysical parameterization is implemented into the Weather Research and Forecasting ()VRF) model. This bulk microphysical scheme has three different options, 2ICE (cloud ice & snow), 3ICE-graupel (cloud ice, snow & graupel) and 3ICE-hail (cloud ice, snow & hail). High-resolution model simulations are conducted to examine the impact of microphysical schemes on two different weather events (a midlatitude linear convective system and an Atlantic hurricane). The results suggest that microphysics has a major impact on the organization and precipitation processes associated with a summer midlatitude convective line system. The Goddard 3ICE scheme with a cloud ice-snow-hail configuration agreed better with observations in terms of rainfall intensity and a narrow convective line than did simulations with a cloud ice-snow-graupel or cloud ice-snow (i.e., 2ICE) configuration. This is because the 3ICE-hail scheme includes dense ice precipitating (hail) particle with very fast fall speed (over 10 in For an Atlantic hurricane case, the Goddard microphysical schemes had no significant impact on the track forecast but did affect the intensity slightly. The improved Goddard schemes are also compared with WRF's three other 3ICE bulk microphysical schemes: WSM6, Purdue-Lin and Thompson. For the summer midlatitude convective line system, all of the schemes resulted in simulated precipitation events that were elongated in the southwest-northeast direction in qualitative agreement with the observed feature. However, the Goddard 3ICE scheme with the hail option and the Thompson scheme agree better with observations in terms of rainfall intensity, expect that the Goddard scheme simulated more heavy rainfall (over 48 mm/h). For the Atlantic hurricane case, none of the schemes had a significant impact on the track forecast; however, the simulated intensity using the Purdue-Lin scheme was much stronger than the other schemes. The vertical distributions of model simulated cloud species (i.e., snow) are quite sensitive to microphysical schemes, which is an important issue for future verification against satellite retrievals. Both the Purdue-Lin and WSM6 schemes simulated very little snow compared to the other schemes for both the midlatitude convective line and hurricane cases. Sensitivity tests are performed for these two WRF schemes to identify that snow productions could be increased by increasing the snow intercept, turning off the auto-conversion from snow to graupel and reducing the transfer processes from cloud-sized particles to precipitation-sized ice.

An evaluation of WRF microphysics schemes for simulating the warm-type heavy rain over the Korean peninsula

NASA Astrophysics Data System (ADS)

Song, Hwan-Jin; Sohn, Byung-Ju

2018-01-01

The Korean peninsula is the region of distinctly showing the heavy rain associated with relatively low storm height and small ice water content in the upper part of cloud system (i.e., so-called warm-type heavy rainfall). The satellite observations for the warmtype rain over Korea led to a conjecture that the cloud microphysics parameterization suitable for the continental deep convection may not work well for the warm-type heavy rainfall over the Korean peninsula. Therefore, there is a growing need to examine the performance of cloud microphysics schemes for simulating the warm-type heavy rain structures over the Korean peninsula. This study aims to evaluate the capabilities of eight microphysics schemes in the Weather Research and Forecasting (WRF) model how warmtype heavy rain structures can be simulated, in reference to the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) reflectivity measurements. The results indicate that the WRF Double Moment 6-class (WDM6) scheme simulated best the vertical structure of warm-type heavy rain by virtue of a reasonable collisioncoalescence process between liquid droplets and the smallest amount of snow. Nonetheless the WDM6 scheme appears to have limitations that need to be improved upon for a realistic reflectivity structure, in terms of the reflectivity slope below the melting layer, discontinuity in reflectivity profiles around the melting layer, and overestimation of upper-level reflectivity due to high graupel content.

An Evaluation of WRF Microphysics Schemes for Simulating the Warm-Type Heavy Rain over the Korean Peninsula

NASA Astrophysics Data System (ADS)

Song, Hwan-Jin; Sohn, Byung-Ju

2018-05-01

The Korean peninsula is the region of distinctly showing the heavy rain associated with relatively low storm height and small ice water content in the upper part of cloud system (i.e., so-called warm-type heavy rainfall). The satellite observations for the warm-type rain over Korea led to a conjecture that the cloud microphysics parameterization suitable for the continental deep convection may not work well for the warm-type heavy rainfall over the Korean peninsula. Therefore, there is a growing need to examine the performance of cloud microphysics schemes for simulating the warm-type heavy rain structures over the Korean peninsula. This study aims to evaluate the capabilities of eight microphysics schemes in the Weather Research and Forecasting (WRF) model how warm-type heavy rain structures can be simulated, in reference to the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) reflectivity measurements. The results indicate that the WRF Double Moment 6-class (WDM6) scheme simulated best the vertical structure of warm-type heavy rain by virtue of a reasonable collision-coalescence process between liquid droplets and the smallest amount of snow. Nonetheless the WDM6 scheme appears to have limitations that need to be improved upon for a realistic reflectivity structure, in terms of the reflectivity slope below the melting layer, discontinuity in reflectivity profiles around the melting layer, and overestimation of upper-level reflectivity due to high graupel content.

Transfer of uncertainty of space-borne high resolution rainfall products at ungauged regions

NASA Astrophysics Data System (ADS)

Tang, Ling

Hydrologically relevant characteristics of high resolution (˜ 0.25 degree, 3 hourly) satellite rainfall uncertainty were derived as a function of season and location using a six year (2002-2007) archive of National Aeronautics and Space Administration (NASA)'s Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) precipitation data. The Next Generation Radar (NEXRAD) Stage IV rainfall data over the continental United States was used as ground validation (GV) data. A geostatistical mapping scheme was developed and tested for transfer (i.e., spatial interpolation) of uncertainty information from GV regions to the vast non-GV regions by leveraging the error characterization work carried out in the earlier step. The open question explored here was, "If 'error' is defined on the basis of independent ground validation (GV) data, how are error metrics estimated for a satellite rainfall data product without the need for much extensive GV data?" After a quantitative analysis of the spatial and temporal structure of the satellite rainfall uncertainty, a proof-of-concept geostatistical mapping scheme (based on the kriging method) was evaluated. The idea was to understand how realistic the idea of 'transfer' is for the GPM era. It was found that it was indeed technically possible to transfer error metrics from a gauged to an ungauged location for certain error metrics and that a regionalized error metric scheme for GPM may be possible. The uncertainty transfer scheme based on a commonly used kriging method (ordinary kriging) was then assessed further at various timescales (climatologic, seasonal, monthly and weekly), and as a function of the density of GV coverage. The results indicated that if a transfer scheme for estimating uncertainty metrics was finer than seasonal scale (ranging from 3-6 hourly to weekly-monthly), the effectiveness for uncertainty transfer worsened significantly. Next, a comprehensive assessment of different kriging methods for spatial transfer (interpolation) of error metrics was performed. Three kriging methods for spatial interpolation are compared, which are: ordinary kriging (OK), indicator kriging (IK) and disjunctive kriging (DK). Additional comparison with the simple inverse distance weighting (IDW) method was also performed to quantify the added benefit (if any) of using geostatistical methods. The overall performance ranking of the kriging methods was found to be as follows: OK=DK > IDW > IK. Lastly, various metrics of satellite rainfall uncertainty were identified for two large continental landmasses that share many similar Koppen climate zones, United States and Australia. The dependence of uncertainty as a function of gauge density was then investigated. The investigation revealed that only the first and second ordered moments of error are most amenable to a Koppen-type climate type classification in different continental landmasses.

Relationships between microbial water quality and environmental conditions in coastal recreational waters: the Fylde coast, UK.

PubMed

Crowther, J; Kay, D; Wyer, M D

2001-12-01

This paper explores ways in which the analysis of microbial data from routine compliance monitoring, in combination with basic environmental data, can provide insight into the factors affecting faecal-indicator organism concentrations in coastal waters. In the case study presented, eight designated bathing waters on the Fylde coast are continuing to exhibit unreliable compliance with the Imperative standards for total coliform (TC) and faecal coliform (FC) concentrations specified in the EU Bathing Water Directive (76/160/EEC), despite significant reductions in geometric mean concentrations following recent major investment in the sewerage infrastructure. Faecal streptococci (FS) concentrations have remained high and have not been improved by the new sewerage schemes. The results suggest that, prior to the schemes, higher bacterial concentrations were strongly associated with rainfall; and sewage sources were important for TC and FC, but less important for FS, which may have been more strongly affected by diffuse catchment sources. In the post-schemes period, catchment sources appear to be of greater significance; rainfall remains as a significant, though less important, predictor; and tide height at time of sampling, together with variables such as sunshine and the proportion of onshore winds (which affect the survival and movement of bacteria that have already entered the coastal waters), assume greater significance. The approach used here provides a cost-effective management tool for the exploratory investigation of any monitoring point that is failing to meet recreational water quality standards.

Mesoscale data assimilation for a local severe rainfall event with the NHM-LETKF system

NASA Astrophysics Data System (ADS)

Kunii, M.

2013-12-01

This study aims to improve forecasts of local severe weather events through data assimilation and ensemble forecasting approaches. Here, the local ensemble transform Kalman filter (LETKF) is implemented with the Japan Meteorological Agency's nonhydrostatic model (NHM). The newly developed NHM-LETKF contains an adaptive inflation scheme and a spatial covariance localization scheme with physical distance. One-way nested analysis in which a finer-resolution LETKF is conducted by using the outputs of an outer model also becomes feasible. These new contents should enhance the potential of the LETKF for convective scale events. The NHM-LETKF is applied to a local severe rainfall event in Japan in 2012. Comparison of the root mean square errors between the model first guess and analysis reveals that the system assimilates observations appropriately. Analysis ensemble spreads indicate a significant increase around the time torrential rainfall occurred, which would imply an increase in the uncertainty of environmental fields. Forecasts initialized with LETKF analyses successfully capture intense rainfalls, suggesting that the system can work effectively for local severe weather. Investigation of probabilistic forecasts by ensemble forecasting indicates that this could become a reliable data source for decision making in the future. A one-way nested data assimilation scheme is also tested. The experiment results demonstrate that assimilation with a finer-resolution model provides an advantage in the quantitative precipitation forecasting of local severe weather conditions.

Effects of Irrigation and Rainfall on the Population Dynamics of Rift Valley Fever and Other Arbovirus Mosquito Vectors in the Epidemic-Prone Tana River County, Kenya.

PubMed

Sang, R; Lutomiah, J; Said, M; Makio, A; Koka, H; Koskei, E; Nyunja, A; Owaka, S; Matoke-Muhia, D; Bukachi, S; Lindahl, J; Grace, D; Bett, B

2017-03-01

Rift Valley fever (RVF) is a mosquito-borne viral zoonosis that is found in most regions of sub-Saharan Africa, and it affects humans, livestock, and some wild ungulates. Outbreaks are precipitated by an abundance of mosquito vectors associated with heavy persistent rainfall with flooding. We determined the impact of flood-irrigation farming and the effect of environmental parameters on the ecology and densities of primary and secondary vectors of the RVF virus (RVFV) in an RVF-epidemic hotspot in the Tana River Basin, Kenya. Mosquito sampling was conducted in farms and villages (settlements) in an irrigated and a neighboring nonirrigated site (Murukani). Overall, a significantly higher number of mosquitoes were collected in farms in the irrigation scheme compared with villages in the same area (P < 0.001), or farms (P < 0.001), and villages (P = 0.03) in Murukani. In particular, key primary vectors of RVFV, Aedes mcintoshi Marks and Aedes ochraceous Theobald, were more prevalent in the farms compared with villages in the irrigation scheme (P = 0.001) both during the dry and the wet seasons. Similarly, there was a greater abundance of secondary vectors, particularly Culex univittatus Theobald and Culex pipiens (L.) in the irrigation scheme than in the Murukani area. Rainfall and humidity were positively correlated with mosquito densities, particularly the primary vectors. Adult floodwater mosquitoes and Mansonia spp. were collected indoors; immatures of Ae. mcintoshi and secondary vectors were collected in the irrigation drainage canals, whereas those of Ae. ochraceous and Aedes sudanensis Theobald were missing from these water bodies. In conclusion, irrigation in RVF endemic areas provides conducive resting and breeding conditions for vectors of RVFV and other endemic arboviruses. © The Authors 2016. Published by Oxford University Press on behalf of Entomological Society of America.

Studying Precipitation Processes in WRF with Goddard Bulk Microphysics in Comparison with Other Microphysical Schemes

NASA Technical Reports Server (NTRS)

Tao, W.K.; Shi, J.J.; Braun, S.; Simpson, J.; Chen, S.S.; Lang, S.; Hong, S.Y.; Thompson, G.; Peters-Lidard, C.

2009-01-01

A Goddard bulk microphysical parameterization is implemented into the Weather Research and Forecasting (WRF) model. This bulk microphysical scheme has three different options, 2ICE (cloud ice & snow), 3ICE-graupel (cloud ice, snow & graupel) and 3ICE-hail (cloud ice, snow & hail). High-resolution model simulations are conducted to examine the impact of microphysical schemes on different weather events: a midlatitude linear convective system and an Atlantic hurricane. The results suggest that microphysics has a major impact on the organization and precipitation processes associated with a summer midlatitude convective line system. The Goddard 3ICE scheme with the cloud ice-snow-hail configuration agreed better with observations ill of rainfall intensity and having a narrow convective line than did simulations with the cloud ice-snow-graupel and cloud ice-snow (i.e., 2ICE) configurations. This is because the Goddard 3ICE-hail configuration has denser precipitating ice particles (hail) with very fast fall speeds (over 10 m/s) For an Atlantic hurricane case, the Goddard microphysical scheme (with 3ICE-hail, 3ICE-graupel and 2ICE configurations) had no significant impact on the track forecast but did affect the intensity slightly. The Goddard scheme is also compared with WRF's three other 3ICE bulk microphysical schemes: WSM6, Purdue-Lin and Thompson. For the summer midlatitude convective line system, all of the schemes resulted in simulated precipitation events that were elongated in southwest-northeast direction in qualitative agreement with the observed feature. However, the Goddard 3ICE-hail and Thompson schemes were closest to the observed rainfall intensities although the Goddard scheme simulated more heavy rainfall (over 48 mm/h). For the Atlantic hurricane case, none of the schemes had a significant impact on the track forecast; however, the simulated intensity using the Purdue-Lin scheme was much stronger than the other schemes. The vertical distributions of model-simulated cloud species (e.g., snow) are quite sensitive to the microphysical schemes, which is an issue for future verification against satellite retrievals. Both the Purdue-Lin and WSM6 schemes simulated very little snow compared to the other schemes for both the midlatitude convective line and hurricane case. Sensitivity tests with these two schemes showed that increasing the snow intercept, turning off the auto-conversion from snow to graupel, eliminating dry growth, and reducing the transfer processes from cloud-sized particles to precipitation-sized ice collectively resulted in a net increase in those schemes' snow amounts.

Convective rainfall estimation from digital GOES-1 infrared data

NASA Technical Reports Server (NTRS)

Sickler, G. L.; Thompson, A. H.

1979-01-01

An investigation was conducted to determine the feasibility of developing and objective technique for estimating convective rainfall from digital GOES-1 infrared data. The study area was a 240 km by 240 km box centered on College Station, Texas (Texas A and M University). The Scofield and Oliver (1977) rainfall estimation scheme was adapted and used with the digital geostationary satellite data. The concept of enhancement curves with respect to rainfall approximation is discussed. Raingage rainfall analyses and satellite-derived rainfall estimation analyses were compared. The correlation for the station data pairs (observed versus estimated rainfall amounts) for the convective portion of the storm was 0.92. It was demonstrated that a fairly accurate objective rainfall technique using digital geostationary infrared satellite data is feasible. The rawinsonde and some synoptic data that were used in this investigation came from NASA's Atmospheric Variability Experiment, AVE 7.

Spatial-temporal variability of soil moisture and its estimation across scales

NASA Astrophysics Data System (ADS)

Brocca, L.; Melone, F.; Moramarco, T.; Morbidelli, R.

2010-02-01

The soil moisture is a quantity of paramount importance in the study of hydrologic phenomena and soil-atmosphere interaction. Because of its high spatial and temporal variability, the soil moisture monitoring scheme was investigated here both for soil moisture retrieval by remote sensing and in view of the use of soil moisture data in rainfall-runoff modeling. To this end, by using a portable Time Domain Reflectometer, a sequence of 35 measurement days were carried out within a single year in seven fields located inside the Vallaccia catchment, central Italy, with area of 60 km2. Every sampling day, soil moisture measurements were collected at each field over a regular grid with an extension of 2000 m2. The optimization of the monitoring scheme, with the aim of an accurate mean soil moisture estimation at the field and catchment scale, was addressed by the statistical and the temporal stability. At the field scale, the number of required samples (NRS) to estimate the field-mean soil moisture within an accuracy of 2%, necessary for the validation of remotely sensed soil moisture, ranged between 4 and 15 for almost dry conditions (the worst case); at the catchment scale, this number increased to nearly 40 and it refers to almost wet conditions. On the other hand, to estimate the mean soil moisture temporal pattern, useful for rainfall-runoff modeling, the NRS was found to be lower. In fact, at the catchment scale only 10 measurements collected in the most "representative" field, previously determined through the temporal stability analysis, can reproduce the catchment-mean soil moisture with a determination coefficient, R2, higher than 0.96 and a root-mean-square error, RMSE, equal to 2.38%. For the "nonrepresentative" fields the accuracy in terms of RMSE decreased, but similar R2 coefficients were found. This insight can be exploited for the sampling in a generic field when it is sufficient to know an index of soil moisture temporal pattern to be incorporated in conceptual rainfall-runoff models. The obtained results can address the soil moisture monitoring network design from which a reliable soil moisture temporal pattern at the catchment scale can be derived.

Application of two direct runoff prediction methods in Puerto Rico

USGS Publications Warehouse

Sepulveda, N.

1997-01-01

Two methods for predicting direct runoff from rainfall data were applied to several basins and the resulting hydrographs compared to measured values. The first method uses a geomorphology-based unit hydrograph to predict direct runoff through its convolution with the excess rainfall hyetograph. The second method shows how the resulting hydraulic routing flow equation from a kinematic wave approximation is solved using a spectral method based on the matrix representation of the spatial derivative with Chebyshev collocation and a fourth-order Runge-Kutta time discretization scheme. The calibrated Green-Ampt (GA) infiltration parameters are obtained by minimizing the sum, over several rainfall events, of absolute differences between the total excess rainfall volume computed from the GA equations and the total direct runoff volume computed from a hydrograph separation technique. The improvement made in predicting direct runoff using a geomorphology-based unit hydrograph with the ephemeral and perennial stream network instead of the strictly perennial stream network is negligible. The hydraulic routing scheme presented here is highly accurate in predicting the magnitude and time of the hydrograph peak although the much faster unit hydrograph method also yields reasonable results.

Belowground Controls on the Dynamics of Plant Communities

NASA Astrophysics Data System (ADS)

Sivandran, G.

2013-12-01

Arid regions are characterized by high variability in the arrival of rainfall, and species found in these areas have adapted mechanisms to ensure the capture of this scarce resource. In particular, the rooting strategies employed by vegetation can be critical to their survival. These rooting strategies also dictate the competitive outcomes within plant communities. A dynamic rooting scheme was incorporated into tRIBS+VEGGIE (a physically-based, distributed ecohydrologic model). The dynamic rooting scheme allows vegetation the freedom to alter its rooting profile in response to changes in rainfall and soil conditions, in a way that more closely mimics observed phenotypic plasticity. A simple competition-colonization model was combined with the new dynamic root scheme to explore the role of root adaptability in plant competition and landscape evolution in semi-arid environments. The influence of model representation of rooting strategy on the long term plant community composition

Predictability of Seasonal Rainfall over the Greater Horn of Africa

NASA Astrophysics Data System (ADS)

Ngaina, J. N.

2016-12-01

The El Nino-Southern Oscillation (ENSO) is a primary mode of climate variability in the Greater of Africa (GHA). The expected impacts of climate variability and change on water, agriculture, and food resources in GHA underscore the importance of reliable and accurate seasonal climate predictions. The study evaluated different model selection criteria which included the Coefficient of determination (R2), Akaike's Information Criterion (AIC), Bayesian Information Criterion (BIC), and the Fisher information approximation (FIA). A forecast scheme based on the optimal model was developed to predict the October-November-December (OND) and March-April-May (MAM) rainfall. The predictability of GHA rainfall based on ENSO was quantified based on composite analysis, correlations and contingency tables. A test for field-significance considering the properties of finiteness and interdependence of the spatial grid was applied to avoid correlations by chance. The study identified FIA as the optimal model selection criterion. However, complex model selection criteria (FIA followed by BIC) performed better compared to simple approach (R2 and AIC). Notably, operational seasonal rainfall predictions over the GHA makes of simple model selection procedures e.g. R2. Rainfall is modestly predictable based on ENSO during OND and MAM seasons. El Nino typically leads to wetter conditions during OND and drier conditions during MAM. The correlations of ENSO indices with rainfall are statistically significant for OND and MAM seasons. Analysis based on contingency tables shows higher predictability of OND rainfall with the use of ENSO indices derived from the Pacific and Indian Oceans sea surfaces showing significant improvement during OND season. The predictability based on ENSO for OND rainfall is robust on a decadal scale compared to MAM. An ENSO-based scheme based on an optimal model selection criterion can thus provide skillful rainfall predictions over GHA. This study concludes that the negative phase of ENSO (La Niña) leads to dry conditions while the positive phase of ENSO (El Niño) anticipates enhanced wet conditions

A Regional Model for Malaria Vector Developmental Habitats Evaluated Using Explicit, Pond-Resolving Surface Hydrology Simulations.

PubMed

Asare, Ernest Ohene; Tompkins, Adrian Mark; Bomblies, Arne

2016-01-01

Dynamical malaria models can relate precipitation to the availability of vector breeding sites using simple models of surface hydrology. Here, a revised scheme is developed for the VECTRI malaria model, which is evaluated alongside the default scheme using a two year simulation by HYDREMATS, a 10 metre resolution, village-scale model that explicitly simulates individual ponds. Despite the simplicity of the two VECTRI surface hydrology parametrization schemes, they can reproduce the sub-seasonal evolution of fractional water coverage. Calibration of the model parameters is required to simulate the mean pond fraction correctly. The default VECTRI model tended to overestimate water fraction in periods subject to light rainfall events and underestimate it during periods of intense rainfall. This systematic error was improved in the revised scheme by including the a parametrization for surface run-off, such that light rainfall below the initial abstraction threshold does not contribute to ponds. After calibration of the pond model, the VECTRI model was able to simulate vector densities that compared well to the detailed agent based model contained in HYDREMATS without further parameter adjustment. Substituting local rain-gauge data with satellite-retrieved precipitation gave a reasonable approximation, raising the prospects for regional malaria simulations even in data sparse regions. However, further improvements could be made if a method can be derived to calibrate the key hydrology parameters of the pond model in each grid cell location, possibly also incorporating slope and soil texture.

A Regional Model for Malaria Vector Developmental Habitats Evaluated Using Explicit, Pond-Resolving Surface Hydrology Simulations

PubMed Central

Asare, Ernest Ohene; Tompkins, Adrian Mark; Bomblies, Arne

2016-01-01

Dynamical malaria models can relate precipitation to the availability of vector breeding sites using simple models of surface hydrology. Here, a revised scheme is developed for the VECTRI malaria model, which is evaluated alongside the default scheme using a two year simulation by HYDREMATS, a 10 metre resolution, village-scale model that explicitly simulates individual ponds. Despite the simplicity of the two VECTRI surface hydrology parametrization schemes, they can reproduce the sub-seasonal evolution of fractional water coverage. Calibration of the model parameters is required to simulate the mean pond fraction correctly. The default VECTRI model tended to overestimate water fraction in periods subject to light rainfall events and underestimate it during periods of intense rainfall. This systematic error was improved in the revised scheme by including the a parametrization for surface run-off, such that light rainfall below the initial abstraction threshold does not contribute to ponds. After calibration of the pond model, the VECTRI model was able to simulate vector densities that compared well to the detailed agent based model contained in HYDREMATS without further parameter adjustment. Substituting local rain-gauge data with satellite-retrieved precipitation gave a reasonable approximation, raising the prospects for regional malaria simulations even in data sparse regions. However, further improvements could be made if a method can be derived to calibrate the key hydrology parameters of the pond model in each grid cell location, possibly also incorporating slope and soil texture. PMID:27003834

Applying the WRF Double-Moment Six-Class Microphysics Scheme in the GRAPES_Meso Model: A Case Study

NASA Astrophysics Data System (ADS)

Zhang, Meng; Wang, Hong; Zhang, Xiaoye; Peng, Yue; Che, Huizheng

2018-04-01

This study incorporated the Weather Research and Forecasting (WRF) model double-moment 6-class (WDM6) microphysics scheme into the mesoscale version of the Global/Regional Assimilation and PrEdiction System (GRAPES_Meso). A rainfall event that occurred during 3-5 June 2015 around Beijing was simulated by using the WDM6, the WRF single-moment 6-class scheme (WSM6), and the NCEP 5-class scheme, respectively. The results show that both the distribution and magnitude of the rainfall simulated with WDM6 were more consistent with the observation. Compared with WDM6, WSM6 simulated larger cloud liquid water content, which provided more water vapor for graupel growth, leading to increased precipitation in the cold-rain processes. For areas with the warmrain processes, the sensitivity experiments using WDM6 showed that an increase in cloud condensation nuclei (CCN) number concentration led to enhanced CCN activation ratio and larger cloud droplet number concentration ( N c) but decreased cloud droplet effective diameter. The formation of more small-size cloud droplets resulted in a decrease in raindrop number concentration ( N r), inhibiting the warm-rain processes, thus gradually decreasing the amount of precipitation. For areas mainly with the cold-rain processes, the overall amount of precipitation increased; however, it gradually decreased when the CCN number concentration reached a certain magnitude. Hence, the effect of CCN number concentration on precipitation exhibits significant differences in different rainfall areas of the same precipitation event.

Variational Continuous Assimilation of TMI and SSM/I Rain Rates: Impact on GEOS-3 Hurricane Analyses and Forecasts

NASA Technical Reports Server (NTRS)

Hou, Arthur Y.; Zhang, Sara Q.; Reale, Oreste

2003-01-01

We describe a variational continuous assimilation (VCA) algorithm for assimilating tropical rainfall data using moisture and temperature tendency corrections as the control variable to offset model deficiencies. For rainfall assimilation, model errors are of special concern since model-predicted precipitation is based on parameterized moist physics, which can have substantial systematic errors. This study examines whether a VCA scheme using the forecast model as a weak constraint offers an effective pathway to precipitation assimilation. The particular scheme we exarnine employs a '1+1' dimension precipitation observation operator based on a 6-h integration of a column model of moist physics from the Goddard Earth Observing System (GEOS) global data assimilation system DAS). In earlier studies, we tested a simplified version of this scheme and obtained improved monthly-mean analyses and better short-range forecast skills. This paper describes the full implementation ofthe 1+1D VCA scheme using background and observation error statistics, and examines how it may improve GEOS analyses and forecasts of prominent tropical weather systems such as hurricanes. Parallel assimilation experiments with and without rainfall data for Hurricanes Bonnie and Floyd show that assimilating 6-h TMI and SSM/I surfice rain rates leads to more realistic storm features in the analysis, which, in turn, provide better initial conditions for 5-day storm track prediction and precipitation forecast. These results provide evidence that addressing model deficiencies in moisture tendency may be crucial to making effective use of precipitation information in data assimilation.

Recursive estimators of mean-areal and local bias in precipitation products that account for conditional bias

NASA Astrophysics Data System (ADS)

Zhang, Yu; Seo, Dong-Jun

2017-03-01

This paper presents novel formulations of Mean field bias (MFB) and local bias (LB) correction schemes that incorporate conditional bias (CB) penalty. These schemes are based on the operational MFB and LB algorithms in the National Weather Service (NWS) Multisensor Precipitation Estimator (MPE). By incorporating CB penalty in the cost function of exponential smoothers, we are able to derive augmented versions of recursive estimators of MFB and LB. Two extended versions of MFB algorithms are presented, one incorporating spatial variation of gauge locations only (MFB-L), and the second integrating both gauge locations and CB penalty (MFB-X). These two MFB schemes and the extended LB scheme (LB-X) are assessed relative to the original MFB and LB algorithms (referred to as MFB-O and LB-O, respectively) through a retrospective experiment over a radar domain in north-central Texas, and through a synthetic experiment over the Mid-Atlantic region. The outcome of the former experiment indicates that introducing the CB penalty to the MFB formulation leads to small, but consistent improvements in bias and CB, while its impacts on hourly correlation and Root Mean Square Error (RMSE) are mixed. Incorporating CB penalty in LB formulation tends to improve the RMSE at high rainfall thresholds, but its impacts on bias are also mixed. The synthetic experiment suggests that beneficial impacts are more conspicuous at low gauge density (9 per 58,000 km2), and tend to diminish at higher gauge density. The improvement at high rainfall intensity is partly an outcome of the conservativeness of the extended LB scheme. This conservativeness arises in part from the more frequent presence of negative eigenvalues in the extended covariance matrix which leads to no, or smaller incremental changes to the smoothed rainfall amounts.

Frequency analysis of urban runoff quality in an urbanizing catchment of Shenzhen, China

NASA Astrophysics Data System (ADS)

Qin, Huapeng; Tan, Xiaolong; Fu, Guangtao; Zhang, Yingying; Huang, Yuefei

2013-07-01

This paper investigates the frequency distribution of urban runoff quality indicators using a long-term continuous simulation approach and evaluates the impacts of proposed runoff control schemes on runoff quality in an urbanizing catchment in Shenzhen, China. Four different indicators are considered to provide a comprehensive assessment of the potential impacts: total runoff depth, event pollutant load, Event Mean Concentration, and peak concentration during a rainfall event. The results obtained indicate that urban runoff quantity and quality in the catchment have significant variations in rainfall events and a very high rate of non-compliance with surface water quality regulations. Three runoff control schemes with the capacity to intercept an initial runoff depth of 5 mm, 10 mm, and 15 mm are evaluated, respectively, and diminishing marginal benefits are found with increasing interception levels in terms of water quality improvement. The effects of seasonal variation in rainfall events are investigated to provide a better understanding of the performance of the runoff control schemes. The pre-flood season has higher risk of poor water quality than other seasons after runoff control. This study demonstrates that frequency analysis of urban runoff quantity and quality provides a probabilistic evaluation of pollution control measures, and thus helps frame a risk-based decision making for urban runoff quality management in an urbanizing catchment.

The Impact of Microphysics and Model Resolution on Precipitation Associated with Typhoon Morakot 2009

NASA Technical Reports Server (NTRS)

Lin, Pay-Liam; Chen, D.; Tao, Wei-Kuo; Shi, Jainn J.; Chang, Mei-Yu

2010-01-01

In recent years, the heavy rainfall that was associated with severe weather events (e.g., typhoons, local heavy precipitation events) has caused significant damages in the economy and loss of human life throughout Taiwan. Especially, the extreme heavy rainfall (over 2500 mm over 24 hours) associated with Typhoon Morakot 2009 caused more than 600 human beings lost and more than $100 million US dollar damage. In this paper, we are using WRF to simulate the precipitation processes associated Typhoon Morakot 2009. The preliminary results indicated that the wrf model with using 2 km grid size and with utilizing the 310E scheme (cloud ice, snow and hail) can simulate more than 2500 mm rainfall over 24 hour integration. In this talk, we will evaluate the performance of the microphysical schemes for the Typhoon Morakot case. In addition, we will examine the impact of model resolution (in both horizontal and vertical) on the Typhoon Morakot case.

A Study of Heavy Precipitation Events in Taiwan During 10-13 August, 1994. Part 2; Mesoscale Model Simulations

NASA Technical Reports Server (NTRS)

Tao, Wei Kuo; Chen, C.-S.; Jia, Y.; Baker, D.; Lang, S.; Wetzel, P.; Lau, W. K.-M.

2001-01-01

Several heavy precipitation episodes occurred over Taiwan from August 10 to 13, 1994. Precipitation patterns and characteristics are quite different between the precipitation events that occurred from August 10 and I I and from August 12 and 13. In Part I (Chen et al. 2001), the environmental situation and precipitation characteristics are analyzed using the EC/TOGA data, ground-based radar data, surface rainfall patterns, surface wind data, and upper air soundings. In this study (Part II), the Penn State/NCAR Mesoscale Model (MM5) is used to study the precipitation characteristics of these heavy precipitation events. Various physical processes (schemes) developed at NASA Goddard Space Flight Center (i.e., cloud microphysics scheme, radiative transfer model, and land-soil-vegetation surface model) have recently implemented into the MM5. These physical packages are described in the paper, Two way interactive nested grids are used with horizontal resolutions of 45, 15 and 5 km. The model results indicated that Cloud physics, land surface and radiation processes generally do not change the location (horizontal distribution) of heavy precipitation. The Goddard 3-class ice scheme produced more rainfall than the 2-class scheme. The Goddard multi-broad-band radiative transfer model reduced precipitation compared to a one-broad band (emissivity) radiation model. The Goddard land-soil-vegetation surface model also reduce the rainfall compared to a simple surface model in which the surface temperature is computed from a Surface energy budget following the "force-re store" method. However, model runs including all Goddard physical processes enhanced precipitation significantly for both cases. The results from these runs are in better agreement with observations. Despite improved simulations using different physical schemes, there are still some deficiencies in the model simulations. Some potential problems are discussed. Sensitivity tests (removing either terrain or radiative processes) are performed to identify the physical processes that determine the precipitation patterns and characteristics for heavy rainfall events. These sensitivity tests indicated that terrain can play a major role in determining the exact location for both precipitation events. The terrain can also play a major role in determining the intensity of precipitation for both events. However, it has a large impact on one event but a smaller one on the other. The radiative processes are also important for determining, the precipitation patterns for one case but. not the other. The radiative processes can also effect the total rainfall for both cases to different extents.

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.

Influences of Appalachian orography on heavy rainfall and rainfall variability associated with the passage of hurricane Isabel by ensemble simulations

NASA Astrophysics Data System (ADS)

Oldaker, Guy; Liu, Liping; Lin, Yuh-Lang

2017-12-01

This study focuses on the heavy rainfall event associated with hurricane Isabel's (2003) passage over the Appalachian mountains of the eastern United States. Specifically, an ensemble consisting of two groups of simulations using the Weather Research and Forecasting model (WRF), with and without topography, is performed to investigate the orographic influences on heavy rainfall and rainfall variability. In general, the simulated ensemble mean with full terrain is able to reproduce the key observed 24-h rainfall amount and distribution, while the flat-terrain mean lacks in this respect. In fact, 30-h rainfall amounts are reduced by 75% with the removal of topography. Rainfall variability is also significantly increased with the presence of orography. Further analysis shows that the complex interaction between the hurricane and terrain along with contributions from varied microphysics, cumulus parametrization, and planetary boundary layer schemes have a pronounced effect on rainfall and rainfall variability. This study follows closely with a previous study, but for a different TC case of Isabel (2003). It is an important sensitivity test for a different TC in a very different environment. This study reveals that the rainfall variability behaves similarly, even with different settings of the environment.

Sensitivity of effective rainfall amount to land use description using GIS tool. Case of a small mediterranean catchment

NASA Astrophysics Data System (ADS)

Payraudeau, S.; Tournoud, M. G.; Cernesson, F.

Distributed modelling in hydrology assess catchment subdivision to take into account physic characteristics. In this paper, we test the effect of land use aggregation scheme on catchment hydrological response. Evolution of intra-subcatchment land use is studied using statistic and entropy methods. The SCS-CN method is used to calculate effective rainfall which is here assimilated to hydrological response. Our purpose is to determine the existence of a critical threshold-area appropriate for the application of hydrological modelling. Land use aggregation effects on effective rainfall is assessed on small mediterranean catchment. The results show that land use aggregation and land use classification type have significant effects on hydrological modelling and in particular on effective rainfall modelling.

A Multiseason Comparison of the Forecast Skills among Three Numerical Models over Southcentral United States

NASA Astrophysics Data System (ADS)

Lu, D.; Reddy, S.

2005-05-01

During the summer 2003 and winter 2003-2004, three mesoscale numerical models, the fifth-generation Pennsylvania State University-NCAR Mesoscale Model (MM5), Navy's Coupled Ocean/Atmospheric Mesoscale Prediction System (COAMPS) and the Weather Research and Forecasting model (WRF), were operationally run at a horizontal resolution of 27 km twice daily in Jackson State University (JSU). Three models were run by the initial and lateral boundary conditions from AVN data. The purpose of this paper is to evaluate the performances of three models during these two seasons. It was found that the temporal variation of distribution and strength of mean error (ME) biases at 12, 24 and 36h was rather weak for surface temperature, sea level pressure and surface wind speed. During two seasons, the MM5 underpredicted the seasonal precipitation while the COAMPS and WRF overpredicted. This is consistent with the statistical score analyses of rainfall. The Bias scores revealed that the MM5 yielded an underprediction of precipitation, especially for heavier rainfall events. Due to the under estimate of rainfall areas and strength, the MM5 presented the lower TS, POD and KSS scores at lighter rainfall events compared to the COAMPS and WRF. At moderate to heavier thresholds, three models produced rather low KSS and POD scores that are consistent with the high FAR values. The WRF skills in predicting precipitation heavily depend on the performance of cumulus parameterization scheme. Instead of Kain-Fritsch scheme, using other two schemes, Grell-Devenyi and Bette-Miller-Janjic, in the WRF for warm season 2003 demonstrated that the precipitation overprediction had been efficiently suppressed. Overall, the performances of three models revealed that the best skill is at 12h and the worst at 36h.

Evaluating the impacts of cumulus, land surface and ocean surface schemes on summertime rainfall simulations over East-to-southeast Asia and the western north Pacific by RegCM4

NASA Astrophysics Data System (ADS)

Li, Yu-Bin; Tam, Chi-Yung; Huang, Wan-Ru; Cheung, Kevin K. W.; Gao, Zhiqiu

2016-04-01

This study evaluates the sensitivity of summertime rainfall simulations over East-to-southeast Asia and the western north Pacific in the regional climate model version 4 (RegCM4) to cumulus (including Grell with Arakawa-Schubert type closure, Grell with Fritsch-Chappell type closure, and Emanuel), land surface (Biosphere-atmosphere transfer scheme or BATS, and the community land model or CLM) and ocean surface (referred to as Zeng1, Zeng2 and BATS1e in the model) schemes by running the model with different combinations of these parameterization packages. For each of these experiments, ensemble integration of the model was carried out in the extended boreal summer of May-October from 1998 to 2007. The simulated spatial distribution, intensity and inter-annual variation of the precipitation, latent heat flux, position of the subtropical high and tropical cyclone genesis patterns from these numerical experiments were analyzed. Examinations show that the combination of Emanuel, CLM and Zeng2 (E-C-Z2) yields the best overall results, consistent with the fact that physical mechanisms considered in E-C-Z2 tend to be more comprehensive in comparison with the others. Additionally, the rainfall quantity is found very sensitive to sea surface roughness length, and the reduction of the roughness length constant (from 2 × 10-4 to 5 × 10-5 m) in our modified BATS1e mitigates the drastic overestimation of latent heat flux and rainfall, and is therefore preferable to the default value for simulations in the western north Pacific region in RegCM4.

Transferring Error Characteristics of Satellite Rainfall Data from Ground Validation (gauged) into Non-ground Validation (ungauged)

NASA Astrophysics Data System (ADS)

Tang, L.; Hossain, F.

2009-12-01

Understanding the error characteristics of satellite rainfall data at different spatial/temporal scales is critical, especially when the scheduled Global Precipitation Mission (GPM) plans to provide High Resolution Precipitation Products (HRPPs) at global scales. Satellite rainfall data contain errors which need ground validation (GV) data for characterization, while satellite rainfall data will be most useful in the regions that are lacking in GV. Therefore, a critical step is to develop a spatial interpolation scheme for transferring the error characteristics of satellite rainfall data from GV regions to Non-GV regions. As a prelude to GPM, The TRMM Multi-satellite Precipitation Analysis (TMPA) products of 3B41RT and 3B42RT (Huffman et al., 2007) over the US spanning a record of 6 years are used as a representative example of satellite rainfall data. Next Generation Radar (NEXRAD) Stage IV rainfall data are used as the reference for GV data. Initial work by the authors (Tang et al., 2009, GRL) has shown promise in transferring error from GV to Non-GV regions, based on a six-year climatologic average of satellite rainfall data assuming only 50% of GV coverage. However, this transfer of error characteristics needs to be investigated for a range of GV data coverage. In addition, it is also important to investigate if proxy-GV data from an accurate space-borne sensor, such as the TRMM PR (or the GPM DPR), can be leveraged for the transfer of error at sparsely gauged regions. The specific question we ask in this study is, “what is the minimum coverage of GV data required for error transfer scheme to be implemented at acceptable accuracy in hydrological relevant scale?” Three geostatistical interpolation methods are compared: ordinary kriging, indicator kriging and disjunctive kriging. Various error metrics are assessed for transfer such as, Probability of Detection for rain and no rain, False Alarm Ratio, Frequency Bias, Critical Success Index, RMSE etc. Understanding the proper space-time scales at which these metrics can be reasonably transferred is also explored in this study. Keyword: Satellite rainfall, error transfer, spatial interpolation, kriging methods.

Ability of WRF to Simulate Rainfall Distribution Over West Africa: Role of Horizontal Resolution and Dynamical Processes

NASA Astrophysics Data System (ADS)

Kouadio, K.; Konare, A.; Bastin, S.; Ajayi, V. O.

2016-12-01

This research work focused on the thorny problem of the representation of rainfall over West Africa and particularly in the Gulf of Guinea and its surroundings by Regional Climate Models (RCMs). The sensitivities of Weather Research and Forecasting (WRF) Model are tested for changes in horizontal resolution (convective permitting versus parameterized) on the replication of West African Climate in year 2014 and also changes in microphysics (MP) and planetary boundary layer (PBL) schemes on June 2014. The sensitivity to horizontal resolution study show that both runs at 24km and 4km (explicit convection) resolution fairly replicate the general distribution of the rainfall over West African region. The analysis also reveals a good replication of the dynamical features of West African monsoon system including Tropical Easterly Jet (TEJ), African Easterly Jet (AEJ), monsoon flow and the West African Heat Low (WAHL). Some differences have been noticed between WRF and ERA-interim outputs irrespective to the spectral nudging used in the experiment which then suggest strong interactions between scales. The link between the seasonal displacement of the WAHL and the spatial distribution of the rainfall and the Sahelian onset is confirmed in this study. The results also show an improvement on the replication of rainfall with the very high resolution run observed at daily scale over the Sahel while a dry bias is observed in WRF simulations of the rainfall over Ivorian Coast and in the Gulf of Guinea. Generally, over the Guinean coast the high resolution run did not provide subsequent improvement on the replication of rainfall. The sensitivity of WRF to MP and PBL on rainfall replication study reveals that the most significant added value over the Guinean coast and surroundings area is provided by the configurations that used the PBL Asymmetric Convective Model V2 (ACM2) suggesting more influence of the PBL compared to MP. The change on microphysics and planetary boundary layer schemes in general, seems to have less effect on the explicit runs into the replication of the rainfall over the Gulf of Guinea and the surroundings seaboard.

Progress Towards Achieving the Challenge of Indian Summer Monsoon Climate Simulation in a Coupled Ocean-Atmosphere Model

NASA Astrophysics Data System (ADS)

Hazra, Anupam; Chaudhari, Hemantkumar S.; Saha, Subodh Kumar; Pokhrel, Samir; Goswami, B. N.

2017-10-01

Simulation of the spatial and temporal structure of the monsoon intraseasonal oscillations (MISOs), which have effects on the seasonal mean and annual cycle of Indian summer monsoon (ISM) rainfall, remains a grand challenge for the state-of-the-art global coupled models. Biases in simulation of the amplitude and northward propagation of MISOs and related dry rainfall bias over ISM region in climate models are limiting the current skill of monsoon prediction. Recent observations indicate that the convective microphysics of clouds may be critical in simulating the observed MISOs. The hypothesis is strongly supported by high fidelity in simulation of the amplitude and space-time spectra of MISO by a coupled climate model, when our physically based modified cloud microphysics scheme is implemented in conjunction with a modified new Simple Arakawa Schubert (nSAS) convective parameterization scheme. Improved simulation of MISOs appears to have been aided by much improved simulation of the observed high cloud fraction and convective to stratiform rain fractions and resulted into a much improved simulation of the ISM rainfall, monsoon onset, and the annual cycle.

El Niño-southern oscillation influences on the Mahaweli streamflow in Sri Lanka

NASA Astrophysics Data System (ADS)

Zubair, Lareef

2003-01-01

Despite advances over the last two decades in the capacity to predict the evolution of the El Niño-southern oscillation (ENSO) phenomenon and advances in understanding of the relationship between ENSO and climate, there has been little use of climate predictions for water resources management in the tropics. As part of an effort to develop such a prediction scheme, the ENSO influences on streamflow and rainfall in the upper catchment of the Mahaweli river in Sri Lanka were investigated with correlation analysis, composite analysis and contingency tables. El Niño conditions were often associated with decreased annual flows and La Niña with increased flows. The relationship of streamflow and rainfall with the ENSO index of NINO3 contrasted between January to September and October to December. During El Niño episodes the streamflow declines from January to September, but from October to December there is no clear relationship. On the other hand, rainfall shows a clear increase from October to December and declines during January, February, March, July and August. The simultaneous correlations of NINO3 with the aggregate January to September streamflow (r = -0.50), with January to September rainfall (r = -0.44) and with October to December rainfall (r = 0.48) are all significant at the 99% level. The correlation between one-season-in-advance NINO3 with both January to September streamflow and October to December rainfall remained significant at the 99% level.This study demonstrates the potential of using ENSO-based predictors for a seasonal hydro-climatic prediction scheme in the Mahaweli basin. It shows the significant contrasts in ENSO influence on rainfall and streamflow due to various hydrological processes. It has demonstrated that the potential for prediction is improved by investigating ENSO influences for the appropriate season for the given river catchment.

Comparison in Schemes for Simulating Depositional Growth of Ice Crystal between Theoretical and Laboratory Data

NASA Astrophysics Data System (ADS)

Zhai, Guoqing; Li, Xiaofan

2015-04-01

The Bergeron-Findeisen process has been simulated using the parameterization scheme for the depositional growth of ice crystal with the temperature-dependent theoretically predicted parameters in the past decades. Recently, Westbrook and Heymsfield (2011) calculated these parameters using the laboratory data from Takahashi and Fukuta (1988) and Takahashi et al. (1991) and found significant differences between the two parameter sets. There are two schemes that parameterize the depositional growth of ice crystal: Hsie et al. (1980), Krueger et al. (1995) and Zeng et al. (2008). In this study, we conducted three pairs of sensitivity experiments using three parameterization schemes and the two parameter sets. The pre-summer torrential rainfall event is chosen as the simulated rainfall case in this study. The analysis of root-mean-squared difference and correlation coefficient between the simulation and observation of surface rain rate shows that the experiment with the Krueger scheme and the Takahashi laboratory-derived parameters produces the best rain-rate simulation. The mean simulated rain rates are higher than the mean observational rain rate. The calculations of 5-day and model domain mean rain rates reveal that the three schemes with Takahashi laboratory-derived parameters tend to reduce the mean rain rate. The Krueger scheme together with the Takahashi laboratory-derived parameters generate the closest mean rain rate to the mean observational rain rate. The decrease in the mean rain rate caused by the Takahashi laboratory-derived parameters in the experiment with the Krueger scheme is associated with the reductions in the mean net condensation and the mean hydrometeor loss. These reductions correspond to the suppressed mean infrared radiative cooling due to the enhanced cloud ice and snow in the upper troposphere.

Comparison of Two Methods for Estimating the Sampling-Related Uncertainty of Satellite Rainfall Averages Based on a Large Radar Data Set

NASA Technical Reports Server (NTRS)

Lau, William K. M. (Technical Monitor); Bell, Thomas L.; Steiner, Matthias; Zhang, Yu; Wood, Eric F.

2002-01-01

The uncertainty of rainfall estimated from averages of discrete samples collected by a satellite is assessed using a multi-year radar data set covering a large portion of the United States. The sampling-related uncertainty of rainfall estimates is evaluated for all combinations of 100 km, 200 km, and 500 km space domains, 1 day, 5 day, and 30 day rainfall accumulations, and regular sampling time intervals of 1 h, 3 h, 6 h, 8 h, and 12 h. These extensive analyses are combined to characterize the sampling uncertainty as a function of space and time domain, sampling frequency, and rainfall characteristics by means of a simple scaling law. Moreover, it is shown that both parametric and non-parametric statistical techniques of estimating the sampling uncertainty produce comparable results. Sampling uncertainty estimates, however, do depend on the choice of technique for obtaining them. They can also vary considerably from case to case, reflecting the great variability of natural rainfall, and should therefore be expressed in probabilistic terms. Rainfall calibration errors are shown to affect comparison of results obtained by studies based on data from different climate regions and/or observation platforms.

Sampling errors for satellite-derived tropical rainfall - Monte Carlo study using a space-time stochastic model

NASA Technical Reports Server (NTRS)

Bell, Thomas L.; Abdullah, A.; Martin, Russell L.; North, Gerald R.

1990-01-01

Estimates of monthly average rainfall based on satellite observations from a low earth orbit will differ from the true monthly average because the satellite observes a given area only intermittently. This sampling error inherent in satellite monitoring of rainfall would occur even if the satellite instruments could measure rainfall perfectly. The size of this error is estimated for a satellite system being studied at NASA, the Tropical Rainfall Measuring Mission (TRMM). First, the statistical description of rainfall on scales from 1 to 1000 km is examined in detail, based on rainfall data from the Global Atmospheric Research Project Atlantic Tropical Experiment (GATE). A TRMM-like satellite is flown over a two-dimensional time-evolving simulation of rainfall using a stochastic model with statistics tuned to agree with GATE statistics. The distribution of sampling errors found from many months of simulated observations is found to be nearly normal, even though the distribution of area-averaged rainfall is far from normal. For a range of orbits likely to be employed in TRMM, sampling error is found to be less than 10 percent of the mean for rainfall averaged over a 500 x 500 sq km area.

Effects of a Simple Convective Organization Scheme in a Two-Plume GCM

NASA Astrophysics Data System (ADS)

Chen, Baohua; Mapes, Brian E.

2018-03-01

A set of experiments is described with the Community Atmosphere Model (CAM5) using a two-plume convection scheme. To represent the differences of organized convection from General Circulation Model (GCM) assumptions of isolated plumes in uniform environments, a dimensionless prognostic "organization" tracer Ω is invoked to lend the second plume a buoyancy advantage relative to the first, as described in Mapes and Neale (2016). When low-entrainment plumes are unconditionally available (Ω = 1 everywhere), deep convection occurs too easily, with consequences including premature (upstream) rainfall in inflows to the deep tropics, excessive convective versus large-scale rainfall, poor relationships to the vapor field, stable bias in the mean state, weak and poor tropical variability, and midday peak in diurnal rainfall over land. Some of these are shown to also be characteristic of CAM4 with its separated deep and shallow convection schemes. When low-entrainment plumes are forbidden by setting Ω = 0 everywhere, some opposite problems can be discerned. In between those extreme cases, an interactive Ω driven by the evaporation of precipitation acts as a local positive feedback loop, concentrating deep convection: In areas of little recent rain, only highly entraining plumes can occur, unfavorable for rain production. This tunable mechanism steadily increases precipitation variance in both space and time, as illustrated here with maps, time-longitude series, and spectra, while avoiding some mean state biases as illustrated with process-oriented diagnostics such as conserved variable profiles and vapor-binned precipitation curves.

Effective control parameters in a deep convection scheme for improved simulation of the Madden-Julian oscillation

NASA Astrophysics Data System (ADS)

Choi, Jin-Ho; Seo, Kyong-Hwan

2017-06-01

This work seeks to find the most effective parameters in a deep convection scheme (relaxed Arakawa-Schubert scheme) of the National Centers of Environmental Prediction Climate Forecast System model for improved simulation of the Madden-Julian Oscillation (MJO). A suite of sensitivity experiments are performed by changing physical components such as the relaxation parameter of mass flux for adjustment of the environment, the evaporation rate from large-scale precipitation, the moisture trigger threshold using relative humidity of the boundary layer, and the fraction of re-evaporation of convective (subgrid-scale) rainfall. Among them, the last two parameters are found to produce a significant improvement. Increasing the strength of these two parameters reduces light rainfall that inhibits complete formation of the tropical convective system or supplies more moisture that help increase a potential energy to large-scale environment in the lower troposphere (especially at 700 hPa), leading to moisture preconditioning favorable for further development and eastward propagation of the MJO. In a more humid environment, more organized MJO structure (i.e., space-time spectral signal, eastward propagation, and tilted vertical structure) is produced.

A new time-space accounting scheme to predict stream water residence time and hydrograph source components at the watershed scale

Treesearch

Takahiro Sayama; Jeffrey J. McDonnell

2009-01-01

Hydrograph source components and stream water residence time are fundamental behavioral descriptors of watersheds but, as yet, are poorly represented in most rainfall-runoff models. We present a new time-space accounting scheme (T-SAS) to simulate the pre-event and event water fractions, mean residence time, and spatial source of streamflow at the watershed scale. We...

A laboratory rainfall simulator to study the soil erosion and runoff water

NASA Astrophysics Data System (ADS)

Cancelo González, Javier; Rial, M. E.; Díaz-Fierros, Francisco

2010-05-01

The soil erosion and the runoff water composition in some areas affected by forest fires or submitted to intensive agriculture are an important factor to keep an account, particularly in sensitive areas like estuary and rias that have a high importance in the socioeconomic development of some regions. An understanding of runoff production indicates the processes by which pollutants reach streams and also indicates the management techniques that might be uses to minimize the discharge of these materials into surface waters. One of the most methodology implemented in the soil erosion studies is a rainfall simulation. This method can reproduce the natural soil degradation processes in field or laboratory experiences. With the aim of improve the rainfall-runoff generation, a laboratory rainfall simulator which incorporates a fan-like intermittent water jet system for rainfall generation were modified. The major change made to the rainfall simulator consist in a system to coupling stainless steel boxes, whose dimensions are 12 x 20 x 45 centimeters, and it allows to place soil samples under the rainfall simulator. Previously these boxes were used to take soil samples in field with more of 20 centimeters of depth, causing the minimum disturbance in their properties and structure. These new implementations in the rainfall simulator also allow collect water samples of runoff in two ways: firstly, the rain water that constituted the overland flow or direct runoff and besides the rain water seeps into the soil by the process of infiltration and contributed to the subsurface runoff. Among main the variables controlled in the rainfall simulations were the soil slope and the intensity and duration of rainfall. With the aim of test the prototype, six soil samples were collected in the same sampling point and subjected to rainfall simulations in laboratory with the same intensity and duration. Two samples will constitute the control test, and they were fully undisturbed, and four samples were subjected to controlled burnings with different fire severity: two samples burnt to 250°C and the other two samples burnt to 450°C. Preliminary laboratory data of soil erosion and surface and subsurface runoff were obtained. The water parameters analysed were: pH, electrical conductivity, temperature (in the moment of sampling) and suspended sediments, ammonium, nitrates, total nitrogen (Kjeldahl method), within 24 hours after sampling.

Scaling Linguistic Characterization of Precipitation Variability

NASA Astrophysics Data System (ADS)

Primo, C.; Gutierrez, J. M.

2003-04-01

Rainfall variability is influenced by changes in the aggregation of daily rainfall. This problem is of great importance for hydrological, agricultural and ecological applications. Rainfall averages, or accumulations, are widely used as standard climatic parameters. However different aggregation schemes may lead to the same average or accumulated values. In this paper we present a fractal method to characterize different aggregation schemes. The method provides scaling exponents characterizing weekly or monthly rainfall patterns for a given station. To this aim, we establish an analogy with linguistic analysis, considering precipitation as a discrete variable (e.g., rain, no rain). Each weekly, or monthly, symbolic precipitation sequence of observed precipitation is then considered as a "word" (in this case, a binary word) which defines a specific weekly rainfall pattern. Thus, each site defines a "language" characterized by the words observed in that site during a period representative of the climatology. Then, the more variable the observed weekly precipitation sequences, the more complex the obtained language. To characterize these languages, we first applied the Zipf's method obtaining scaling histograms of rank ordered frequencies. However, to obtain significant exponents, the scaling must be maintained some orders of magnitude, requiring long sequences of daily precipitation which are not available at particular stations. Thus this analysis is not suitable for applications involving particular stations (such as regionalization). Then, we introduce an alternative fractal method applicable to data from local stations. The so-called Chaos-Game method uses Iterated Function Systems (IFS) for graphically representing rainfall languages, in a way that complex languages define complex graphical patterns. The box-counting dimension and the entropy of the resulting patterns are used as linguistic parameters to quantitatively characterize the complexity of the patterns. We illustrate the high climatological discrimination power of the linguistic parameters in the Iberian peninsula, when compared with other standard techniques (such as seasonal mean accumulated precipitation). As an example, standard and linguistic parameters are used as inputs for a clustering regionalization method, comparing the resulting clusters.

Bias correction method for climate change impact assessment at a basin scale

NASA Astrophysics Data System (ADS)

Nyunt, C.; Jaranilla-sanchez, P. A.; Yamamoto, A.; Nemoto, T.; Kitsuregawa, M.; Koike, T.

2012-12-01

Climate change impact studies are mainly based on the general circulation models GCM and these studies play an important role to define suitable adaptation strategies for resilient environment in a basin scale management. For this purpose, this study summarized how to select appropriate GCM to decrease the certain uncertainty amount in analysis. This was applied to the Pampanga, Angat and Kaliwa rivers in Luzon Island, the main island of Philippine and these three river basins play important roles in irrigation water supply, municipal water source for Metro Manila. According to the GCM scores of both seasonal evolution of Asia summer monsoon and spatial correlation and root mean squared error of atmospheric variables over the region, finally six GCM is chosen. Next, we develop a complete, efficient and comprehensive statistical bias correction scheme covering extremes events, normal rainfall and frequency of dry period. Due to the coarse resolution and parameterization scheme of GCM, extreme rainfall underestimation, too many rain days with low intensity and poor representation of local seasonality have been known as bias of GCM. Extreme rainfall has unusual characteristics and it should be focused specifically. Estimated maximum extreme rainfall is crucial for planning and design of infrastructures in river basin. Developing countries have limited technical, financial and management resources for implementing adaptation measures and they need detailed information of drought and flood for near future. Traditionally, the analysis of extreme has been examined using annual maximum series (AMS) adjusted to a Gumbel or Lognormal distribution. The drawback is the loss of the second, third etc, largest rainfall. Another approach is partial duration series (PDS) constructed using the values above a selected threshold and permit more than one event per year. The generalized Pareto distribution (GPD) has been used to model PDS and it is the series of excess over a threshold. In this study, the lowest value of AMS of observed is selected as threshold and simultaneously same frequency is considered as extremes in corresponding GCM gridded series. After fitting to GP distribution, bias corrected GCM extreme is found by using the inverse function of observed extremes. The results show it can remove bias effectively. For projected climate, the same transfer function between historical observed and GCM was applied. Moreover, frequency analysis of maximum extreme intensity estimation was done for validation and then approximate for near future by using identical function as past. To fix the error in the number of no rain days of GCM, ranking order statistics is used and define in GCM same as the frequency of wet days in observed station. After this rank, GCM output will be zero and identify same threshold for future projection. Normal rainfall is classified as between threshold of extreme and no rain day. We assume monthly normal rainfall follow gamma distribution. Then, we mapped the CDF of GCM normal rainfall to station's one in each month and bias corrected rainfall is available. In summary, bias of GCM have been addressed efficiently and validated at point scale by seasonal climatology and at all stations for evaluating downscaled rainfall performance. The results show bias corrected and downscaled scheme is good enough for climate impact study.

Assessing the changes of groundwater recharge / irrigation water use between SRI and traditional irrigation schemes in Central Taiwan

NASA Astrophysics Data System (ADS)

Chen, Shih-Kai; Jang, Cheng-Shin; Tsai, Cheng-Bin

2015-04-01

To respond to agricultural water shortage impacted by climate change without affecting rice yield in the future, the application of water-saving irrigation, such as SRI methodology, is considered to be adopted in rice-cultivation in Taiwan. However, the flooded paddy fields could be considered as an important source of groundwater recharge in Central Taiwan. The water-saving benefit of this new methodology and its impact on the reducing of groundwater recharge should be integrally assessed in this area. The objective of this study was to evaluate the changes of groundwater recharge/ irrigation water use between the SRI and traditional irrigation schemes (continuous irrigation, rotational irrigation). An experimental paddy field located in the proximal area of the Choushui River alluvial fan (the largest groundwater pumping region in Taiwan) was chosen as the study area. The 3-D finite element groundwater model (FEMWATER) with the variable boundary condition analog functions, was applied in simulating groundwater recharge process and amount under traditional irrigation schemes and SRI methodology. The use of effective rainfall was taken into account or not in different simulation scenarios for each irrigation scheme. The simulation results showed that there were no significant variations of infiltration rate in the use of effective rainfall or not, but the low soil moisture setting in deep soil layers resulted in higher infiltration rate. Taking the use of effective rainfall into account, the average infiltration rate for continuous irrigation, rotational irrigation, and SRI methodology in the first crop season of 2013 were 4.04 mm/day, 4.00 mm/day and 3.92 mm/day, respectively. The groundwater recharge amount of SRI methodology was slightly lower than those of traditional irrigation schemes, reducing 4% and 2% compared with continuous irrigation and rotational irrigation, respectively. The field irrigation requirement amount of SRI methodology was significantly lower than those of traditional irrigation schemes, saving 35% and 9% compared with continuous irrigation and rotational irrigation, respectively. The SRI methodology significantly improved water-saving benefit compared with the disadvantage of reducing groundwater recharge. The results could be used as a basis for the relevant government agency to formulate the integral water resource management strategies in this area. Keywords: SRI, Paddy field, Infiltration, Groundwater recharge

A simplified rainfall-runoff stochastic simulation method for an application of the SCHADEX method to ungauged catchments.

NASA Astrophysics Data System (ADS)

Penot, David; Paquet, Emmanuel; Lang, Michel

2014-05-01

SCHADEX is a probabilistic method for extreme flood estimation, developed and applied since 2006 at Electricité de France (EDF) for dam spillway design [Paquet et al., 2013]. SCHADEX is based on a semi-continuous rainfall-runoff simulation process. The method has been built around two models: a Multi-Exponential Weather Pattern (MEWP) distribution for rainfall probability estimation [Garavaglia et al., 2010] and the MORDOR hydrological model. To use SCHADEX in ungauged context, rainfall distribution and hydrological model must be regionalized. The regionalization of the MEWP rainfall distribution can be managed with SPAZM, a daily rainfall interpolator [Gottardi et al., 2012] which provides reasonable estimates of point and areal rainfall up to hight quantiles. The main issue remains to regionalize MORDOR which is heavily parametrized. A much more simple model has been considered: the SCS model. It is a well known model for event simulation [USDA SCS, 1985; Beven, 2003] and it relies on only one parameter. Then, the idea is to use the SCS model instead of MORDOR within a simplified stochastic simulation scheme to produce a distribution of flood volume from an exhaustive crossing between rainy events and catchment saturation hazards. The presentation details this process and its capacity to generate a runoff distribution based on catchment areal rainfall distribution. The simulation method depends on a unique parameter Smax, the maximum initial loss of the catchment. Then an initial loss S (between zero and Smax) can be drawn to account for the variability of catchment state (between dry and saturated). The distribution of initial loss (or conversely, of catchment saturation, as modeled by MORDOR) seems closely linked to the catchment's regime, therefore easily to regionalize. The simulation takes into account a snow contribution for snow driven catchments, and an antecedent runoff. The presentation shows the results of this stochastic procedure applied on 80 French catchments and its capacity to represent the asymptotic behaviour of the runoff distribution. References: K. J. Beven. Rainfall-Runoff modelling The Primer, British Library, 2003. F. Garavaglia, J. Gailhard, E. Paquet, M. Lang, R. Garçon, and P. Bernardara. Introducing a rainfall compound distribution model based on weather patterns sub-sampling. Hydrology and Earth System Sciences, 14(6):951-964, 2010. F. Gottardi, C. Obled, J. Gailhard, and E. Paquet. Statistical reanalysis of precipitation fields based on ground network data and weather patterns : Application over french mountains. Journal of Hydrology, 432-433:154-167, 2012. ISSN 0022-1694. E. Paquet, F. Garavaglia, R Garçon, and J. Gailhard. The schadex method : a semi-continuous rainfall-runoff simulation for extreme flood estimation. Journal of Hydrology, 2013. USDA SCS, National Engineering Handbook, Supplement A, Section 4, Chapter 10. Whashington DC, 1985.

Prediction of Root Zone Soil Moisture using Remote Sensing Products and In-Situ Observation under Climate Change Scenario

NASA Astrophysics Data System (ADS)

Singh, G.; Panda, R. K.; Mohanty, B.

2015-12-01

Prediction of root zone soil moisture status at field level is vital for developing efficient agricultural water management schemes. In this study, root zone soil moisture was estimated across the Rana watershed in Eastern India, by assimilation of near-surface soil moisture estimate from SMOS satellite into a physically-based Soil-Water-Atmosphere-Plant (SWAP) model. An ensemble Kalman filter (EnKF) technique coupled with SWAP model was used for assimilating the satellite soil moisture observation at different spatial scales. The universal triangle concept and artificial intelligence techniques were applied to disaggregate the SMOS satellite monitored near-surface soil moisture at a 40 km resolution to finer scale (1 km resolution), using higher spatial resolution of MODIS derived vegetation indices (NDVI) and land surface temperature (Ts). The disaggregated surface soil moisture were compared to ground-based measurements in diverse landscape using portable impedance probe and gravimetric samples. Simulated root zone soil moisture were compared with continuous soil moisture profile measurements at three monitoring stations. In addition, the impact of projected climate change on root zone soil moisture were also evaluated. The climate change projections of rainfall were analyzed for the Rana watershed from statistically downscaled Global Circulation Models (GCMs). The long-term root zone soil moisture dynamics were estimated by including a rainfall generator of likely scenarios. The predicted long term root zone soil moisture status at finer scale can help in developing efficient agricultural water management schemes to increase crop production, which lead to enhance the water use efficiency.

Rainfall-Runoff Parameters Uncertainity

NASA Astrophysics Data System (ADS)

Heidari, A.; Saghafian, B.; Maknoon, R.

2003-04-01

Karkheh river basin, located in southwest of Iran, drains an area of over 40000 km2 and is considered a flood active basin. A flood forecasting system is under development for the basin, which consists of a rainfall-runoff model, a river routing model, a reservior simulation model, and a real time data gathering and processing module. SCS, Clark synthetic unit hydrograph, and Modclark methods are the main subbasin rainfall-runoff transformation options included in the rainfall-runoff model. Infiltration schemes, such as exponentioal and SCS-CN methods, account for infiltration losses. Simulation of snow melt is based on degree day approach. River flood routing is performed by FLDWAV model based on one-dimensional full dynamic equation. Calibration and validation of the rainfall-runoff model on Karkheh subbasins are ongoing while the river routing model awaits cross section surveys.Real time hydrometeological data are collected by a telemetry network. The telemetry network is equipped with automatic sensors and INMARSAT-C comunication system. A geographic information system (GIS) stores and manages the spatial data while a database holds the hydroclimatological historical and updated time series. Rainfall runoff parameters uncertainty is analyzed by Monte Carlo and GLUE approaches.

Future changes in precipitation of the baiu season under RCP scenarios

NASA Astrophysics Data System (ADS)

Okada, Y.; Takemi, T.; Ishikawa, H.

2014-12-01

Recently, the relationship between global warming and rainfall during the rainy season, which called the baiu in Japan, has been attracting attention in association with heavy rainfall in this period. In the Innovative Program of Climate Change Projection for the 21st Century, many studies show a delay in the northward march of the baiu front, and significant increase of daily precipitation amounts around western Japan during the late baiu season (e.g., Kusunoki et al. 2011, Kanada et al. 2012). The future climate experiment in these studies was performed under the IPCC SRES A1B scenarios for global warming conditions. In this study, we discuss the future changes in precipitation using calculated 60km-mesh model (MRI-AGCM3.2H) under Representative Concentration Pathways (RCP) scenarios. Support of this dataset is provided by the Meteorological Research Institute (MRI). These dataset are calculated by setting the Yoshimura (YS) scheme mainly.Seasonal progression of future precipitation generally indicates the northward in RCP2.6 and 4.5 scenarios, around western Japan. In RCP6.0 scenario, precipitation intensity is weak compared to the other scenarios. RCP8.5 scenario is calculated by setting three different cumulus schemes (YS, Arakawa-Schubert (AS), and Kain-Fritsch (KF) schemes). RCP8.5 configured in YS scheme showed that the rainband associated with the baiu front is not clear. Moreover, peak is remarkable during late June. In AS scheme, the precipitation area stagnates around 30 N until August. And it in KF scheme shows gradual northward migration.This work was conducted under the Program for Risk Information on Climate Change supported by the Ministry of Education, Culture, Sports, Science, and Technology-Japan (MEXT).

An application of hybrid downscaling model to forecast summer precipitation at stations in China

NASA Astrophysics Data System (ADS)

Liu, Ying; Fan, Ke

2014-06-01

A pattern prediction hybrid downscaling method was applied to predict summer (June-July-August) precipitation at China 160 stations. The predicted precipitation from the downscaling scheme is available one month before. Four predictors were chosen to establish the hybrid downscaling scheme. The 500-hPa geopotential height (GH5) and 850-hPa specific humidity (q85) were from the skillful predicted output of three DEMETER (Development of a European Multi-model Ensemble System for Seasonal to Interannual Prediction) general circulation models (GCMs). The 700-hPa geopotential height (GH7) and sea level pressure (SLP) were from reanalysis datasets. The hybrid downscaling scheme (HD-4P) has better prediction skill than a conventional statistical downscaling model (SD-2P) which contains two predictors derived from the output of GCMs, although two downscaling schemes were performed to improve the seasonal prediction of summer rainfall in comparison with the original output of the DEMETER GCMs. In particular, HD-4P downscaling predictions showed lower root mean square errors than those based on the SD-2P model. Furthermore, the HD-4P downscaling model reproduced the China summer precipitation anomaly centers more accurately than the scenario of the SD-2P model in 1998. A hybrid downscaling prediction should be effective to improve the prediction skill of summer rainfall at stations in China.

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

Effect of tillage system and cumulative rainfall on multifractal parameters of soil surface microrelief

NASA Astrophysics Data System (ADS)

Vidal Vázquez, E.; Miranda, J. G. V.; Mirás-Avalos, J. M.; Díaz, M. C.; Paz-Ferreiro, J.

2009-04-01

Mathematical description of the spatial characteristics of soil surface microrelief still remains a challenge. Soil surface roughness parameters are required for modelling overland flow and erosion. The objective of this work was to evaluate the potential of multifractal for analyzing the decay of initial surface roughness induced by natural rainfall under different soil tillage systems. Field experiments were performed on an Oxisol at Campinas, São Paulo State (Brazil). Six tillage treatments, namely, disc harrow, disc plow, chisel plow, disc harrow + disc level, disc plow + disc level and chisel plow + disc level were tested. In each plot soil surface microrelief was measured for times, with increasing amounts of natural rainfall using a pinmeter. The sampling scheme was a square grid with 25 x 25 mm point spacing and the plot size was 1350 x 1350 mm, so that each data set consisted of 3025 individual elevation points. Duplicated measurements were taken per treatment and date, yielding a total of 48 experimental data sets. All the investigated microrelief data sets exhibited, in general, scale properties, and the degree of multifractality showed wide differences between them. Multifractal analysis distinguishes two different patterns of soil surface microrelief, the first one has features close to monofractal spectra and the second clearly indicates multifractal behavior. Both, singularity spectra and generalized dimension spectra allow differentiating between soil tillage systems. In general, changes in values of multifractal parameters under simulated rainfall showed no or little correspondence with the evolution of the vertical microrelief component described by indices such as the standard deviation of the point height measurements. Multifractal parameters provided valuable information for chararacterizing the spatial features of soil surface microrelief as they were able to discriminate data sets with similar values for the vertical component of roughness.

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

Developments in radar and remote-sensing methods for measuring and forecasting rainfall.

PubMed

Collier, C G

2002-07-15

Over the last 25 years or so, weather-radar networks have become an integral part of operational meteorological observing systems. While measurements of rainfall made using radar systems have been used qualitatively by weather forecasters, and by some operational hydrologists, acceptance has been limited as a consequence of uncertainties in the quality of the data. Nevertheless, new algorithms for improving the accuracy of radar measurements of rainfall have been developed, including the potential to calibrate radars using the measurements of attenuation on microwave telecommunications links. Likewise, ways of assimilating these data into both meteorological and hydrological models are being developed. In this paper we review the current accuracy of radar estimates of rainfall, pointing out those approaches to the improvement of accuracy which are likely to be most successful operationally. Comment is made on the usefulness of satellite data for estimating rainfall in a flood-forecasting context. Finally, problems in coping with the error characteristics of all these data using both simple schemes and more complex four-dimensional variational analysis are being addressed, and are discussed briefly in this paper.

Transfer of Satellite Rainfall Uncertainty from Gauged to Ungauged Regions at Regional and Seasonal Timescales

NASA Technical Reports Server (NTRS)

Tang, Ling; Hossain, Faisal; Huffman, George J.

2010-01-01

Hydrologists and other users need to know the uncertainty of the satellite rainfall data sets across the range of time/space scales over the whole domain of the data set. Here, uncertainty' refers to the general concept of the deviation' of an estimate from the reference (or ground truth) where the deviation may be defined in multiple ways. This uncertainty information can provide insight to the user on the realistic limits of utility, such as hydrologic predictability, that can be achieved with these satellite rainfall data sets. However, satellite rainfall uncertainty estimation requires ground validation (GV) precipitation data. On the other hand, satellite data will be most useful over regions that lack GV data, for example developing countries. This paper addresses the open issues for developing an appropriate uncertainty transfer scheme that can routinely estimate various uncertainty metrics across the globe by leveraging a combination of spatially-dense GV data and temporally sparse surrogate (or proxy) GV data, such as the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar and the Global Precipitation Measurement (GPM) mission Dual-Frequency Precipitation Radar. The TRMM Multi-satellite Precipitation Analysis (TMPA) products over the US spanning a record of 6 years are used as a representative example of satellite rainfall. It is shown that there exists a quantifiable spatial structure in the uncertainty of satellite data for spatial interpolation. Probabilistic analysis of sampling offered by the existing constellation of passive microwave sensors indicate that transfer of uncertainty for hydrologic applications may be effective at daily time scales or higher during the GPM era. Finally, a commonly used spatial interpolation technique (kriging), that leverages the spatial correlation of estimation uncertainty, is assessed at climatologic, seasonal, monthly and weekly timescales. It is found that the effectiveness of kriging is sensitive to the type of uncertainty metric, time scale of transfer and the density of GV data within the transfer domain. Transfer accuracy is lowest at weekly timescales with the error doubling from monthly to weekly.However, at very low GV data density (<20% of the domain), the transfer accuracy is too low to show any distinction as a function of the timescale of transfer.

Analysis of the linkage between rain and flood regime and its application to regional flood frequency estimation

NASA Astrophysics Data System (ADS)

Cunderlik, Juraj M.; Burn, Donald H.

2002-04-01

Improving techniques of flood frequency estimation at ungauged sites is one of the foremost goals of contemporary hydrology. River flood regime is a resultant reflection of a composite catchment hydrologic response to flood producing processes. In this sense the process of identifying homogeneous pooling groups can be plausibly based on catchment similarity in flood regime. Unfortunately the application of any pooling approach that is based on flood regime is restricted to gauged sites. Because flood regime can be markedly determined by rainfall regime, catchment similarity in rainfall regime can be an alternative option for identifying flood frequency pooling groups. An advantage of such a pooling approach is that rainfall data are usually spatially and temporary more abundant than flood data and the approach can also be applied at ungauged sites. Therefore in this study we have quantified the linkage between rainfall and flood regime and explored the appropriateness of substituting rainfall regime for flood regime in regional pooling schemes. Two different approaches to describing rainfall regime similarity using tools of directional statistics have been tested and used for evaluation of the potential of rainfall regime for identification of hydrologically homogeneous pooling groups. The outputs were compared to an existing pooling framework adopted in the Flood Estimation Handbook. The results demonstrate that regional pooling based on rainfall regime information leads to a high number of initially homogeneous groups and seems to be a sound pooling alternative for catchments with a close linkage between rain and flood regimes.

Novel SVM-based technique to improve rainfall estimation over the Mediterranean region (north of Algeria) using the multispectral MSG SEVIRI imagery

NASA Astrophysics Data System (ADS)

Sehad, Mounir; Lazri, Mourad; Ameur, Soltane

2017-03-01

In this work, a new rainfall estimation technique based on the high spatial and temporal resolution of the Spinning Enhanced Visible and Infra Red Imager (SEVIRI) aboard the Meteosat Second Generation (MSG) is presented. This work proposes efficient scheme rainfall estimation based on two multiclass support vector machine (SVM) algorithms: SVM_D for daytime and SVM_N for night time rainfall estimations. Both SVM models are trained using relevant rainfall parameters based on optical, microphysical and textural cloud proprieties. The cloud parameters are derived from the Spectral channels of the SEVIRI MSG radiometer. The 3-hourly and daily accumulated rainfall are derived from the 15 min-rainfall estimation given by the SVM classifiers for each MSG observation image pixel. The SVMs were trained with ground meteorological radar precipitation scenes recorded from November 2006 to March 2007 over the north of Algeria located in the Mediterranean region. Further, the SVM_D and SVM_N models were used to estimate 3-hourly and daily rainfall using data set gathered from November 2010 to March 2011 over north Algeria. The results were validated against collocated rainfall observed by rain gauge network. Indeed, the statistical scores given by correlation coefficient, bias, root mean square error and mean absolute error, showed good accuracy of rainfall estimates by the present technique. Moreover, rainfall estimates of our technique were compared with two high accuracy rainfall estimates methods based on MSG SEVIRI imagery namely: random forests (RF) based approach and an artificial neural network (ANN) based technique. The findings of the present technique indicate higher correlation coefficient (3-hourly: 0.78; daily: 0.94), and lower mean absolute error and root mean square error values. The results show that the new technique assign 3-hourly and daily rainfall with good and better accuracy than ANN technique and (RF) model.

Rainfall characteristics for shallow landsliding in Seattle, Washington, USA

USGS Publications Warehouse

Godt, J.W.; Baum, R.L.; Chleborad, A.F.

2006-01-01

Shallow landsliding in the Seattle, Washington, area, has caused the occasional loss of human life and millions of dollars in damage to property. The effective management of the hazzard requires an understanding of the rainfall conditions that result in landslides. We present an empirical approach to quantify the antecedent moisture conditions and rainstorm intensity and duration that have triggered shallow landsliding using 25 years of hourly rainfull data and a complementary record of landslide occurrence. Our approach combines a simple water balance to estimate the antecedent moisture conditions of hillslope materials and a rainfall intensity-duration threshold to identify periods when shallow landsliding can be expected. The water balance is calibrated with field-monitoring data and combined with the rainfall intensity-duration threshold using a decision tree. Results are cast in terms of a hypothetical landslide warning system. Two widespread landslide events are correctly identified by the warning scheme; however, it is less accurate for more isolated landsliding. Copyright ?? 2005 John Wiley & Sons, Ltd.

Hurricane Impact on Seepage Water in Larga Cave, Puerto Rico

NASA Astrophysics Data System (ADS)

Vieten, Rolf; Warken, Sophie; Winter, Amos; Schröder-Ritzrau, Andrea; Scholz, Denis; Spötl, Christoph

2018-03-01

Hurricane-induced rainfall over Puerto Rico has characteristic δ18O values which are more negative than local rainfall events. Thus, hurricanes may be recorded in speleothems from Larga cave, Puerto Rico, as characteristic oxygen isotope excursions. Samples of 84 local rainfall events between 2012 and 2013 ranged from -6.2 to +0.3‰, whereas nine rainfall samples belonging to a rainband of hurricane Isaac (23-24 August 2012) ranged from -11.8 to -7.1‰. Cave monitoring covered the hurricane season of 2014 and investigated the impact of hurricane rainfall on drip water chemistry. δ18O values were measured in cumulative monthly rainwater samples above the cave. Inside the cave, δ18O values of instantaneous drip water samples were analyzed and drip rates were recorded at six drip sites. Most effective recharge appears to occur during the wet months (April-May and August-November). δ18O values of instantaneous drip water samples ranged from -3.5 to -2.4‰. In April 2014 and April 2015 some drip sites showed more negative δ18O values than the effective rainfall (-2.9‰), implying an influence of hurricane rainfall reaching the cave via stratified seepage flow months to years after the event. Speleothems from these drip sites in Larga cave have a high potential for paleotempestology studies.

Effects of Planetary Boundary Layer Parameterizations on CWRF Regional Climate Simulation

NASA Astrophysics Data System (ADS)

Liu, S.; Liang, X.

2011-12-01

Planetary Boundary Layer (PBL) parameterizations incorporated in CWRF (Climate extension of the Weather Research and Forecasting model) are first evaluated by comparing simulated PBL heights with observations. Among the 10 evaluated PBL schemes, 2 (CAM, UW) are new in CWRF while the other 8 are original WRF schemes. MYJ, QNSE and UW determine the PBL heights based on turbulent kinetic energy (TKE) profiles, while others (YSU, ACM, GFS, CAM, TEMF) are from bulk Richardson criteria. All TKE-based schemes (MYJ, MYNN, QNSE, UW, Boulac) substantially underestimate convective or residual PBL heights from noon toward evening, while others (ACM, CAM, YSU) well capture the observed diurnal cycle except for the GFS with systematic overestimation. These differences among the schemes are representative over most areas of the simulation domain, suggesting systematic behaviors of the parameterizations. Lower PBL heights simulated by the QNSE and MYJ are consistent with their smaller Bowen ratios and heavier rainfalls, while higher PBL tops by the GFS correspond to warmer surface temperatures. Effects of PBL parameterizations on CWRF regional climate simulation are then compared. The QNSE PBL scheme yields systematically heavier rainfall almost everywhere and throughout the year; this is identified with a much greater surface Bowen ratio (smaller sensible versus larger latent heating) and wetter soil moisture than other PBL schemes. Its predecessor MYJ scheme shares the same deficiency to a lesser degree. For temperature, the performance of the QNSE and MYJ schemes remains poor, having substantially larger rms errors in all seasons. GFS PBL scheme also produces large warm biases. Pronounced sensitivities are also found to the PBL schemes in winter and spring over most areas except the southern U.S. (Southeast, Gulf States, NAM); excluding the outliers (QNSE, MYJ, GFS) that cause extreme biases of -6 to +3°C, the differences among the schemes are still visible (±2°C), where the CAM is generally more realistic. QNSE, MYJ, GFS and BouLac PBL parameterizations are identified as obvious outliers of overall performance in representing precipitation, surface air temperature or PBL height variations. Their poor performance may result from deficiencies in physical formulations, dependences on applicable scales, or trouble numerical implementations, requiring future detailed investigation to isolate the actual cause.

Modern control concepts in hydrology. [parameter identification in adaptive stochastic control approach

NASA Technical Reports Server (NTRS)

Duong, N.; Winn, C. B.; Johnson, G. R.

1975-01-01

Two approaches to an identification problem in hydrology are presented, based upon concepts from modern control and estimation theory. The first approach treats the identification of unknown parameters in a hydrologic system subject to noisy inputs as an adaptive linear stochastic control problem; the second approach alters the model equation to account for the random part in the inputs, and then uses a nonlinear estimation scheme to estimate the unknown parameters. Both approaches use state-space concepts. The identification schemes are sequential and adaptive and can handle either time-invariant or time-dependent parameters. They are used to identify parameters in the Prasad model of rainfall-runoff. The results obtained are encouraging and confirm the results from two previous studies; the first using numerical integration of the model equation along with a trial-and-error procedure, and the second using a quasi-linearization technique. The proposed approaches offer a systematic way of analyzing the rainfall-runoff process when the input data are imbedded in noise.

The roles of dry convection, cloud-radiation feedback processes and the influence of recent improvements in the parameterization of convection in the GLA GCM

NASA Technical Reports Server (NTRS)

Sud, Y.; Molod, A.

1988-01-01

The Goddard Laboratory for Atmospheres GCM is used to study the sensitivity of the simulated July circulation to modifications in the parameterization of dry and moist convection, evaporation from falling raindrops, and cloud-radiation interaction. It is shown that the Arakawa-Schubert (1974) cumulus parameterization and a more realistic dry convective mixing calculation yielded a better intertropical convergence zone over North Africa than the previous convection scheme. It is found that the physical mechanism for the improvement was the upward mixing of PBL moisture by vigorous dry convective mixing. A modified rain-evaporation parameterization which accounts for raindrop size distribution, the atmospheric relative humidity, and a typical spatial rainfall intensity distribution for convective rain was developed and implemented. This scheme led to major improvements in the monthly mean vertical profiles of relative humidity and temperature, convective and large-scale cloudiness, rainfall distributions, and mean relative humidity in the PBL.

Modern control concepts in hydrology

NASA Technical Reports Server (NTRS)

Duong, N.; Johnson, G. R.; Winn, C. B.

1974-01-01

Two approaches to an identification problem in hydrology are presented based upon concepts from modern control and estimation theory. The first approach treats the identification of unknown parameters in a hydrologic system subject to noisy inputs as an adaptive linear stochastic control problem; the second approach alters the model equation to account for the random part in the inputs, and then uses a nonlinear estimation scheme to estimate the unknown parameters. Both approaches use state-space concepts. The identification schemes are sequential and adaptive and can handle either time invariant or time dependent parameters. They are used to identify parameters in the Prasad model of rainfall-runoff. The results obtained are encouraging and conform with results from two previous studies; the first using numerical integration of the model equation along with a trial-and-error procedure, and the second, by using a quasi-linearization technique. The proposed approaches offer a systematic way of analyzing the rainfall-runoff process when the input data are imbedded in noise.

Increased Spatial Variability and Intensification of Extreme Monsoon Rainfall due to Urbanization.

PubMed

Paul, Supantha; Ghosh, Subimal; Mathew, Micky; Devanand, Anjana; Karmakar, Subhankar; Niyogi, Dev

2018-03-02

While satellite data provides a strong robust signature of urban feedback on extreme precipitation; urbanization signal is often not so prominent with station level data. To investigate this, we select the case study of Mumbai, India and perform a high resolution (1 km) numerical study with Weather Research and Forecasting (WRF) model for eight extreme rainfall days during 2014-2015. The WRF model is coupled with two different urban schemes, the Single Layer Urban Canopy Model (WRF-SUCM), Multi-Layer Urban Canopy Model (WRF-MUCM). The differences between the WRF-MUCM and WRF-SUCM indicate the importance of the structure and characteristics of urban canopy on modifications in precipitation. The WRF-MUCM simulations resemble the observed distributed rainfall. WRF-MUCM also produces intensified rainfall as compared to the WRF-SUCM and WRF-NoUCM (without UCM). The intensification in rainfall is however prominent at few pockets of urban regions, that is seen in increased spatial variability. We find that the correlation of precipitation across stations within the city falls below statistical significance at a distance greater than 10 km. Urban signature on extreme precipitation will be reflected on station rainfall only when the stations are located inside the urban pockets having intensified precipitation, which needs to be considered in future analysis.

Comparison of WRF local and nonlocal boundary layer Physics in Greater Kuala Lumpur, Malaysia

NASA Astrophysics Data System (ADS)

Ooi, M. C. G.; Chan, A.; Kumarenthiran, S.; Morris, K. I.; Oozeer, M. Y.; Islam, M. A.; Salleh, S. A.

2018-02-01

The urban boundary layer (UBL) is the internal advection layer of atmosphere above urban region which determines the exchanges of momentum, water and other atmospheric constituents between the urban land surface and the free troposphere. This paper tested the performance of three planetary boundary layer (PBL) physics schemes of Weather Research and Forecast (WRF) software to ensure the appropriate representation of vertical structure of UBL in Greater Kuala Lumpur (GKL). Comparison was conducted on the performance of respective PBL schemes to generate vertical and near-surface weather profile and rainfall. Mellor-Yamada- Janjíc (MYJ) local PBL scheme coupled with Eta MM5 surface layer scheme was found to predict the near-surface temperature and wind profile and mixing height better than the nonlocal schemes during the intermonsoonal period with least influences of the synoptic background weather.

Evaluation of Bias Correction Method for Satellite-Based Rainfall Data

PubMed Central

Bhatti, Haris Akram; Rientjes, Tom; Haile, Alemseged Tamiru; Habib, Emad; Verhoef, Wouter

2016-01-01

With the advances in remote sensing technology, satellite-based rainfall estimates are gaining attraction in the field of hydrology, particularly in rainfall-runoff modeling. Since estimates are affected by errors correction is required. In this study, we tested the high resolution National Oceanic and Atmospheric Administration’s (NOAA) Climate Prediction Centre (CPC) morphing technique (CMORPH) satellite rainfall product (CMORPH) in the Gilgel Abbey catchment, Ethiopia. CMORPH data at 8 km-30 min resolution is aggregated to daily to match in-situ observations for the period 2003–2010. Study objectives are to assess bias of the satellite estimates, to identify optimum window size for application of bias correction and to test effectiveness of bias correction. Bias correction factors are calculated for moving window (MW) sizes and for sequential windows (SW’s) of 3, 5, 7, 9, …, 31 days with the aim to assess error distribution between the in-situ observations and CMORPH estimates. We tested forward, central and backward window (FW, CW and BW) schemes to assess the effect of time integration on accumulated rainfall. Accuracy of cumulative rainfall depth is assessed by Root Mean Squared Error (RMSE). To systematically correct all CMORPH estimates, station based bias factors are spatially interpolated to yield a bias factor map. Reliability of interpolation is assessed by cross validation. The uncorrected CMORPH rainfall images are multiplied by the interpolated bias map to result in bias corrected CMORPH estimates. Findings are evaluated by RMSE, correlation coefficient (r) and standard deviation (SD). Results showed existence of bias in the CMORPH rainfall. It is found that the 7 days SW approach performs best for bias correction of CMORPH rainfall. The outcome of this study showed the efficiency of our bias correction approach. PMID:27314363

Evaluation of Bias Correction Method for Satellite-Based Rainfall Data.

PubMed

Bhatti, Haris Akram; Rientjes, Tom; Haile, Alemseged Tamiru; Habib, Emad; Verhoef, Wouter

2016-06-15

With the advances in remote sensing technology, satellite-based rainfall estimates are gaining attraction in the field of hydrology, particularly in rainfall-runoff modeling. Since estimates are affected by errors correction is required. In this study, we tested the high resolution National Oceanic and Atmospheric Administration's (NOAA) Climate Prediction Centre (CPC) morphing technique (CMORPH) satellite rainfall product (CMORPH) in the Gilgel Abbey catchment, Ethiopia. CMORPH data at 8 km-30 min resolution is aggregated to daily to match in-situ observations for the period 2003-2010. Study objectives are to assess bias of the satellite estimates, to identify optimum window size for application of bias correction and to test effectiveness of bias correction. Bias correction factors are calculated for moving window (MW) sizes and for sequential windows (SW's) of 3, 5, 7, 9, …, 31 days with the aim to assess error distribution between the in-situ observations and CMORPH estimates. We tested forward, central and backward window (FW, CW and BW) schemes to assess the effect of time integration on accumulated rainfall. Accuracy of cumulative rainfall depth is assessed by Root Mean Squared Error (RMSE). To systematically correct all CMORPH estimates, station based bias factors are spatially interpolated to yield a bias factor map. Reliability of interpolation is assessed by cross validation. The uncorrected CMORPH rainfall images are multiplied by the interpolated bias map to result in bias corrected CMORPH estimates. Findings are evaluated by RMSE, correlation coefficient (r) and standard deviation (SD). Results showed existence of bias in the CMORPH rainfall. It is found that the 7 days SW approach performs best for bias correction of CMORPH rainfall. The outcome of this study showed the efficiency of our bias correction approach.

Comparing Nitrous Oxide Emissions from Three Residential Landscapes under Different Management Schemes Following Natural Rainfall Events

EPA Science Inventory

Cultural lawn management practices that produce aesthetically appealing landscapes may also create environmental conditions that stimulate soil nitrous oxide (N2O) emissions. The purpose of this study is to investigate the effects of lawn management practices on N2O fluxes from ...

Analysis of Darwin Rainfall Data: Implications on Sampling Strategy

NASA Technical Reports Server (NTRS)

Rafael, Qihang Li; Bras, Rafael L.; Veneziano, Daniele

1996-01-01

Rainfall data collected by radar in the vicinity of Darwin, Australia, have been analyzed in terms of their mean, variance, autocorrelation of area-averaged rain rate, and diurnal variation. It is found that, when compared with the well-studied GATE (Global Atmospheric Research Program Atlantic Tropical Experiment) data, Darwin rainfall has larger coefficient of variation (CV), faster reduction of CV with increasing area size, weaker temporal correlation, and a strong diurnal cycle and intermittence. The coefficient of variation for Darwin rainfall has larger magnitude and exhibits larger spatial variability over the sea portion than over the land portion within the area of radar coverage. Stationary, and nonstationary models have been used to study the sampling errors associated with space-based rainfall measurement. The nonstationary model shows that the sampling error is sensitive to the starting sampling time for some sampling frequencies, due to the diurnal cycle of rain, but not for others. Sampling experiments using data also show such sensitivity. When the errors are averaged over starting time, the results of the experiments and the stationary and nonstationary models match each other very closely. In the small areas for which data are available for I>oth Darwin and GATE, the sampling error is expected to be larger for Darwin due to its larger CV.

Remote sensing entropy to assess the sustainability of rainfall in tropical catchment

NASA Astrophysics Data System (ADS)

Mahmud, M. R.; Reba, M. N. M.; Wei, J. S.; Razak, N. H. Abdul

2018-02-01

This study demonstrated the utility of entropy computation using the satellite precipitation remote sensing data to assess the sustainability of rainfall in tropical catchments. There were two major issues need to be anticipated in monitoring the tropical catchments; first is the frequent monitoring of the rainfall and second is the appropriate indicator that sensitive to rainfall pattern changes or disorder. For the first issue, the use of satellite remote sensing precipitation data is suggested. Meanwhile for the second issue, the utilization of entropy concept in interpreting the disorder of temporal rainfall can be used to assess the sustain ability had been successfully adopted in some studies. Therefore, we hypothesized that the use of satellite precipitation as main data to compute entropy can be a novel tool in anticipating the above-mentioned conflict earlier. The remote sensing entropy results and in-situ river level showed good agreement indicating its reliability. 72% of the catchment has moderate to good rainfall supply during normal or non-drought condition. However, our result showed that the catchments were highly sensitive to drought especially in the west coast and southern part of the Peninsular Malaysia. High resiliency was identified in the east coast. We summarized that the proposed entropy-quantity scheme was a useful tool for cost-effective, quick, and operational sustainability assessment This study demonstrated the utility of entropy computation using the satellite precipitation remote sensing data to assess the sustainability of rainfall in tropical catchments.

Does the GPM mission resolve the systematic error dependence with climatology and topography - a statistical and hydrologic evaluation over India?

NASA Astrophysics Data System (ADS)

Beria, H.; Nanda, T., Sr.; Bisht, D. S.; Chatterjee, C.

2016-12-01

Increasing hydrologic extremes in a changing climate with lack of quality rainfall forcings have inspired the development of a number of satellite and reanalysis based precipitation products in the past decade. Tropical Rainfall Measuring Mission (TRMM) has emerged as the front runner in this race, providing high quality precipitation forcings in the tropical part of the world. However, TRMM is known to suffer from its poor sensitivity to low rainfall intensities due to limited resolving power of its sensors, and is also not known to accurately resolve topography in its rainfall estimates. The Global Precipitation Mission (GPM), a follow-up mission of TRMM, promises enhanced spatio-temporal resolution along with upgrades in sensors and rainfall estimation techniques. In this study, the rainfall estimates of Integrated Multi-satellitE Retrievals for GPM (IMERG), was compared with those of TRMM for the major basins in India for the year 2014. IMERG depicted higher skill (in terms of correlation) for the majority of basins at all rainfall intensities, with a drastic improvement in low rainfall estimates (smaller biases in 75 out of 86 basins). IMERG was found to improve the topographic resolution, with lower error in high elevation basins. IMERG could better resolve the sharp topographic gradient in the Western Ghat region of India. However, IMERG suffered from poor skill in the semi-arid basins of Rajasthan, at all rainfall intensities. Rainfall-runoff exercise over Mahanadi River basin (a flood prone basin on the Eastern coast of India) using Variable Infiltration Capacity Model (VIC) showed better simulations with TRMM, mainly due to the overestimation of low rainfall events by IMERG. Also, the calibration scheme could be put to fault as the period of availability of IMERG is rather small, and more in-depth hydrologic analysis could only be carried out with sufficiently longer time series. Overall, the fine spatial and temporal resolution along with improved accuracy, promises new horizons in hydrologic forecasting under data scarcity.

A medium scale mobile rainfall simulator for experiments on soil erosion and soil hydrology

NASA Astrophysics Data System (ADS)

Kavka, Petr; Dostál, Tomáš; Iserloh, Thomas; Davidová, Tereza; Krása, Josef; David, Václav; Vopravil, Jan; Khel, Tomáš; Bauer, Miroslav

2015-04-01

Numerous types of rainfall simulators (RS) have been used to the study the behaviour of surface runoff and sediment transport caused by rainfall. It has been documented, that reproducibility and the knowledge of test conditions are essential for gathering necessary and comparable data. Therefore medium, to large scale field rainfall simulators are very desirable. Such devices are nevertheless very much time and laboratory consuming and their weakness is especially a high water consumption. A new, compact and mobile medium scale rainfall simulator has been developed under close cooperation of CTU Prague and Research Institute of Soil Conservation. The main idea was to develop a device, which is easily to handle by 4 persons, transportable with trailer behind an off-road car and independent of additional water sources and energy. Therefore, a special construction fixed on a standard trailer has been developed. It consists of an aggregate to produce power, an electric pump and a water tank with a capacity up to 1000 l. The pump can work in reverse mode, what allows filling the water tank from any source, including stream or pond. The capacity of the tank is normally sufficient for experiments with duration up to 30 minutes. The RS itself consist of a folding arm, which carries 4 nozzles (SS Full Jet 40WSQ), controlled by electromagnetic valves, which allow to set up desired rainfall intensity by opening intervals. A simple logical unit allows programming various schemes of operation of individual nozzles, to keep low pressure fluctuation in the system. The arm is first unfolded into total length of 9.6 m and then lifted up, using simple crab to its operation position which is 2.3 - 2.65 m above terrain surface. The distance between individual nozzles had been optimized based on number of calibrating experiments on 2.4 m. There is also special space at the trailer for transportation of metal sheets and collector (for experimental plot), additional equipment, tools and measurement devices. To prevent the wind effect, whole construction can be easily covered by tarpaulin. The experimental plot has a basic size of 9.5 x 2 m, however, we usually use only 8 x 2 m. The nozzles are fed with a water pressure of about 0.8 bars. Various schemes of opened nozzles allow varying rainfall intensities between 40 and 80 mm.h-1. Rainfall collectors were used to measure spatial rainfall distribution. The spatial rainfall distribution on the entire plot is higher than 80% (Christiansen-Uniformity Coefficient). Drop size distribution and drop fall velocities were analyzed by means of a Laser Precipitation Monitor (by Thies) with satisfactory results. The mean drop sizes ranging between 0.75 - 2.00 mm depending on applied intensity. Resulting kinetic energies ranging from 188 - 582 J m-2 mm-1. The measured rainfall variables show low fluctuations throughout the tests and are therefore reproducible in field investigations. The research has been supported by the research projects SGS14/180/OHK1/3T/11 and QJ330118.

Rainfall assimilation in RAMS by means of the Kuo parameterisation inversion: method and preliminary results

NASA Astrophysics Data System (ADS)

Orlandi, A.; Ortolani, A.; Meneguzzo, F.; Levizzani, V.; Torricella, F.; Turk, F. J.

2004-03-01

In order to improve high-resolution forecasts, a specific method for assimilating rainfall rates into the Regional Atmospheric Modelling System model has been developed. It is based on the inversion of the Kuo convective parameterisation scheme. A nudging technique is applied to 'gently' increase with time the weight of the estimated precipitation in the assimilation process. A rough but manageable technique is explained to estimate the partition of convective precipitation from stratiform one, without requiring any ancillary measurement. The method is general purpose, but it is tuned for geostationary satellite rainfall estimation assimilation. Preliminary results are presented and discussed, both through totally simulated experiments and through experiments assimilating real satellite-based precipitation observations. For every case study, Rainfall data are computed with a rapid update satellite precipitation estimation algorithm based on IR and MW satellite observations. This research was carried out in the framework of the EURAINSAT project (an EC research project co-funded by the Energy, Environment and Sustainable Development Programme within the topic 'Development of generic Earth observation technologies', Contract number EVG1-2000-00030).

Optimizing the Betts-Miller-Janjic cumulus parameterization with Intel Many Integrated Core (MIC) architecture

NASA Astrophysics Data System (ADS)

Huang, Melin; Huang, Bormin; Huang, Allen H.-L.

2015-10-01

The schemes of cumulus parameterization are responsible for the sub-grid-scale effects of convective and/or shallow clouds, and intended to represent vertical fluxes due to unresolved updrafts and downdrafts and compensating motion outside the clouds. Some schemes additionally provide cloud and precipitation field tendencies in the convective column, and momentum tendencies due to convective transport of momentum. The schemes all provide the convective component of surface rainfall. Betts-Miller-Janjic (BMJ) is one scheme to fulfill such purposes in the weather research and forecast (WRF) model. National Centers for Environmental Prediction (NCEP) has tried to optimize the BMJ scheme for operational application. As there are no interactions among horizontal grid points, this scheme is very suitable for parallel computation. With the advantage of Intel Xeon Phi Many Integrated Core (MIC) architecture, efficient parallelization and vectorization essentials, it allows us to optimize the BMJ scheme. If compared to the original code respectively running on one CPU socket (eight cores) and on one CPU core with Intel Xeon E5-2670, the MIC-based optimization of this scheme running on Xeon Phi coprocessor 7120P improves the performance by 2.4x and 17.0x, respectively.

Regionalizing nonparametric models of precipitation amounts on different temporal scales

NASA Astrophysics Data System (ADS)

Mosthaf, Tobias; Bárdossy, András

2017-05-01

Parametric distribution functions are commonly used to model precipitation amounts corresponding to different durations. The precipitation amounts themselves are crucial for stochastic rainfall generators and weather generators. Nonparametric kernel density estimates (KDEs) offer a more flexible way to model precipitation amounts. As already stated in their name, these models do not exhibit parameters that can be easily regionalized to run rainfall generators at ungauged locations as well as at gauged locations. To overcome this deficiency, we present a new interpolation scheme for nonparametric models and evaluate it for different temporal resolutions ranging from hourly to monthly. During the evaluation, the nonparametric methods are compared to commonly used parametric models like the two-parameter gamma and the mixed-exponential distribution. As water volume is considered to be an essential parameter for applications like flood modeling, a Lorenz-curve-based criterion is also introduced. To add value to the estimation of data at sub-daily resolutions, we incorporated the plentiful daily measurements in the interpolation scheme, and this idea was evaluated. The study region is the federal state of Baden-Württemberg in the southwest of Germany with more than 500 rain gauges. The validation results show that the newly proposed nonparametric interpolation scheme provides reasonable results and that the incorporation of daily values in the regionalization of sub-daily models is very beneficial.

Why the predictions for monsoon rainfall fail?

NASA Astrophysics Data System (ADS)

Lee, J.

2016-12-01

To be in line with the Global Land/Atmosphere System Study (GLASS) of the Global Energy and Water Cycle Experiment (GEWEX) international research scheme, this study discusses classical arguments about the feedback mechanisms between land surface and precipitation to improve the predictions of African monsoon rainfall. In order to clarify the impact of antecedent soil moisture on subsequent rainfall evolution, several data sets will be presented. First, in-situ soil moisture field measurements acquired by the AMMA field campaign will be shown together with rain gauge data. This data set will validate various model and satellite data sets such as NOAH land surface model, TRMM rainfall, CMORPH rainfall and HadGEM climate models, SMOS soil moisture. To relate soil moisture with precipitation, two approaches are employed: one approach makes a direct comparison between the spatial distributions of soil moisture as an absolute value and rainfall, while the other measures a temporal evolution of the consecutive dry days (i.e. a relative change within the same soil moisture data set over time) and rainfall occurrences. Consecutive dry days shows consistent results of a negative feedback between soil moisture and rainfall across various data sets, contrary to the direct comparison of soil moisture state. This negative mechanism needs attention, as most climate models usually focus on a positive feedback only. The approach of consecutive dry days takes into account the systematic errors in satellite observations, reminding us that it may cause the misinterpretation to directly compare model with satellite data, due to their difference in data retrievals. This finding is significant, as the climate indices employed by the Intergovernmental Panel on Climate Change (IPCC) modelling archive are based on the atmospheric variable rathr than land.

A simple lightning assimilation technique for improving ...

EPA Pesticide Factsheets

Convective rainfall is often a large source of error in retrospective modeling applications. In particular, positive rainfall biases commonly exist during summer months due to overactive convective parameterizations. In this study, lightning assimilation was applied in the Kain-Fritsch (KF) convective scheme to improve retrospective simulations using the Weather Research and Forecasting (WRF) model. The assimilation method has a straightforward approach: force KF deep convection where lightning is observed and, optionally, suppress deep convection where lightning is absent. WRF simulations were made with and without lightning assimilation over the continental United States for July 2012, July 2013, and January 2013. The simulations were evaluated against NCEP stage-IV precipitation data and MADIS near-surface meteorological observations. In general, the use of lightning assimilation considerably improves the simulation of summertime rainfall. For example, the July 2012 monthly averaged bias of 6 h accumulated rainfall is reduced from 0.54 to 0.07 mm and the spatial correlation is increased from 0.21 to 0.43 when lightning assimilation is used. Statistical measures of near-surface meteorological variables also are improved. Consistent improvements also are seen for the July 2013 case. These results suggest that this lightning assimilation technique has the potential to substantially improve simulation of warm-season rainfall in retrospective WRF applications. The

A Simple Lightning Assimilation Technique For Improving ...

EPA Pesticide Factsheets

Convective rainfall is often a large source of error in retrospective modeling applications. In particular, positive rainfall biases commonly exist during summer months due to overactive convective parameterizations. In this study, lightning assimilation was applied in the Kain-Fritsch (KF) convective scheme to improve retrospective simulations using the Weather Research and Forecasting (WRF) model. The assimilation method has a straightforward approach: Force KF deep convection where lightning is observed and, optionally, suppress deep convection where lightning is absent. WRF simulations were made with and without lightning assimilation over the continental United States for July 2012, July 2013, and January 2013. The simulations were evaluated against NCEP stage-IV precipitation data and MADIS near-surface meteorological observations. In general, the use of lightning assimilation considerably improves the simulation of summertime rainfall. For example, the July 2012 monthly-averaged bias of 6-h accumulated rainfall is reduced from 0.54 mm to 0.07 mm and the spatial correlation is increased from 0.21 to 0.43 when lightning assimilation is used. Statistical measures of near-surface meteorological variables also are improved. Consistent improvements also are seen for the July 2013 case. These results suggest that this lightning assimilation technique has the potential to substantially improve simulation of warm-season rainfall in retrospective WRF appli

Stable Isotope Anatomy of Tropical Cyclone Ita, North-Eastern Australia, April 2014

PubMed Central

Munksgaard, Niels C.; Zwart, Costijn; Kurita, Naoyuki; Bass, Adrian; Nott, Jon; Bird, Michael I.

2015-01-01

The isotope signatures registered in speleothems during tropical cyclones (TC) provides information about the frequency and intensity of past TCs but the precise relationship between isotopic composition and the meteorology of TCs remain uncertain. Here we present continuous δ18O and δ2H data in rainfall and water vapour, as well as in discrete rainfall samples, during the passage of TC Ita and relate the evolution in isotopic compositions to local and synoptic scale meteorological observations. High-resolution data revealed a close relationship between isotopic compositions and cyclonic features such as spiral rainbands, periods of stratiform rainfall and the arrival of subtropical and tropical air masses with changing oceanic and continental moisture sources. The isotopic compositions in discrete rainfall samples were remarkably constant along the ~450 km overland path of the cyclone when taking into account the direction and distance to the eye of the cyclone at each sampling time. Near simultaneous variations in δ18O and δ2H values in rainfall and vapour and a near-equilibrium rainfall-vapour isotope fractionation indicates strong isotopic exchange between rainfall and surface inflow of vapour during the approach of the cyclone. In contrast, after the passage of spiral rainbands close to the eye of the cyclone, different moisture sources for rainfall and vapour are reflected in diverging d-excess values. High-resolution isotope studies of modern TCs refine the interpretation of stable isotope signatures found in speleothems and other paleo archives and should aim to further investigate the influence of cyclone intensity and longevity on the isotopic composition of associated rainfall. PMID:25742628

Location-Based Rainfall Nowcasting Service for Public

NASA Astrophysics Data System (ADS)

Woo, Wang-chun

2013-04-01

The Hong Kong Observatory has developed the "Short-range Warning of Intense Rainstorms in Localized Systems (SWIRLS)", a radar-based rainfall nowcasting system originally to support forecasters in rainstorm warning and severe weather forecasting such as hail, lightning and strong wind gusts in Hong Kong. The system has since been extended to provide rainfall nowcast service direct for the public in recent years. Following the launch of "Rainfall Nowcast for the Pearl River Delta Region" service provided via a Geographical Information System (GIS) platform in 2008, a location-based rainfall nowcast service served through "MyObservatory", a smartphone app for iOS and Android developed by the Observatory, debuted in September 2012. The new service takes advantage of the capability of smartphones to detect own locations and utilizes the quantitative precipitation forecast (QPF) from SWIRLS to provide location-based rainfall nowcast to the public. The conversion of radar reflectivity data (at 2 or 3 km above ground) to rainfall in SWIRLS is based on the Z-R relationship (Z=aRb) with dynamical calibration of the coefficients a and b determined using real-time rain gauge data. Adopting the "Multi-scale Optical-flow by Variational Analysis (MOVA)" scheme to track the movement of radar echoes and Semi-Lagrangian Advection (SLA) scheme to extrapolate their movement, the system is capable of producing QPF for the next six hours in a grid of 480 x 480 that covers a domain of 256 km x 256 km once every 6 minutes. Referencing the closest point in a resampled 2-km grid over the territory of Hong Kong, a prediction as to whether there will be rainfall exceeding 0.5 mm in every 30 minute intervals for the next two hours at users' own or designated locations are made available to the users in both textual and graphical format. For those users who have opted to receive notifications, a message would pop up on the user's phone whenever rain is predicted in the next two hours in a user-configurable manner. Verification indicates that the service achieves a detection rate of 76% and a false alarm rate of 26% in the first 30 minute forecast. The skill decreases as the forecast range extends, with the detection rate lowered to 40% and false alarm rate increased to 63% for the two hour forecast. A number of factors affect the accuracy of the forecast, notably the anomalous propagation, the sensitivity and vertical coverage of the radar, as well as the growth and decay of the rain echoes. The service has been gaining popularity rapidly since launch, and has already registered over 12,000 users who have opted for notifications. The successful launch of the location-based rainfall nowcast service in Hong Kong and favourable verification results reveal the high practicality of such services.

Using the Firefly optimization method to weight an ensemble of rainfall forecasts from the Brazilian developments on the Regional Atmospheric Modeling System (BRAMS)

NASA Astrophysics Data System (ADS)

dos Santos, A. F.; Freitas, S. R.; de Mattos, J. G. Z.; de Campos Velho, H. F.; Gan, M. A.; da Luz, E. F. P.; Grell, G. A.

2013-09-01

In this paper we consider an optimization problem applying the metaheuristic Firefly algorithm (FY) to weight an ensemble of rainfall forecasts from daily precipitation simulations with the Brazilian developments on the Regional Atmospheric Modeling System (BRAMS) over South America during January 2006. The method is addressed as a parameter estimation problem to weight the ensemble of precipitation forecasts carried out using different options of the convective parameterization scheme. Ensemble simulations were performed using different choices of closures, representing different formulations of dynamic control (the modulation of convection by the environment) in a deep convection scheme. The optimization problem is solved as an inverse problem of parameter estimation. The application and validation of the methodology is carried out using daily precipitation fields, defined over South America and obtained by merging remote sensing estimations with rain gauge observations. The quadratic difference between the model and observed data was used as the objective function to determine the best combination of the ensemble members to reproduce the observations. To reduce the model rainfall biases, the set of weights determined by the algorithm is used to weight members of an ensemble of model simulations in order to compute a new precipitation field that represents the observed precipitation as closely as possible. The validation of the methodology is carried out using classical statistical scores. The algorithm has produced the best combination of the weights, resulting in a new precipitation field closest to the observations.

Simulating the complex output of rainfall and hydrological processes using the information contained in large data sets: the Direct Sampling approach.

NASA Astrophysics Data System (ADS)

Oriani, Fabio

2017-04-01

The unpredictable nature of rainfall makes its estimation as much difficult as it is essential to hydrological applications. Stochastic simulation is often considered a convenient approach to asses the uncertainty of rainfall processes, but preserving their irregular behavior and variability at multiple scales is a challenge even for the most advanced techniques. In this presentation, an overview on the Direct Sampling technique [1] and its recent application to rainfall and hydrological data simulation [2, 3] is given. The algorithm, having its roots in multiple-point statistics, makes use of a training data set to simulate the outcome of a process without inferring any explicit probability measure: the data are simulated in time or space by sampling the training data set where a sufficiently similar group of neighbor data exists. This approach allows preserving complex statistical dependencies at different scales with a good approximation, while reducing the parameterization to the minimum. The straights and weaknesses of the Direct Sampling approach are shown through a series of applications to rainfall and hydrological data: from time-series simulation to spatial rainfall fields conditioned by elevation or a climate scenario. In the era of vast databases, is this data-driven approach a valid alternative to parametric simulation techniques? [1] Mariethoz G., Renard P., and Straubhaar J. (2010), The Direct Sampling method to perform multiple-point geostatistical simulations, Water. Rerous. Res., 46(11), http://dx.doi.org/10.1029/2008WR007621 [2] Oriani F., Straubhaar J., Renard P., and Mariethoz G. (2014), Simulation of rainfall time series from different climatic regions using the direct sampling technique, Hydrol. Earth Syst. Sci., 18, 3015-3031, http://dx.doi.org/10.5194/hess-18-3015-2014 [3] Oriani F., Borghi A., Straubhaar J., Mariethoz G., Renard P. (2016), Missing data simulation inside flow rate time-series using multiple-point statistics, Environ. Model. Softw., vol. 86, pp. 264 - 276, http://dx.doi.org/10.1016/j.envsoft.2016.10.002

Seasonality on the rainfall partitioning of a fast-growing tree plantation under Mediterranean conditions

NASA Astrophysics Data System (ADS)

molina, antonio; llorens, pilar; biel, carme

2014-05-01

Studies on rainfall interception in fast-growing tree plantations are less numerous than those in natural forests. Trees in these plantations are regularly distributed, and the canopy cover is clumped but changes quickly, resulting on high variability in the volume and composition of water that reach the soil. In addition, irrigation supply is normally required in semiarid areas to get optimal wood production; consequently, knowing rainfall interception and its yearly evolution is crucial to manage the irrigation scheme properly. This work studies the rainfall partitioning seasonality in a cherry tree (Prunus avium) plantation orientated to timber production under Mediterranean conditions. The monitoring design started on March 2012 and consists of a set of 58 throughfall tipping buckets randomly distributed (based on a 1x1 m2 grid) in a plot of 128 m2 with 8 trees. Stemflow is measured in all the trees with 2 tipping buckets and 6 accumulative collectors. Canopy cover is regularly measured throughout the study period, in leaf and leafless periods, by mean of sky-orientated photographs taken 50 cm above the center of each tipping bucket. Others tree biometrics are also measured such as diameter and leaf area index. Meteorological conditions are measured at 2 m above the forest cover. This work presents the first analyses describing the rainfall partitioning and its dependency on canopy cover, distance to tree and meteorological conditions. The modified Gash' model for rainfall interception in dispersed vegetation is also preliminary evaluated.

Regionalisation of a distributed method for flood quantiles estimation: Revaluation of local calibration hypothesis to enhance the spatial structure of the optimised parameter

NASA Astrophysics Data System (ADS)

Odry, Jean; Arnaud, Patrick

2016-04-01

The SHYREG method (Aubert et al., 2014) associates a stochastic rainfall generator and a rainfall-runoff model to produce rainfall and flood quantiles on a 1 km2 mesh covering the whole French territory. The rainfall generator is based on the description of rainy events by descriptive variables following probability distributions and is characterised by a high stability. This stochastic generator is fully regionalised, and the rainfall-runoff transformation is calibrated with a single parameter. Thanks to the stability of the approach, calibration can be performed against only flood quantiles associated with observated frequencies which can be extracted from relatively short time series. The aggregation of SHYREG flood quantiles to the catchment scale is performed using an areal reduction factor technique unique on the whole territory. Past studies demonstrated the accuracy of SHYREG flood quantiles estimation for catchments where flow data are available (Arnaud et al., 2015). Nevertheless, the parameter of the rainfall-runoff model is independently calibrated for each target catchment. As a consequence, this parameter plays a corrective role and compensates approximations and modelling errors which makes difficult to identify its proper spatial pattern. It is an inherent objective of the SHYREG approach to be completely regionalised in order to provide a complete and accurate flood quantiles database throughout France. Consequently, it appears necessary to identify the model configuration in which the calibrated parameter could be regionalised with acceptable performances. The revaluation of some of the method hypothesis is a necessary step before the regionalisation. Especially the inclusion or the modification of the spatial variability of imposed parameters (like production and transfer reservoir size, base flow addition and quantiles aggregation function) should lead to more realistic values of the only calibrated parameter. The objective of the work presented here is to develop a SHYREG evaluation scheme focusing on both local and regional performances. Indeed, it is necessary to maintain the accuracy of at site flood quantiles estimation while identifying a configuration leading to a satisfactory spatial pattern of the calibrated parameter. This ability to be regionalised can be appraised by the association of common regionalisation techniques and split sample validation tests on a set of around 1,500 catchments representing the whole diversity of France physiography. Also, the presence of many nested catchments and a size-based split sample validation make possible to assess the relevance of the calibrated parameter spatial structure inside the largest catchments. The application of this multi-objective evaluation leads to the selection of a version of SHYREG more suitable for regionalisation. References: Arnaud, P., Cantet, P., Aubert, Y., 2015. Relevance of an at-site flood frequency analysis method for extreme events based on stochastic simulation of hourly rainfall. Hydrological Sciences Journal: on press. DOI:10.1080/02626667.2014.965174 Aubert, Y., Arnaud, P., Ribstein, P., Fine, J.A., 2014. The SHYREG flow method-application to 1605 basins in metropolitan France. Hydrological Sciences Journal, 59(5): 993-1005. DOI:10.1080/02626667.2014.902061

Improving operational flood ensemble prediction by the assimilation of satellite soil moisture: comparison between lumped and semi-distributed schemes

USDA-ARS?s Scientific Manuscript database

Assimilation of remotely sensed soil moisture data (SM-DA) to correct soil water stores of rainfall-runoff models has shown skill in improving streamflow prediction. In the case of large and sparsely monitored catchments, SM-DA is a particularly attractive tool.Within this context, we assimilate act...

A Metastatistical Approach to Satellite Estimates of Extreme Rainfall Events

NASA Astrophysics Data System (ADS)

Zorzetto, E.; Marani, M.

2017-12-01

The estimation of the average recurrence interval of intense rainfall events is a central issue for both hydrologic modeling and engineering design. These estimates require the inference of the properties of the right tail of the statistical distribution of precipitation, a task often performed using the Generalized Extreme Value (GEV) distribution, estimated either from a samples of annual maxima (AM) or with a peaks over threshold (POT) approach. However, these approaches require long and homogeneous rainfall records, which often are not available, especially in the case of remote-sensed rainfall datasets. We use here, and tailor it to remotely-sensed rainfall estimates, an alternative approach, based on the metastatistical extreme value distribution (MEVD), which produces estimates of rainfall extreme values based on the probability distribution function (pdf) of all measured `ordinary' rainfall event. This methodology also accounts for the interannual variations observed in the pdf of daily rainfall by integrating over the sample space of its random parameters. We illustrate the application of this framework to the TRMM Multi-satellite Precipitation Analysis rainfall dataset, where MEVD optimally exploits the relatively short datasets of satellite-sensed rainfall, while taking full advantage of its high spatial resolution and quasi-global coverage. Accuracy of TRMM precipitation estimates and scale issues are here investigated for a case study located in the Little Washita watershed, Oklahoma, using a dense network of rain gauges for independent ground validation. The methodology contributes to our understanding of the risk of extreme rainfall events, as it allows i) an optimal use of the TRMM datasets in estimating the tail of the probability distribution of daily rainfall, and ii) a global mapping of daily rainfall extremes and distributional tail properties, bridging the existing gaps in rain gauges networks.

Physical Validation of TRMM TMI and PR Monthly Rain Products Over Oklahoma

NASA Technical Reports Server (NTRS)

Fisher, Brad L.

2004-01-01

The Tropical Rainfall Measuring Mission (TRMM) provides monthly rainfall estimates using data collected by the TRMM satellite. These estimates cover a substantial fraction of the earth's surface. The physical validation of TRMM estimates involves corroborating the accuracy of spaceborne estimates of areal rainfall by inferring errors and biases from ground-based rain estimates. The TRMM error budget consists of two major sources of error: retrieval and sampling. Sampling errors are intrinsic to the process of estimating monthly rainfall and occur because the satellite extrapolates monthly rainfall from a small subset of measurements collected only during satellite overpasses. Retrieval errors, on the other hand, are related to the process of collecting measurements while the satellite is overhead. One of the big challenges confronting the TRMM validation effort is how to best estimate these two main components of the TRMM error budget, which are not easily decoupled. This four-year study computed bulk sampling and retrieval errors for the TRMM microwave imager (TMI) and the precipitation radar (PR) by applying a technique that sub-samples gauge data at TRMM overpass times. Gridded monthly rain estimates are then computed from the monthly bulk statistics of the collected samples, providing a sensor-dependent gauge rain estimate that is assumed to include a TRMM equivalent sampling error. The sub-sampled gauge rain estimates are then used in conjunction with the monthly satellite and gauge (without sub- sampling) estimates to decouple retrieval and sampling errors. The computed mean sampling errors for the TMI and PR were 5.9% and 7.796, respectively, in good agreement with theoretical predictions. The PR year-to-year retrieval biases exceeded corresponding TMI biases, but it was found that these differences were partially due to negative TMI biases during cold months and positive TMI biases during warm months.

Impact of spatial and temporal aggregation of input parameters on the assessment of irrigation scheme performance

NASA Astrophysics Data System (ADS)

Lorite, I. J.; Mateos, L.; Fereres, E.

2005-01-01

SummaryThe simulations of dynamic, spatially distributed non-linear models are impacted by the degree of spatial and temporal aggregation of their input parameters and variables. This paper deals with the impact of these aggregations on the assessment of irrigation scheme performance by simulating water use and crop yield. The analysis was carried out on a 7000 ha irrigation scheme located in Southern Spain. Four irrigation seasons differing in rainfall patterns were simulated (from 1996/1997 to 1999/2000) with the actual soil parameters and with hypothetical soil parameters representing wider ranges of soil variability. Three spatial aggregation levels were considered: (I) individual parcels (about 800), (II) command areas (83) and (III) the whole irrigation scheme. Equally, five temporal aggregation levels were defined: daily, weekly, monthly, quarterly and annually. The results showed little impact of spatial aggregation in the predictions of irrigation requirements and of crop yield for the scheme. The impact of aggregation was greater in rainy years, for deep-rooted crops (sunflower) and in scenarios with heterogeneous soils. The highest impact on irrigation requirement estimations was in the scenario of most heterogeneous soil and in 1999/2000, a year with frequent rainfall during the irrigation season: difference of 7% between aggregation levels I and III was found. Equally, it was found that temporal aggregation had only significant impact on irrigation requirements predictions for time steps longer than 4 months. In general, simulated annual irrigation requirements decreased as the time step increased. The impact was greater in rainy years (specially with abundant and concentrated rain events) and in crops which cycles coincide in part with the rainy season (garlic, winter cereals and olive). It is concluded that in this case, average, representative values for the main inputs of the model (crop, soil properties and sowing dates) can generate results within 1% of those obtained by providing spatially specific values for about 800 parcels.

A Robust Multi-Scale Modeling System for the Study of Cloud and Precipitation Processes

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo

2012-01-01

During the past decade, numerical weather and global non-hydrostatic models have started using more complex microphysical schemes originally developed for high resolution cloud resolving models (CRMs) with 1-2 km or less horizontal resolutions. These microphysical schemes affect the dynamic through the release of latent heat (buoyancy loading and pressure gradient) the radiation through the cloud coverage (vertical distribution of cloud species), and surface processes through rainfall (both amount and intensity). Recently, several major improvements of ice microphysical processes (or schemes) have been developed for cloud-resolving model (Goddard Cumulus Ensemble, GCE, model) and regional scale (Weather Research and Forecast, WRF) model. These improvements include an improved 3-ICE (cloud ice, snow and graupel) scheme (Lang et al. 2010); a 4-ICE (cloud ice, snow, graupel and hail) scheme and a spectral bin microphysics scheme and two different two-moment microphysics schemes. The performance of these schemes has been evaluated by using observational data from TRMM and other major field campaigns. In this talk, we will present the high-resolution (1 km) GeE and WRF model simulations and compared the simulated model results with observation from recent field campaigns [i.e., midlatitude continental spring season (MC3E; 2010), high latitude cold-season (C3VP, 2007; GCPEx, 2012), and tropical oceanic (TWP-ICE, 2006)].

Accounting for rainfall evaporation using dual-polarization radar and mesoscale model data

NASA Astrophysics Data System (ADS)

Pallardy, Quinn; Fox, Neil I.

2018-02-01

Implementation of dual-polarization radar should allow for improvements in quantitative precipitation estimates due to dual-polarization capability allowing for the retrieval of the second moment of the gamma drop size distribution. Knowledge of the shape of the DSD can then be used in combination with mesoscale model data to estimate the motion and evaporation of each size of drop falling from the height at which precipitation is observed by the radar to the surface. Using data from Central Missouri at a range between 130 and 140 km from the operational National Weather Service radar a rain drop tracing scheme was developed to account for the effects of evaporation, where individual raindrops hitting the ground were traced to the point in space and time where they interacted with the radar beam. The results indicated evaporation played a significant role in radar rainfall estimation in situations where the atmosphere was relatively dry. Improvements in radar estimated rainfall were also found in these situations by accounting for evaporation. The conclusion was made that the effects of raindrop evaporation were significant enough to warrant further research into the inclusion high resolution model data in the radar rainfall estimation process for appropriate locations.

Improving the accuracy of flood forecasting with transpositions of ensemble NWP rainfall fields considering orographic effects

NASA Astrophysics Data System (ADS)

Yu, Wansik; Nakakita, Eiichi; Kim, Sunmin; Yamaguchi, Kosei

2016-08-01

The use of meteorological ensembles to produce sets of hydrological predictions increased the capability to issue flood warnings. However, space scale of the hydrological domain is still much finer than meteorological model, and NWP models have challenges with displacement. The main objective of this study to enhance the transposition method proposed in Yu et al. (2014) and to suggest the post-processing ensemble flood forecasting method for the real-time updating and the accuracy improvement of flood forecasts that considers the separation of the orographic rainfall and the correction of misplaced rain distributions using additional ensemble information through the transposition of rain distributions. In the first step of the proposed method, ensemble forecast rainfalls from a numerical weather prediction (NWP) model are separated into orographic and non-orographic rainfall fields using atmospheric variables and the extraction of topographic effect. Then the non-orographic rainfall fields are examined by the transposition scheme to produce additional ensemble information and new ensemble NWP rainfall fields are calculated by recombining the transposition results of non-orographic rain fields with separated orographic rainfall fields for a generation of place-corrected ensemble information. Then, the additional ensemble information is applied into a hydrologic model for post-flood forecasting with a 6-h interval. The newly proposed method has a clear advantage to improve the accuracy of mean value of ensemble flood forecasting. Our study is carried out and verified using the largest flood event by typhoon 'Talas' of 2011 over the two catchments, which are Futatsuno (356.1 km2) and Nanairo (182.1 km2) dam catchments of Shingu river basin (2360 km2), which is located in the Kii peninsula, Japan.

Quasi-continuous stochastic simulation framework for flood modelling

NASA Astrophysics Data System (ADS)

Moustakis, Yiannis; Kossieris, Panagiotis; Tsoukalas, Ioannis; Efstratiadis, Andreas

2017-04-01

Typically, flood modelling in the context of everyday engineering practices is addressed through event-based deterministic tools, e.g., the well-known SCS-CN method. A major shortcoming of such approaches is the ignorance of uncertainty, which is associated with the variability of soil moisture conditions and the variability of rainfall during the storm event.In event-based modeling, the sole expression of uncertainty is the return period of the design storm, which is assumed to represent the acceptable risk of all output quantities (flood volume, peak discharge, etc.). On the other hand, the varying antecedent soil moisture conditions across the basin are represented by means of scenarios (e.g., the three AMC types by SCS),while the temporal distribution of rainfall is represented through standard deterministic patterns (e.g., the alternative blocks method). In order to address these major inconsistencies,simultaneously preserving the simplicity and parsimony of the SCS-CN method, we have developed a quasi-continuous stochastic simulation approach, comprising the following steps: (1) generation of synthetic daily rainfall time series; (2) update of potential maximum soil moisture retention, on the basis of accumulated five-day rainfall; (3) estimation of daily runoff through the SCS-CN formula, using as inputs the daily rainfall and the updated value of soil moisture retention;(4) selection of extreme events and application of the standard SCS-CN procedure for each specific event, on the basis of synthetic rainfall.This scheme requires the use of two stochastic modelling components, namely the CastaliaR model, for the generation of synthetic daily data, and the HyetosMinute model, for the disaggregation of daily rainfall to finer temporal scales. Outcomes of this approach are a large number of synthetic flood events, allowing for expressing the design variables in statistical terms and thus properly evaluating the flood risk.

Influence of Superparameterization and a Higher-Order Turbulence Closure on Rainfall Bias Over Amazonia in Community Atmosphere Model Version 5: How Parameterization Changes Rainfall

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

Zhang, Kai; Fu, Rong; Shaikh, Muhammad J.

We evaluate the Community Atmosphere Model Version 5 (CAM5) with a higher-order turbulence closure scheme, named Cloud Layers Unified By Binomials (CLUBB), and a Multiscale Modeling Framework (MMF) with two different microphysics configurations to investigate their influences on rainfall simulations over Southern Amazonia. The two different microphysics configurations in MMF are the one-moment cloud microphysics without aerosol treatment (SAM1MOM) and two-moment cloud microphysics coupled with aerosol treatment (SAM2MOM). Results show that both MMF-SAM2MOM and CLUBB effectively reduce the low biases of rainfall, mainly during the wet season. The CLUBB reduces low biases of humidity in the lower troposphere with furthermore » reduced shallow clouds. The latter enables more surface solar flux, leading to stronger convection and more rainfall. MMF, especially MMF-SAM2MOM, unstablizes the atmosphere with more moisture and higher atmospheric temperatures in the atmospheric boundary layer, allowing the growth of more extreme convection and further generating more deep convection. MMF-SAM2MOM significantly increases rainfall in the afternoon, but it does not reduce the early bias of the diurnal rainfall peak; LUBB, on the other hand, delays the afternoon peak time and produces more precipitation in the early morning, due to more realistic gradual transition between shallow and deep convection. MMF appears to be able to realistically capture the observed increase of relative humidity prior to deep convection, especially with its two-moment configuration. In contrast, in CAM5 and CAM5 with CLUBB, occurrence of deep convection in these models appears to be a result of stronger heating rather than higher relative humidity.« less

Multiscale characterization and prediction of monsoon rainfall in India using Hilbert-Huang transform and time-dependent intrinsic correlation analysis

NASA Astrophysics Data System (ADS)

Adarsh, S.; Reddy, M. Janga

2017-07-01

In this paper, the Hilbert-Huang transform (HHT) approach is used for the multiscale characterization of All India Summer Monsoon Rainfall (AISMR) time series and monsoon rainfall time series from five homogeneous regions in India. The study employs the Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) for multiscale decomposition of monsoon rainfall in India and uses the Normalized Hilbert Transform and Direct Quadrature (NHT-DQ) scheme for the time-frequency characterization. The cross-correlation analysis between orthogonal modes of All India monthly monsoon rainfall time series and that of five climate indices such as Quasi Biennial Oscillation (QBO), El Niño Southern Oscillation (ENSO), Sunspot Number (SN), Atlantic Multi Decadal Oscillation (AMO), and Equatorial Indian Ocean Oscillation (EQUINOO) in the time domain showed that the links of different climate indices with monsoon rainfall are expressed well only for few low-frequency modes and for the trend component. Furthermore, this paper investigated the hydro-climatic teleconnection of ISMR in multiple time scales using the HHT-based running correlation analysis technique called time-dependent intrinsic correlation (TDIC). The results showed that both the strength and nature of association between different climate indices and ISMR vary with time scale. Stemming from this finding, a methodology employing Multivariate extension of EMD and Stepwise Linear Regression (MEMD-SLR) is proposed for prediction of monsoon rainfall in India. The proposed MEMD-SLR method clearly exhibited superior performance over the IMD operational forecast, M5 Model Tree (MT), and multiple linear regression methods in ISMR predictions and displayed excellent predictive skill during 1989-2012 including the four extreme events that have occurred during this period.

Stormwater-runoff data, Madison, Wisconsin, 1993-94

USGS Publications Warehouse

Waschbusch, R.J.

1996-01-01

As required by Section 402(P) of the Water Quality Control Act of 1987, stormwater-runoff samples collected during storms that met three criteria (rainfall depths 50 to 150 percent of average depth range, rainfall durations 50 to 150 percent of average duration, and antecedent dry-weather period of at least 72 hours) were analyzed for semivolatile organic chemicals, total metals, pesticides, polychlorinated biphenyls, inorganic constituents, bacteria, oil and grease, pH, and water temperature. Two of the seven sites also had samples analyzed for volatile organic chemicals. In addition to the required sampling, additional runoff samples that did not necessarily meet the three rainfall criteria, were analyzed for total metals and inorganic constituents. Storm loads of selected constituents were computed.

Influence of the balance of the intertropical front on seasonal variations of the isotopic composition in rainfall at Kisiba Masoko (Rungwe Volcanic Province, SW, Tanzania).

PubMed

Nivet, Fantine; Bergonzini, Laurent; Mathé, Pierre-Etienne; Noret, Aurélie; Monvoisin, Gaël; Majule, Amos; Williamson, David

2018-08-01

Tropical rainfall isotopic composition results from complex processes. The climatological and environmental variability in East Africa increases this complexity. Long rainfall isotope datasets are needed to fill the lack of observations in this region. At Kisiba Masoko, Tanzania, rainfall and rain isotopic composition have been monitored during 6 years. Mean year profiles allow to analyse the seasonal variations. The mean annual rainfall is 2099 mm with a rain-weighted mean composition of -3.2 ‰ for δ 18 O and -11.7 ‰ for δ 2 H. The results are consistent with available data although they present their own specificity. Thus, if the local meteoric water line is δ 2 H = 8.6 δ 18 O + 14.8, two seasonal lines are observed. The seasonality of the isotopic composition in rain and deuterium excess has been compared with precipitating air masses backtracking trajectories to characterize a simple scheme of vapour histories. The three major oceanic sources have two moisture signatures with their own trajectory histories: one originated from the tropical Indian Ocean at the beginning of the rainy season and one from the Austral Ocean at its end. The presented isotopic seasonality depends on the balance of the intertropical front and provides a useful dataset to improve the knowledge about local processes.

Fine-tuning satellite-based rainfall estimates

NASA Astrophysics Data System (ADS)

Harsa, Hastuadi; Buono, Agus; Hidayat, Rahmat; Achyar, Jaumil; Noviati, Sri; Kurniawan, Roni; Praja, Alfan S.

2018-05-01

Rainfall datasets are available from various sources, including satellite estimates and ground observation. The locations of ground observation scatter sparsely. Therefore, the use of satellite estimates is advantageous, because satellite estimates can provide data on places where the ground observations do not present. However, in general, the satellite estimates data contain bias, since they are product of algorithms that transform the sensors response into rainfall values. Another cause may come from the number of ground observations used by the algorithms as the reference in determining the rainfall values. This paper describe the application of bias correction method to modify the satellite-based dataset by adding a number of ground observation locations that have not been used before by the algorithm. The bias correction was performed by utilizing Quantile Mapping procedure between ground observation data and satellite estimates data. Since Quantile Mapping required mean and standard deviation of both the reference and the being-corrected data, thus the Inverse Distance Weighting scheme was applied beforehand to the mean and standard deviation of the observation data in order to provide a spatial composition of them, which were originally scattered. Therefore, it was possible to provide a reference data point at the same location with that of the satellite estimates. The results show that the new dataset have statistically better representation of the rainfall values recorded by the ground observation than the previous dataset.

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.

An investigation of the effects of an arterial drainage scheme on the rainfall-runoff transformation behaviour of the Brosna catchment in Ireland

NASA Astrophysics Data System (ADS)

Bhattarai, K. P.; O'Connor, K. M.

2003-04-01

Inefficient natural land drainage and the consequent frequent flooding of rivers are a problem of particular significance to the Irish economy. Such problems can be attributed less to the amount of annual rainfall, than to the topological configuration of Ireland. Its high maritime rim and relatively flat interior results in poor river gradients, intercepted by many lakes. As a remedial measure to tackle these problems, Arterial Drainage Schemes (ADSs) were started in Ireland from as early as the beginning of the nineteenth century. The major activities carried out under ADSs have been the deepening and widening of channels to increase their discharge-carrying capacity, which naturally affected the hydrological behaviour of the catchments involved. Earlier studies carried out in order to assess the effects of such ADSs on the hydrological behaviour of Irish catchments were concentrated mainly on comparisons of unit hydrographs and relationship between flood peaks of pre- and post-drainage periods. The present study, carried out on the River Brosna catchment in Ireland, concentrates on assessing the changes in the rainfall runoff transformation process, by using the conceptual Soil Moisture Accounting and Routing Model (SMAR), one of the constituent models of the "Galway River Flow Modelling and Forecasting System (GFMFS)" software package. Hydro-meteorological data of the pre-drainage (1942--1947) and post-drainage (1954--2000) periods have been used in this study. The results of the present study show that, for similar patterns of rainfall, the catchment produces higher annual maximum daily flows, and lower annual minimum daily flows in the post-drainage period than in the pre-drainage period. Moreover, the post-drainage unit hydrographs are more "peaky" and have quicker recessions than the pre-drainage counterparts, thus confirming the findings of the earlier studies. It is also observed that, apart from the expected pre-to-post-drainage change, the nature of the catchment response throughout the post-drainage period has not remained the same as it reverted to pre-drainage-like behaviour after the first one-and-a-half decades (around 1969), indicating that the effects of the ADS had died out over that time. This behaviour was also confirmed by comparing the evolving nature of the unit hydrograph produced for a five-year moving calibration window period from 1959 to 1974. It is unclear at this point whether this change was due to the observed reduction in rainfall in the mid-seventies, inefficient maintenance of the channels, land subsidence following drainage, changes in land use, urbanization, climate change, or some other factors or combinations. The results of the present study further show that, during the nineties, the response pattern changed back again to something akin to early post-drainage-like behaviour, the reason for which is even less clear but obviously can not be attributed to the ADS. Further investigations are currently underway to try to explain such changes in the catchment response to rainfall and also to establish if similar changes occurred on other Irish catchments which also underwent arterial drainage schemes.

Dynamic root distributions in ecohydrological modeling: A case study at Walnut Gulch Experimental Watershed

NASA Astrophysics Data System (ADS)

Sivandran, Gajan; Bras, Rafael L.

2013-06-01

Arid regions are characterized by high variability in the arrival of rainfall, and species found in these areas have adapted mechanisms to ensure the capture of this scarce resource. In particular, the rooting strategies employed by vegetation can be critical to their survival. However, land surface models currently prescribe rooting profiles as a function of only the plant functional type of interest with no consideration for the soil texture or rainfall regime of the region being modeled. Additionally, these models do not incorporate the ability of vegetation to dynamically alter their rooting strategies in response to transient changes in environmental forcings or competition from other plant species and therefore tend to underestimate the resilience of these ecosystems. To address the simplicity of the current representation of roots in land surface models, a new dynamic rooting scheme was incorporated into the framework of the distributed ecohydrological model tRIBS+VEGGIE. The new scheme optimizes the allocation of carbon to the root zone to reduce the perceived stress of the vegetation, so that root profiles evolve based upon local climate and soil conditions. The ability of the new scheme to capture the complex dynamics of natural systems was evaluated by comparisons to hourly timescale energy flux, soil moisture, and vegetation growth observations from the Walnut Gulch Experimental Watershed, Arizona. Robust agreement was found between the model and observations, providing confidence that the improved model is able to capture the multidirectional interactions between climate, soil, and vegetation at this site.

Statistical description of large datasets of Cumulated and Duration values related to shallow landslides initiated by rainfalls

NASA Astrophysics Data System (ADS)

Pisano, Luca; Vessia, Giovanna; Vennari, Carmela; Parise, Mario

2015-04-01

Empirical rainfall thresholds are a well established method to draw information about Duration (D) and Cumulated (E) values of the rainfalls that are likely to initiate shallow landslides. To this end, rain-gauge records of rainfall heights are commonly used. Several procedures can be applied to address the calculation of the Duration-Cumulated height and, eventually, the Intensity values related to the rainfall events responsible for shallow landslide onset. A large number of procedures are drawn from particular geological settings and climate conditions based on an expert identification of the rainfall event. A few researchers recently devised automated procedures to reconstruct the rainfall events responsible for landslide onset. In this study, 300 pairs of D, E couples, related to shallow landslides that occurred in a ten year span 2002-2012 on the Italian territory, have been drawn by means of two procedures: the expert method (Brunetti et al., 2010) and the automated method (Vessia et al., 2014). The two procedures start from the same sources of information on shallow landslides occurred during or soon after a rainfall. Although they have in common the method to select the date (up to the hour of the landslide occurrence), the site of the landslide and the choice of the rain-gauge representative for the rainfall, they differ when calculating the Duration and Cumulated height of the rainfall event. Moreover, the expert procedure identifies only one D, E pair for each landslide whereas the automated procedure draws 6 possible D,E pairs for the same landslide event. Each one of the 300 D, E pairs calculated by the automated procedure reproduces about 80% of the E values and about 60% of the D values calculated by the expert procedure. Unfortunately, no standard methods are available for checking the forecasting ability of both the expert and the automated reconstruction of the true D, E pairs that result in shallow landslide. Nonetheless, a statistical analysis on marginal distributions of the seven samples of 300 D and E values are performed in this study. The main objective of this statistical analysis is to highlight similarities and differences in the two sets of samples of Duration and Cumulated values collected by the two procedures. At first, the sample distributions have been investigated: the seven E samples are Lognormal distributed, whereas the D samples are all distributed Weibull like. On E samples, due to their Lognormal distribution, statistical tests can be applied to check two null hypotheses: equal mean values through the Student test, equal standard deviations through the Fisher test. These two hypotheses are accepted for the seven E samples, meaning that they come from the same population, at a confidence level of 95%. Conversely, the preceding tests cannot be applied to the seven D samples that are Weibull distributed with shape parameters k ranging between 0.9 to 1.2. Nonetheless, the two procedures calculate the rainfall event through the selection of the E values; after that the D is drawn. Thus, the results of this statistical analysis preliminary confirms the similarities of the two D,E pair set of values drawn from the two different procedures. References Brunetti, M.T., Peruccacci, S., Rossi, M., Luciani, S., Valigi, D., and Guzzetti, F.: Rainfall thresholds for the possible occurrence of landslides in Italy, Nat. Hazards Earth Syst. Sci., 10, 447-458, doi:10.5194/nhess-10-447-2010, 2010. Vessia G., Parise M., Brunetti M.T., Peruccacci S., Rossi M., Vennari C., and Guzzetti F.: Automated reconstruction of rainfall events responsible for shallow landslides, Nat. Hazards Earth Syst. Sci., 14, 2399-2408, doi: 10.5194/nhess-14-2399-2014, 2014.

Agricultural Spray Drift Concentrations in Rainwater, Stemflow ...

EPA Pesticide Factsheets

In order to study spray drift contribution to non-targeted habitats, pesticide concentrations were measured in stemflow (water flowing down the trunk of a tree during a rain event), rainfall, and amphibians in an agriculturally impacted wetland area near Tifton, Georgia, USA. Agricultural fields and sampling locations were located on the University of Georgia's Gibbs research farm. Samples were analyzed for >150 pesticides and over 20 different pesticides were detected in these matrices. Data indicated that herbicides (metolachlor and atrazine) and fungicides (tebuconazole) were present with the highest concentrations in stemflow, followed by those in rainfall and amphibian tissue samples. Metolachlor had the highest frequency of detection and highest concentration in rainfall and stemflow samples. Higher concentrations of pesticides were observed in stemflow for a longer period than rainfall. Furthermore, rainfall and stemflow concentrations were compared against aquatic life benchmarks and environmental water screening values to determine if adverse effects would potentially occur for non-targeted organisms. Of the pesticides detected, several had concentrations that exceeded the aquatic life benchmark value. The majority of the time mixtures were present in the different matrices, making it difficult to determine the potential adverse effects that these compounds will have on non-target species, due to unknown potentiating effects. These data help assess the

Evaluating the extreme precipitation events using a mesoscale atmopshere model

NASA Astrophysics Data System (ADS)

Yucel, I.; Onen, A.

2012-04-01

Evidence is showing that global warming or climate change has a direct influence on changes in precipitation and the hydrological cycle. Extreme weather events such as heavy rainfall and flooding are projected to become much more frequent as climate warms. Mesoscale atmospheric models coupled with land surface models provide efficient forecasts for meteorological events in high lead time and therefore they should be used for flood forecasting and warning issues as they provide more continuous monitoring of precipitation over large areas. This study examines the performance of the Weather Research and Forecasting (WRF) model in producing the temporal and spatial characteristics of the number of extreme precipitation events observed in West Black Sea Region of Turkey. Extreme precipitation events usually resulted in flood conditions as an associated hydrologic response of the basin. The performance of the WRF system is further investigated by using the three dimensional variational (3D-VAR) data assimilation scheme within WRF. WRF performance with and without data assimilation at high spatial resolution (4 km) is evaluated by making comparison with gauge precipitation and satellite-estimated rainfall data from Multi Precipitation Estimates (MPE). WRF-derived precipitation showed capabilities in capturing the timing of the precipitation extremes and in some extent spatial distribution and magnitude of the heavy rainfall events. These precipitation characteristics are enhanced with the use of 3D-VAR scheme in WRF system. Data assimilation improved area-averaged precipitation forecasts by 9 percent and at some points there exists quantitative match in precipitation events, which are critical for hydrologic forecast application.

Effects of Raindrop Shape Parameter on the Simulation of Plum Rains

NASA Astrophysics Data System (ADS)

Mei, H.; Zhou, L.; Li, X.; Huang, X.; Guo, W.

2017-12-01

The raindrop shape parameter of particle distribution is generally set as constant in a Double-moment Bulk Microphysics Scheme (DBMS) using Gama distribution function though which suggest huge differences in time and space according to observations. Based on Milbrandt 2-mon(MY) DBMS, four cases during Plum Rains season are simulated coupled with four empirical relationships between shape parameter (μr) and slope parameter of raindrop which have been concluded from observations of raindrop distributions. The analysis of model results suggest that μr have some influences on rainfall. Introducing the diagnostic formulas of μr may have some improvement on systematic biases of 24h accumulated rainfall and show some correction ability on local characteristics of rainfall distribution. Besides,the tendency to improve strong rainfall could be sensitive to μr. With the improvement of the diagnosis of μr using the empirically diagnostic formulas, μr increases generally in the middle- and lower-troposphere and decreases with the stronger rainfall. Its conclued that, the decline in raindrop water content and the increased raindrop mass-weighted average terminal velocity directly related to μr are the direct reasons of variations in the precipitation.On the other side, the environmental conditions including relative humidity and dynamical parameters are the key indirectly causes which has close relationships with the changes in cloud particles and rainfall distributions.Furthermore,the differences in the scale of improvement between the weak and heavy rainfall mainly come from the distinctions of response features about their variable fields respectively. The extent of variation in the features of cloud particles in warm clouds of heavy rainfall differs greatly from that of weak rainfall, though they share the same trend of variation. On the conditions of weak rainfall, the response of physical characteristics to μr performed consistent trends and some linear features. However, environmental conditions of relative humidity and dynamical parameters perform strong and vertically deep adjustments in the heavy precipitation with vigorous cloud systems. In this case, the microphysical processes and environmental conditions experience complex interactions with each other and no significant laws could be concluded.

Sequential sampling: a novel method in farm animal welfare assessment.

PubMed

Heath, C A E; Main, D C J; Mullan, S; Haskell, M J; Browne, W J

2016-02-01

Lameness in dairy cows is an important welfare issue. As part of a welfare assessment, herd level lameness prevalence can be estimated from scoring a sample of animals, where higher levels of accuracy are associated with larger sample sizes. As the financial cost is related to the number of cows sampled, smaller samples are preferred. Sequential sampling schemes have been used for informing decision making in clinical trials. Sequential sampling involves taking samples in stages, where sampling can stop early depending on the estimated lameness prevalence. When welfare assessment is used for a pass/fail decision, a similar approach could be applied to reduce the overall sample size. The sampling schemes proposed here apply the principles of sequential sampling within a diagnostic testing framework. This study develops three sequential sampling schemes of increasing complexity to classify 80 fully assessed UK dairy farms, each with known lameness prevalence. Using the Welfare Quality herd-size-based sampling scheme, the first 'basic' scheme involves two sampling events. At the first sampling event half the Welfare Quality sample size is drawn, and then depending on the outcome, sampling either stops or is continued and the same number of animals is sampled again. In the second 'cautious' scheme, an adaptation is made to ensure that correctly classifying a farm as 'bad' is done with greater certainty. The third scheme is the only scheme to go beyond lameness as a binary measure and investigates the potential for increasing accuracy by incorporating the number of severely lame cows into the decision. The three schemes are evaluated with respect to accuracy and average sample size by running 100 000 simulations for each scheme, and a comparison is made with the fixed size Welfare Quality herd-size-based sampling scheme. All three schemes performed almost as well as the fixed size scheme but with much smaller average sample sizes. For the third scheme, an overall association between lameness prevalence and the proportion of lame cows that were severely lame on a farm was found. However, as this association was found to not be consistent across all farms, the sampling scheme did not prove to be as useful as expected. The preferred scheme was therefore the 'cautious' scheme for which a sampling protocol has also been developed.

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

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

Implementation of reactive and predictive real-time control strategies to optimize dry stormwater detention ponds

NASA Astrophysics Data System (ADS)

Gaborit, Étienne; Anctil, François; Vanrolleghem, Peter A.; Pelletier, Geneviève

2013-04-01

Dry detention ponds have been widely implemented in U.S.A (National Research Council, 1993) and Canada (Shammaa et al. 2002) to mitigate the impacts of urban runoff on receiving water bodies. The aim of such structures is to allow a temporary retention of the water during rainfall events, decreasing runoff velocities and volumes (by infiltration in the pond) as well as providing some water quality improvement from sedimentation. The management of dry detention ponds currently relies on static control through a fixed pre-designed limitation of their maximum outflow (Middleton and Barrett 2008), for example via a proper choice of their outlet pipe diameter. Because these ponds are designed for large storms, typically 1- or 2-hour duration rainfall events with return periods comprised between 5 and 100 years, one of their main drawbacks is that they generally offer almost no retention for smaller rainfall events (Middleton and Barrett 2008), which are by definition much more common. Real-Time Control (RTC) has a high potential for optimizing retention time (Marsalek 2005) because it allows adopting operating strategies that are flexible and hence more suitable to the prevailing fluctuating conditions than static control. For dry ponds, this would basically imply adapting the outlet opening percentage to maximize water retention time, while being able to open it completely for severe storms. This study developed several enhanced RTC scenarios of a dry detention pond located at the outlet of a small urban catchment near Québec City, Canada, following the previous work of Muschalla et al. (2009). The catchment's runoff quantity and TSS concentration were simulated by a SWMM5 model with an improved wash-off formulation. The control procedures rely on rainfall detection and measures of the pond's water height for the reactive schemes, and on rainfall forecasts in addition to these variables for the predictive schemes. The automatic reactive control schemes implemented here increased the pond's TSS (and associated pollution) removal efficiency from 46% (current state) to between 70 and 90%, depending on the pond's capacity considered. The RTC strategies allow simultaneously maximizing the detention time of water, while minimizing the hydraulic shocks induced to the receiving water bodies and preventing overflow. A constraint relative to a maximum time of 4 days with water accumulated in the pond was thus respected to avoid mosquito breeding issues. The predictive control schemes (taking rainfall forecasts into consideration) can further reinforce the safety of the management strategies, even if meteorological forecasts are, of course, not error-free. With RTC, the studied pond capacity could thus have been limited to 1250 m3 instead of the 4000 m3 capacity currently used under static control. References Marsalek, J. 2005. Evolution of urban drainage: from cloaca maxima to environmental sustainability. Paper presented at Acqua e Citta, I Convegno Nazionale di Idraulica Urbana, Cent. Stud. Idraul. Urbana, Sant'Agnello di Sorrento, Italy, 28- 30 Sept. Middleton, J.R. and Barrett, M.E. 2008. Water quality performance of a batch-type stormwater detention basin. Water Environment Research, 80 (2): 172-178. Doi: http://dx.doi.org/10.2175/106143007X220842 Muschalla, D., Pelletier, G., Berrouard, É., Carpenter, J.-F., Vallet, B., and Vanrolleghem, P.A. 2009. Ecohydraulic-driven real-time control of stormwater basins. In: Proceedings 8th International Conference on Urban Drainage Modelling (8UDM), Tokyo, Japan, September 7-11. National Research Council, 1993. Managing Wastewater in Coastal Urban Areas. Washington, DC: National Academy Press. Shammaa, Y., Zhu, D.Z., Gyürék, L.L., and Labatiuk C.W. 2002. Effectiveness of dry ponds for stormwater total suspended solids removal. Canadian Journal of Civil Engineering, 29 (2): 316-324 (9). Doi: 10.1139/l02-008

Random errors of oceanic monthly rainfall derived from SSM/I using probability distribution functions

NASA Technical Reports Server (NTRS)

Chang, Alfred T. C.; Chiu, Long S.; Wilheit, Thomas T.

1993-01-01

Global averages and random errors associated with the monthly oceanic rain rates derived from the Special Sensor Microwave/Imager (SSM/I) data using the technique developed by Wilheit et al. (1991) are computed. Accounting for the beam-filling bias, a global annual average rain rate of 1.26 m is computed. The error estimation scheme is based on the existence of independent (morning and afternoon) estimates of the monthly mean. Calculations show overall random errors of about 50-60 percent for each 5 deg x 5 deg box. The results are insensitive to different sampling strategy (odd and even days of the month). Comparison of the SSM/I estimates with raingage data collected at the Pacific atoll stations showed a low bias of about 8 percent, a correlation of 0.7, and an rms difference of 55 percent.

A new framework for comprehensive, robust, and efficient global sensitivity analysis: 2. Application

NASA Astrophysics Data System (ADS)

Razavi, Saman; Gupta, Hoshin V.

2016-01-01

Based on the theoretical framework for sensitivity analysis called "Variogram Analysis of Response Surfaces" (VARS), developed in the companion paper, we develop and implement a practical "star-based" sampling strategy (called STAR-VARS), for the application of VARS to real-world problems. We also develop a bootstrap approach to provide confidence level estimates for the VARS sensitivity metrics and to evaluate the reliability of inferred factor rankings. The effectiveness, efficiency, and robustness of STAR-VARS are demonstrated via two real-data hydrological case studies (a 5-parameter conceptual rainfall-runoff model and a 45-parameter land surface scheme hydrology model), and a comparison with the "derivative-based" Morris and "variance-based" Sobol approaches are provided. Our results show that STAR-VARS provides reliable and stable assessments of "global" sensitivity across the full range of scales in the factor space, while being 1-2 orders of magnitude more efficient than the Morris or Sobol approaches.

Occurrence analysis of daily rainfalls by using non-homogeneous Poissonian processes

NASA Astrophysics Data System (ADS)

Sirangelo, B.; Ferrari, E.; de Luca, D. L.

2009-09-01

In recent years several temporally homogeneous stochastic models have been applied to describe the rainfall process. In particular stochastic analysis of daily rainfall time series may contribute to explain the statistic features of the temporal variability related to the phenomenon. Due to the evident periodicity of the physical process, these models have to be used only to short temporal intervals in which occurrences and intensities of rainfalls can be considered reliably homogeneous. To this aim, occurrences of daily rainfalls can be considered as a stationary stochastic process in monthly periods. In this context point process models are widely used for at-site analysis of daily rainfall occurrence; they are continuous time series models, and are able to explain intermittent feature of rainfalls and simulate interstorm periods. With a different approach, periodic features of daily rainfalls can be interpreted by using a temporally non-homogeneous stochastic model characterized by parameters expressed as continuous functions in the time. In this case, great attention has to be paid to the parsimony of the models, as regards the number of parameters and the bias introduced into the generation of synthetic series, and to the influence of threshold values in extracting peak storm database from recorded daily rainfall heights. In this work, a stochastic model based on a non-homogeneous Poisson process, characterized by a time-dependent intensity of rainfall occurrence, is employed to explain seasonal effects of daily rainfalls exceeding prefixed threshold values. In particular, variation of rainfall occurrence intensity ? (t) is modelled by using Fourier series analysis, in which the non-homogeneous process is transformed into a homogeneous and unit one through a proper transformation of time domain, and the choice of the minimum number of harmonics is evaluated applying available statistical tests. The procedure is applied to a dataset of rain gauges located in different geographical zones of Mediterranean area. Time series have been selected on the basis of the availability of at least 50 years in the time period 1921-1985, chosen as calibration period, and of all the years of observation in the subsequent validation period 1986-2005, whose daily rainfall occurrence process variability is under hypothesis. Firstly, for each time series and for each fixed threshold value, parameters estimation of the non-homogeneous Poisson model is carried out, referred to calibration period. As second step, in order to test the hypothesis that daily rainfall occurrence process preserves the same behaviour in more recent time periods, the intensity distribution evaluated for calibration period is also adopted for the validation period. Starting from this and using a Monte Carlo approach, 1000 synthetic generations of daily rainfall occurrences, of length equal to validation period, have been carried out, and for each simulation sample ?(t) has been evaluated. This procedure is adopted because of the complexity of determining analytical statistical confidence limits referred to the sample intensity ?(t). Finally, sample intensity, theoretical function of the calibration period and 95% statistical band, evaluated by Monte Carlo approach, are matching, together with considering, for each threshold value, the mean square error (MSE) between the theoretical ?(t) and the sample one of recorded data, and his correspondent 95% one tail statistical band, estimated from the MSE values between the sample ?(t) of each synthetic series and the theoretical one. The results obtained may be very useful in the context of the identification and calibration of stochastic rainfall models based on historical precipitation data. Further applications of the non-homogeneous Poisson model will concern the joint analyses of the storm occurrence process with the rainfall height marks, interpreted by using a temporally homogeneous model in proper sub-year intervals.

Rainfall and runoff quantity and quality data collected at four urban land-use catchments in Fresno, California, October 1981-April 1983

USGS Publications Warehouse

Oltmann, R.N.; Guay, J.R.; Shay, J.M.

1987-01-01

Data were collected as part of the National Urban Runoff Program to characterize urban runoff in Fresno, California. Rainfall-runoff quantity and quality data are included along with atmospheric dry-deposition and street-surface particulate quality data. The data are presented in figures and tables that reflect four land uses: industrial, single-dwelling residential, multiple-dwelling residential, and commercial. A total of 255 storms were monitored for rainfall and runoff quantity. Runoff samples from 112 of these storms were analyzed for physical, organic, inorganic, and biological constituents. The majority of the remaining storms have pH and specific conductance data only. Ninety-two composite rain samples were collected. Of these, 63 were analyzed for physical, inorganic, and (or) organic constituents. The remaining rainfall samples have pH and specific conductance data only. Nineteen atmospheric deposition and 21 street-particulate samples were collected and analyzed for inorganic and organic constituents. The report also details equipment utilization and operation, and discusses data collection methods. (USGS)

Evaluation of monthly rainfall estimates derived from the special sensor microwave/imager (SSM/I) over the tropical Pacific

NASA Technical Reports Server (NTRS)

Berg, Wesley; Avery, Susan K.

1995-01-01

Estimates of monthly rainfall have been computed over the tropical Pacific using passive microwave satellite observations from the special sensor microwave/imager (SSM/I) for the period from July 1987 through December 1990. These monthly estimates are calibrated using data from a network of Pacific atoll rain gauges in order to account for systematic biases and are then compared with several visible and infrared satellite-based rainfall estimation techniques for the purpose of evaluating the performance of the microwave-based estimates. Although several key differences among the various techniques are observed, the general features of the monthly rainfall time series agree very well. Finally, the significant error sources contributing to uncertainties in the monthly estimates are examined and an estimate of the total error is produced. The sampling error characteristics are investigated using data from two SSM/I sensors and a detailed analysis of the characteristics of the diurnal cycle of rainfall over the oceans and its contribution to sampling errors in the monthly SSM/I estimates is made using geosynchronous satellite data. Based on the analysis of the sampling and other error sources the total error was estimated to be of the order of 30 to 50% of the monthly rainfall for estimates averaged over 2.5 deg x 2.5 deg latitude/longitude boxes, with a contribution due to diurnal variability of the order of 10%.

Sampling Errors of SSM/I and TRMM Rainfall Averages: Comparison with Error Estimates from Surface Data and a Sample Model

NASA Technical Reports Server (NTRS)

Bell, Thomas L.; Kundu, Prasun K.; Kummerow, Christian D.; Einaudi, Franco (Technical Monitor)

2000-01-01

Quantitative use of satellite-derived maps of monthly rainfall requires some measure of the accuracy of the satellite estimates. The rainfall estimate for a given map grid box is subject to both remote-sensing error and, in the case of low-orbiting satellites, sampling error due to the limited number of observations of the grid box provided by the satellite. A simple model of rain behavior predicts that Root-mean-square (RMS) random error in grid-box averages should depend in a simple way on the local average rain rate, and the predicted behavior has been seen in simulations using surface rain-gauge and radar data. This relationship was examined using satellite SSM/I data obtained over the western equatorial Pacific during TOGA COARE. RMS error inferred directly from SSM/I rainfall estimates was found to be larger than predicted from surface data, and to depend less on local rain rate than was predicted. Preliminary examination of TRMM microwave estimates shows better agreement with surface data. A simple method of estimating rms error in satellite rainfall estimates is suggested, based on quantities that can be directly computed from the satellite data.

The Global Precipitation Mission

NASA Technical Reports Server (NTRS)

Braun, Scott; Kummerow, Christian

2000-01-01

The Global Precipitation Mission (GPM), expected to begin around 2006, is a follow-up to the Tropical Rainfall Measuring Mission (TRMM). Unlike TRMM, which primarily samples the tropics, GPM will sample both the tropics and mid-latitudes. The primary, or core, satellite will be a single, enhanced TRMM satellite that can quantify the 3-D spatial distributions of precipitation and its associated latent heat release. The core satellite will be complemented by a constellation of very small and inexpensive drones with passive microwave instruments that will sample the rainfall with sufficient frequency to be not only of climate interest, but also have local, short-term impacts by providing global rainfall coverage at approx. 3 h intervals. The data is expected to have substantial impact upon quantitative precipitation estimation/forecasting and data assimilation into global and mesoscale numerical models. Based upon previous studies of rainfall data assimilation, GPM is expected to lead to significant improvements in forecasts of extratropical and tropical cyclones. For example, GPM rainfall data can provide improved initialization of frontal systems over the Pacific and Atlantic Oceans. The purpose of this talk is to provide information about GPM to the USWRP (U.S. Weather Research Program) community and to discuss impacts on quantitative precipitation estimation/forecasting and data assimilation.

The association between rainfall rate and occurrence of an enterovirus epidemic due to a contaminated well.

PubMed

Jean, J-S; Guo, H-R; Chen, S-H; Liu, C-C; Chang, W-T; Yang, Y-J; Huang, M-C

2006-12-01

To determine the association between rainfall rate and occurrence of enterovirus infection related to contamination of drinking water. One fatality case and three cases of severe illness were observed during the enterovirus epidemic in a village in southern Taiwan from 16 September to 3 October 1998. Groundwater samples were collected from the public well in the village after heavy rainfall to test for enterovirus using the reverse transcription-polymerase chain reaction (RT-PCR) assay. The RT-PCR assay detected the enterovirus in the groundwater sample collected on 26 September 1998. The logistic regression model also revealed a statistically significant association between the rainfall rate and the observation of cases of enterovirus infection. According to the fitted logistic regression model, the probability of detecting cases of enterovirus infection was greater than 50% at rainfall rates >31 mm h(-1). The higher the rainfall rate, the higher the probability of enterovirus epidemic. Contamination of drinking water by the enterovirus may lead to epidemics that cause deaths and severe illness, and such contamination may be caused by heavy rainfall. The major finding in this study is that the enterovirus could be flushed to groundwater in an unconfined aquifer after a heavy rainfall. This work allows for a warning level so that an action can be taken to minimize future outbreaks and so protect public health.

A cellular automata approach for modeling surface water runoff

NASA Astrophysics Data System (ADS)

Jozefik, Zoltan; Nanu Frechen, Tobias; Hinz, Christoph; Schmidt, Heiko

2015-04-01

This abstract reports the development and application of a two-dimensional cellular automata based model, which couples the dynamics of overland flow, infiltration processes and surface evolution through sediment transport. The natural hill slopes are represented by their topographic elevation and spatially varying soil properties infiltration rates and surface roughness coefficients. This model allows modeling of Hortonian overland flow and infiltration during complex rainfall events. An advantage of the cellular automata approach over the kinematic wave equations is that wet/dry interfaces that often appear with rainfall overland flows can be accurately captured and are not a source of numerical instabilities. An adaptive explicit time stepping scheme allows for rainfall events to be adequately resolved in time, while large time steps are taken during dry periods to provide for simulation run time efficiency. The time step is constrained by the CFL condition and mass conservation considerations. The spatial discretization is shown to be first-order accurate. For validation purposes, hydrographs for non-infiltrating and infiltrating plates are compared to the kinematic wave analytic solutions and data taken from literature [1,2]. Results show that our cellular automata model quantitatively accurately reproduces hydrograph patterns. However, recent works have showed that even through the hydrograph is satisfyingly reproduced, the flow field within the plot might be inaccurate [3]. For a more stringent validation, we compare steady state velocity, water flux, and water depth fields to rainfall simulation experiments conducted in Thies, Senegal [3]. Comparisons show that our model is able to accurately capture these flow properties. Currently, a sediment transport and deposition module is being implemented and tested. [1] M. Rousseau, O. Cerdan, O. Delestre, F. Dupros, F. James, S. Cordier. Overland flow modeling with the Shallow Water Equation using a well balanced numerical scheme: Adding efficiency or sum more complexity?. 2012. [2] Fritz R. Fiedler, J. A. Ramirez. A numerical method for simulating discontinuous shallow flow over an infiltrating surface. In. J. Numer. Mech. Fluids 200: 32: 219-240. [3] C. Mügler, O. Planchon, J. Patin, S. Weill, N. Silvera, P. Richard, E. Mouche. Comparison of Roughness models to simulate overland flow and tracer transport experiments under simulated rainfall at plot scale. Journal of Hydrology. 402 (2011) 25-40.

Regulations of irrigation on regional climate in the Heihe watershed, China, and its implications to water budget

NASA Astrophysics Data System (ADS)

Zhang, X.

2015-12-01

In the arid area, such as the Heihe watershed in Northwest China, agriculture is heavily dependent on the irrigation. Irrigation suggests human-induced hydro process, which modifies the local climate and water budget. In this study, we simulated the irrigation-induced changes in surface energy/moisture budgets and modifications on regional climate, using the WRF-NoahMP modle with an irrigation scheme. The irrigation scheme was implemented following the roles that soil moisture is assigned a saturated value once the mean soil moisture of all root layers is lower than 70% of fileld capacity. Across the growth season refering from May to September, the simulated mean irrigation amount of the 1181 cropland gridcells is ~900 mm, wihch is close to the field measurments of around 1000 mm. Such an irrigation largely modified the surface energy budget. Due to irrigation, the surface net solar radiation increased by ~76.7 MJ (~11 Wm-2) accouting for ~2.3%, surface latent and senbile heat flux increased by 97.7 Wm-2 and decreased by ~79.7 Wm-2 respectively; and local daily mean surface air temperature was thereby cooling by ~1.1°C. Corresponding to the surface energy changes, wind and circulation were also modified and regional water budget is therefore regulated. The total rainfall in the irrigation area increased due to more moisture from surface. However, the increased rainfall is only ~6.5mm (accounting for ~5% of background rainfall) which is much less than the increased evaporation of ~521.5mm from surface. The ~515mm of water accounting for 57% of total irrigation was transported outward by wind. The other ~385 mm accounting for 43% of total irrigation was transformed to be runoff and soil water. These results suggest that in the Heihe watershed irrigation largely modify local energy budget and cooling surface. This study also implicate that the existing irrigation may waste a large number of water. It is thereby valuable to develope effective irrigation scheme to save water resources.

Two Distinct Modes in One-Day Rainfall Event during MC3E Field Campaign: Analyses of Disdrometer Observations and WRF-SBM Simulation

NASA Technical Reports Server (NTRS)

Iguchi, Takamichi; Matsui, Toshihisa; Tokay, Ali; Kollias, Pavlos; Tao, Wei-Kuo

2012-01-01

A unique microphysical structure of rainfall is observed by the surface laser optical Particle Size and Velocity (Parsivel) disdrometers on 25 April 2011 during Midlatitude Continental Convective Clouds Experiment (MC3E). According to the systematic differences in rainfall rate and bulk effective droplet radius, the sampling data can be divided into two groups; the rainfall mostly from the deep convective clouds has relatively high rainfall rate and large bulk effective droplet radius, whereas the reverse is true for the rainfall from the shallow wrm clouds. The Weather Research and Forecasting model coupled with spectral bin microphysics (WRF-SBM) successfully reproduces the two distinct modes in the observed rainfall microphysical structure. The results show that the up-to-date model can demonstrate how the cloud physics and the weather condition on the day are involved in forming the unique rainfall characteristic.

Two distinct modes in one-day rainfall event during MC3E field campaign: Analyses of disdrometer observations and WRF-SBM simulation

NASA Astrophysics Data System (ADS)

Iguchi, Takamichi; Matsui, Toshihisa; Tokay, Ali; Kollias, Pavlos; Tao, Wei-Kuo

2012-12-01

A unique microphysical structure of rainfall is observed by the surface laser optical Particle Size and Velocity (Parsivel) disdrometers on 25 April 2011 during Midlatitude Continental Convective Clouds Experiment (MC3E). According to the systematic differences in rainfall rate and bulk effective droplet radius, the sampling data can be divided into two groups; the rainfall mostly from the deep convective clouds has relatively high rainfall rate and large bulk effective droplet radius, whereas the reverse is true for the rainfall from the shallow warm clouds. The Weather Research and Forecasting model coupled with spectral bin microphysics (WRF-SBM) successfully reproduces the two distinct modes in the observed rainfall microphysical structure. The results show that the up-to-date model can demonstrate how the cloud physics and the weather condition on the day are involved in forming the unique rainfall characteristic.

Attribution of Extreme Rainfall from Landfalling Tropical Cyclones to Climate Change for the Eastern United States

NASA Astrophysics Data System (ADS)

Liu, M.; Yang, L.; Smith, J. A.; Vecchi, G. A.

2017-12-01

Extreme rainfall and flooding associated with landfalling tropical cyclones (TC) is responsible for vast socioeconomic losses and fatalities. Landfalling tropical cyclones are an important element of extreme rainfall and flood peak distributions in the eastern United States. Record floods for USGS stream gauging stations over the eastern US are closely tied to landfalling hurricanes. A small number of storms account for the largest record floods, most notably Hurricanes Diane (1955) and Agnes (1972). The question we address is: if the synoptic conditions accompanying those hurricanes were to be repeated in the future, how would the thermodynamic and dynamic storm properties and associated extreme rainfall differ in response to climate change? We examine three hurricanes: Diane (1955), Agnes (1972) and Irene (2011), due to the contrasts in structure/evolution properties and their important roles in dictating the upper tail properties of extreme rainfall and flood frequency over eastern US. Extreme rainfall from Diane is more localized as the storm maintains tropical characteristics, while synoptic-scale vertical motion associated with extratropical transition is a central feature for extreme rainfall induced by Agnes. Our analyses are based on ensemble simulations using the Weather Research and Forecasting (WRF) model, considering combinations of different physics options (i.e., microphysics, boundary layer schemes). The initial and boundary conditions of WRF simulations for the present-day climate are using the Twentieth Century Reanalysis (20thCR). A sub-selection of GCMs is used, as part of phase 5 of the Coupled Model Intercomparison Project (CMIP5), to provide future climate projections. For future simulations, changes in model fields (i.e., temperature, humidity, geopotential height) between present-day and future climate are first derived and then added to the same 20thCR initial and boundary data used for the present-day simulations, and the ensemble is rerun using identical model configurations. Response of extreme rainfall as well as changes in thermodynamic and dynamic storm properties will be presented and analyzed. Contrasting responses across the three storm events to climate change will shed light on critical environmental factors for TC-related extreme rainfall over eastern US.

Evaluation of precipitation forecasts from 3D-Var and hybrid GSI-based system during Indian summer monsoon 2015

NASA Astrophysics Data System (ADS)

Singh, Sanjeev Kumar; Prasad, V. S.

2018-02-01

This paper presents a systematic investigation of medium-range rainfall forecasts from two versions of the National Centre for Medium Range Weather Forecasting (NCMRWF)-Global Forecast System based on three-dimensional variational (3D-Var) and hybrid analysis system namely, NGFS and HNGFS, respectively, during Indian summer monsoon (June-September) 2015. The NGFS uses gridpoint statistical interpolation (GSI) 3D-Var data assimilation system, whereas HNGFS uses hybrid 3D ensemble-variational scheme. The analysis includes the evaluation of rainfall fields and comparisons of rainfall using statistical score such as mean precipitation, bias, correlation coefficient, root mean square error and forecast improvement factor. In addition to these, categorical scores like Peirce skill score and bias score are also computed to describe particular aspects of forecasts performance. The comparison results of mean precipitation reveal that both the versions of model produced similar large-scale feature of Indian summer monsoon rainfall for day-1 through day-5 forecasts. The inclusion of fully flow-dependent background error covariance significantly improved the wet biases in HNGFS over the Indian Ocean. The forecast improvement factor and Peirce skill score in the HNGFS have also found better than NGFS for day-1 through day-5 forecasts.

Dynamic gauge adjustment of high-resolution X-band radar data for convective rain storms: Model-based evaluation against measured combined sewer overflow

NASA Astrophysics Data System (ADS)

Borup, Morten; Grum, Morten; Linde, Jens Jørgen; Mikkelsen, Peter Steen

2016-08-01

Numerous studies have shown that radar rainfall estimates need to be adjusted against rain gauge measurements in order to be useful for hydrological modelling. In the current study we investigate if adjustment can improve radar rainfall estimates to the point where they can be used for modelling overflows from urban drainage systems, and we furthermore investigate the importance of the aggregation period of the adjustment scheme. This is done by continuously adjusting X-band radar data based on the previous 5-30 min of rain data recorded by multiple rain gauges and propagating the rainfall estimates through a hydraulic urban drainage model. The model is built entirely from physical data, without any calibration, to avoid bias towards any specific type of rainfall estimate. The performance is assessed by comparing measured and modelled water levels at a weir downstream of a highly impermeable, well defined, 64 ha urban catchment, for nine overflow generating rain events. The dynamically adjusted radar data perform best when the aggregation period is as small as 10-20 min, in which case it performs much better than static adjusted radar data and data from rain gauges situated 2-3 km away.

Where do forests influence rainfall?

NASA Astrophysics Data System (ADS)

Wang-Erlandsson, Lan; van der Ent, Ruud; Fetzer, Ingo; Keys, Patrick; Savenije, Hubert; Gordon, Line

2017-04-01

Forests play a major role in hydrology. Not only by immediate control of soil moisture and streamflow, but also by regulating climate through evaporation (i.e., transpiration, interception, and soil evaporation). The process of evaporation travelling through the atmosphere and returning as precipitation on land is known as moisture recycling. Whether evaporation is recycled depends on wind direction and geography. Moisture recycling and forest change studies have primarily focused on either one region (e.g. the Amazon), or one biome type (e.g. tropical humid forests). We will advance this via a systematic global inter-comparison of forest change impacts on precipitation depending on both biome type and geographic location. The rainfall effects are studied for three contemporary forest changes: afforestation, deforestation, and replacement of mature forest by forest plantations. Furthermore, as there are indications in the literature that moisture recycling in some places intensifies during dry years, we will also compare the rainfall impacts of forest change between wet and dry years. We model forest change effects on evaporation using the global hydrological model STEAM and trace precipitation changes using the atmospheric moisture tracking scheme WAM-2layers. This research elucidates the role of geographical location of forest change driven modifications on rainfall as a function of the type of forest change and climatic conditions. These knowledge gains are important at a time of both rapid forest and climate change. Our conclusions nuance our understanding of how forests regulate climate and pinpoint hotspot regions for forest-rainfall coupling.

Short-term ensemble radar rainfall forecasts for hydrological applications

NASA Astrophysics Data System (ADS)

Codo de Oliveira, M.; Rico-Ramirez, M. A.

2016-12-01

Flooding is a very common natural disaster around the world, putting local population and economy at risk. Forecasting floods several hours ahead and issuing warnings are of main importance to permit proper response in emergency situations. However, it is important to know the uncertainties related to the rainfall forecasting in order to produce more reliable forecasts. Nowcasting models (short-term rainfall forecasts) are able to produce high spatial and temporal resolution predictions that are useful in hydrological applications. Nonetheless, they are subject to uncertainties mainly due to the nowcasting model used, errors in radar rainfall estimation, temporal development of the velocity field and to the fact that precipitation processes such as growth and decay are not taken into account. In this study an ensemble generation scheme using rain gauge data as a reference to estimate radars errors is used to produce forecasts with up to 3h lead-time. The ensembles try to assess in a realistic way the residual uncertainties that remain even after correction algorithms are applied in the radar data. The ensembles produced are compered to a stochastic ensemble generator. Furthermore, the rainfall forecast output was used as an input in a hydrodynamic sewer network model and also in hydrological model for catchments of different sizes in north England. A comparative analysis was carried of how was carried out to assess how the radar uncertainties propagate into these models. The first named author is grateful to CAPES - Ciencia sem Fronteiras for funding this PhD research.

Optimization of storage tank locations in an urban stormwater drainage system using a two-stage approach.

PubMed

Wang, Mingming; Sun, Yuanxiang; Sweetapple, Chris

2017-12-15

Storage is important for flood mitigation and non-point source pollution control. However, to seek a cost-effective design scheme for storage tanks is very complex. This paper presents a two-stage optimization framework to find an optimal scheme for storage tanks using storm water management model (SWMM). The objectives are to minimize flooding, total suspended solids (TSS) load and storage cost. The framework includes two modules: (i) the analytical module, which evaluates and ranks the flooding nodes with the analytic hierarchy process (AHP) using two indicators (flood depth and flood duration), and then obtains the preliminary scheme by calculating two efficiency indicators (flood reduction efficiency and TSS reduction efficiency); (ii) the iteration module, which obtains an optimal scheme using a generalized pattern search (GPS) method based on the preliminary scheme generated by the analytical module. The proposed approach was applied to a catchment in CZ city, China, to test its capability in choosing design alternatives. Different rainfall scenarios are considered to test its robustness. The results demonstrate that the optimal framework is feasible, and the optimization is fast based on the preliminary scheme. The optimized scheme is better than the preliminary scheme for reducing runoff and pollutant loads under a given storage cost. The multi-objective optimization framework presented in this paper may be useful in finding the best scheme of storage tanks or low impact development (LID) controls. Copyright © 2017 Elsevier Ltd. All rights reserved.

Evaluation of a spatial rainfall generator and an interpolation methods for the creation of future gridded data sets over complex terrains

NASA Astrophysics Data System (ADS)

Camera, Corrado; Bruggeman, Adriana; Hadjinicolaou, Panos; Michaelides, Silas; Lange, Manfred A.

2015-04-01

Space-time variability of precipitation plays a key role as a driver of many processes in different environmental fields like hydrology, ecology, biology, agriculture, and natural hazards. The objective of this study was to compare two approaches for statistical downscaling of precipitation from climate models. The study was applied to the island of Cyprus, an orographically complex terrain. The first approach makes use of a spatial temporal Neyman-Scott Rectangular Pulses (NSRP) model and a previously tested interpolation scheme (Camera et al., 2014). The second approach is based on the use of the single site NSRP model and a simplified gridded scheme based on scaling coefficients obtained from past observations. The rainfall generators were evaluated on the period 1980-2010. Both approaches were subsequently used to downscale three RCMs from the EU ENSEMBLE project to calculate climate projections (2020-2050). The main advantage of the spatial-temporal approach is that it allows creating spatially consistent daily maps of precipitation. On the other hand, due to the assumptions made using a stochastic generator based on homogeneous Poisson processes, it shows a smoothing out of all the rainfall statistics (except mean and variance) all over the study area. This leads to high errors when analyzing indices related to extremes. Examples are the number of days with rainfall over 50 mm (R50 - mean error 65%), the 95th percentile value of rainy days (RT95 - mean error 19%), and the mean annual rainfall recorded on days with rainfall above the 95th percentile (RA95 - mean error 22%). The single site approach excludes the possibility of using the created gridded data sets for case studies involving spatial connection between grid cells (e.g. hydrologic modelling), but it leads to a better reproduction of rainfall statistics and properties. The errors for the extreme indices are in fact much lower: 17% for R50, 4% for RT95, and 2% for RA95. Future projections show a decrease of the mean annual rainfall (for both approaches) over the study area between 70 mm (≈15%) and 5 mm (≈1%), in comparison to the reference period 1980-2010. Regarding extremes, calculated only with the single site approach, the projections show a decrease of the R50 index between 25% and 7%, and of the RT95 between 8% and 0%. Thus, these projections indicate that a slight reduction in the number and intensity of extremes can be expected. Further research will be done to adapt and evaluate the use of a spatial-temporal generator with nonhomogeneous spatial activation of raincells (Burton et al., 2010) to the study area. Burton, A., Fowler, H.J., Kilsby, C.G., O'Connell, P. E., 2010a. A stochastic model for the spatial-temporal simulation of non-homogeneous rainfall occurrence and amounts, Water Resour. Res. 46, W11501. DOI: 10.1029/2009WR008884 Camera, C., Bruggeman, A., Hadjinicolaou, P., Pashiardis, S., Lange, M. A., 2014. Evaluation of interpolation techniques for the creation of gridded daily precipitation (1 × 1 km2); Cyprus, 1980-2010. J. Geophys. Res. Atmos., 119, 693-712. DOI: 10.1002/2013JD020611.

A small single-nozzle rainfall simulator to measure erosion response on different burn severities in southern British Columbia, Canada

NASA Astrophysics Data System (ADS)

Covert, Ashley; Jordan, Peter

2010-05-01

To study the effects of wildfire burn severity on runoff generation and soil erosion from high intensity rainfall, we constructed an effective yet simple rainfall simulator that was inexpensive, portable and easily operated by two people on steep, forested slopes in southern British Columbia, Canada. The entire apparatus, including simulator, pumps, hoses, collapsible water bladders and sample bottles, was designed to fit into a single full-sized pick-up truck. The three-legged simulator extended to approximately 3.3 metres above ground on steep slopes and used a single Spraying Systems 1/2HH-30WSQ nozzle which can easily be interchanged for other sized nozzles. Rainfall characteristics were measured using a digital camera which took images of the raindrops against a grid. Median drop size and velocity 5 cm above ground were measured and found to be 3/4 of the size of natural rain drops of that diameter class, and fell 7% faster than terminal velocity. The simulator was used for experiments on runoff and erosion on sites burned in 2007 by two wildfires in southern British Columbia. Simulations were repeated one and two years after the fires. Rainfall was simulated at an average rate of 67 mm hr-1 over a 1 m2 plot for 20 minutes. This rainfall rate is similar to the 100 year return period rainfall intensity for this duration at a nearby weather station. Simulations were conducted on five replicate 1 m2 plots in each experimental unit including high burn severity, moderate burn severity, unburned, and unburned with forest floor removed. During the simulation a sample was collected for 30 seconds every minute, with two additional samples until runoff ceased, resulting in 22 samples per simulation. Runoff, overland flow coefficient, infiltration and sediment yield were compared between treatments. Additional simulations were conducted immediately after a 2009 wildfire to test different mulch treatments. Typical results showed that runoff on plots with high burn severity and with forest floor removed was similar, reaching on average a steady rate of about 60% of rainfall rate after about 7 minutes. Runoff on unburned plots with intact forest floor was much lower, typically less than 20% of rainfall rate. Sediment yield was greatest on plots with forest floor removed, followed by severely burned plots. Sediment yield on unburned and moderately burned plots was very low to zero. These results are consistent with qualitative observations made following several extreme rainfall events on recent burns in the region.

Improving Global Reanalyses and Short Range Forecast Using TRMM and SSM/I-Derived Precipitation and Moisture Observations

NASA Technical Reports Server (NTRS)

Hou, Arthur Y.; Zhang, Sara Q.; deSilva, Arlindo M.

2000-01-01

Global reanalyses currently contain significant errors in the primary fields of the hydrological cycle such as precipitation, evaporation, moisture, and the related cloud fields, especially in the tropics. The Data Assimilation Office (DAO) at the NASA Goddard Space Flight Center has been exploring the use of tropical rainfall and total precipitable water (TPW) observations from the TRMM Microwave Imager (TMI) and the Special Sensor Microwave/ Imager (SSM/I) instruments to improve short-range forecast and reanalyses. We describe a "1+1"D procedure for assimilating 6-hr averaged rainfall and TPW in the Goddard Earth Observing System (GEOS) Data Assimilation System (DAS). The algorithm is based on a 6-hr time integration of a column version of the GEOS DAS, hence the "1+1"D designation. The scheme minimizes the least-square differences between the observed TPW and rain rates and those produced by the column model over the 6-hr analysis window. This 1+lD scheme, in its generalization to four dimensions, is related to the standard 4D variational assimilation but uses analysis increments instead of the initial condition as the control variable. Results show that assimilating the TMI and SSM/I rainfall and TPW observations improves not only the precipitation and moisture fields but also key climate parameters such as clouds, the radiation, the upper-tropospheric moisture, and the large-scale circulation in the tropics. In particular, assimilating these data reduce the state-dependent systematic errors in the assimilated products. The improved analysis also provides better initial conditions for short-range forecasts, but the improvements in forecast are less than improvements in the time-averaged assimilation fields, indicating that using these data types is effective in correcting biases and other errors of the forecast model in data assimilation.

Improving Global Reanalyses and Short-Range Forecast Using TRMM and SSM/I-Derived Precipitation and Moisture Observations

NASA Technical Reports Server (NTRS)

Hou, Arthur Y.; Zhang, Sara Q.; daSilva, Arlindo M.

1999-01-01

Global reanalyses currently contain significant errors in the primary fields of the hydrological cycle such as precipitation, evaporation, moisture, and the related cloud fields, especially in the tropics. The Data Assimilation Office (DAO) at the NASA Goddard Space Flight Center has been exploring the use of tropical rainfall and total precipitable water (TPW) observations from the TRMM Microwave Imager (TMI) and the Special Sensor Microwave/ Imager (SSM/I) instruments to improve short-range forecast and reanalyses. We describe a 1+1D procedure for assimilating 6-hr averaged rainfall and TPW in the Goddard Earth Observing System (GEOS) Data Assimilation System (DAS). The algorithm is based on a 6-hr time integration of a column version of the GEOS DAS, hence the 1+1D designation. The scheme minimizes the least-square differences between the observed TPW and rain rates and those produced by the column model over the 6-hr analysis window. This 1+1D scheme, in its generalization to four dimensions, is related to the standard 4D variational assimilation but uses analysis increments instead of the initial condition as the control variable. Results show that assimilating the TMI and SSW rainfall and TPW observations improves not only the precipitation and moisture fields but also key climate parameters such as clouds, the radiation, the upper-tropospheric moisture, and the large-scale circulation in the tropics. In particular, assimilating these data reduce the state-dependent systematic errors in the assimilated products. The improved analysis also provides better initial conditions for short-range forecasts, but the improvements in forecast are less than improvements in the time-averaged assimilation fields, indicating that using these data types is effective in correcting biases and other errors of the forecast model in data assimilation.

Interannual Tropical Rainfall Variability in General Circulation Model Simulations Associated with the Atmospheric Model Intercomparison Project.

NASA Astrophysics Data System (ADS)

Sperber, K. R.; Palmer, T. N.

1996-11-01

The interannual variability of rainfall over the Indian subcontinent, the African Sahel, and the Nordeste region of Brazil have been evaluated in 32 models for the period 1979-88 as part of the Atmospheric Model Intercomparison Project (AMIP). The interannual variations of Nordeste rainfall are the most readily captured, owing to the intimate link with Pacific and Atlantic sea surface temperatures. The precipitation variations over India and the Sahel are less well simulated. Additionally, an Indian monsoon wind shear index was calculated for each model. Evaluation of the interannual variability of a wind shear index over the summer monsoon region indicates that the models exhibit greater fidelity in capturing the large-scale dynamic fluctuations than the regional-scale rainfall variations. A rainfall/SST teleconnection quality control was used to objectively stratify model performance. Skill scores improved for those models that qualitatively simulated the observed rainfall/El Niño- Southern Oscillation SST correlation pattern. This subset of models also had a rainfall climatology that was in better agreement with observations, indicating a link between systematic model error and the ability to simulate interannual variations.A suite of six European Centre for Medium-Range Weather Forecasts (ECMWF) AMIP runs (differing only in their initial conditions) have also been examined. As observed, all-India rainfall was enhanced in 1988 relative to 1987 in each of these realizations. All-India rainfall variability during other years showed little or no predictability, possibly due to internal chaotic dynamics associated with intraseasonal monsoon fluctuations and/or unpredictable land surface process interactions. The interannual variations of Nordeste rainfall were best represented. The State University of New York at Albany/National Center for Atmospheric Research Genesis model was run in five initial condition realizations. In this model, the Nordeste rainfall variability was also best reproduced. However, for all regions the skill was less than that of the ECMWF model.The relationships of the all-India and Sahel rainfall/SST teleconnections with horizontal resolution, convection scheme closure, and numerics have been evaluated. Models with resolution T42 performed more poorly than lower-resolution models. The higher resolution models were predominantly spectral. At low resolution, spectral versus gridpoint numerics performed with nearly equal verisimilitude. At low resolution, moisture convergence closure was slightly more preferable than other convective closure techniques. At high resolution, the models that used moisture convergence closure performed very poorly, suggesting that moisture convergence may be problematic for models with horizontal resolution T42.

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.

Characteristics of PAHs in farmland soil and rainfall runoff in Tianjin, China.

PubMed

Shi, Rongguang; Xu, Mengmeng; Liu, Aifeng; Tian, Yong; Zhao, Zongshan

2017-10-14

Rainfall runoff can remove certain amounts of pollutants from contaminated farmland soil and result in a decline in water quality. However, the leaching behaviors of polycyclic aromatic hydrocarbons (PAHs) with rainfall have been rarely reported due to wide variations in the soil compositions, rainfall conditions, and sources of soil PAHs in complex farmland ecosystems. In this paper, the levels, spatial distributions, and composition profiles of PAHs in 30 farmland soil samples and 49 rainfall-runoff samples from the Tianjin region in 2012 were studied to investigate their leaching behaviors caused by rainfall runoff. The contents of the Σ 16 PAHs ranged from 58.53 to 3137.90 μg/kg in the soil and 146.58 to 3636.59 μg/L in the runoff. In total, most of the soil sampling sites (23 of 30) were contaminated, and biomass and petroleum combustion were proposed as the main sources of the soil PAHs. Both the spatial distributions of the soil and the runoff PAHs show a decreasing trend moving away from the downtown, which suggested that the leaching behaviors of PAHs in a larger region during rainfall may be mainly affected by the compounds themselves. In addition, 4- and 5-ring PAHs are the dominant components in farmland soil and 3- and 4-ring PAHs dominate the runoff. Comparisons of the PAH pairs and enrichment ratios showed that acenaphthylene, acenaphthene, benzo[a]anthracene, chrysene, and fluoranthene were more easily transferred into water systems from soil than benzo[b]fluoranthene, benzo[k]fluoranthene, benzo[ghi]perylene, and indeno[123-cd]pyrene, which indicated that PAHs with low molecular weight are preferentially dissolved due to their higher solubility compared to those with high molecular weight.

Size distributions of manure particles released under simulated rainfall.

PubMed

Pachepsky, Yakov A; Guber, Andrey K; Shelton, Daniel R; McCarty, Gregory W

2009-03-01

Manure and animal waste deposited on cropland and grazing lands serve as a source of microorganisms, some of which may be pathogenic. These microorganisms are released along with particles of dissolved manure during rainfall events. Relatively little if anything is known about the amounts and sizes of manure particles released during rainfall, that subsequently may serve as carriers, abode, and nutritional source for microorganisms. The objective of this work was to obtain and present the first experimental data on sizes of bovine manure particles released to runoff during simulated rainfall and leached through soil during subsequent infiltration. Experiments were conducted using 200 cm long boxes containing turfgrass soil sod; the boxes were designed so that rates of manure dissolution and subsequent infiltration and runoff could be monitored independently. Dairy manure was applied on the upper portion of boxes. Simulated rainfall (ca. 32.4 mm h(-1)) was applied for 90 min on boxes with stands of either live or dead grass. Electrical conductivity, turbidity, and particle size distributions obtained from laser diffractometry were determined in manure runoff and soil leachate samples. Turbidity of leachates and manure runoff samples decreased exponentially. Turbidity of manure runoff samples was on average 20% less than turbidity of soil leachate samples. Turbidity of leachate samples from boxes with dead grass was on average 30% less than from boxes with live grass. Particle size distributions in manure runoff and leachate suspensions remained remarkably stable after 15 min of runoff initiation, although the turbidity continued to decrease. Particles had the median diameter of 3.8 microm, and 90% of particles were between 0.6 and 17.8 microm. The particle size distributions were not affected by the grass status. Because manure particles are known to affect transport and retention of microbial pathogens in soil, more information needs to be collected about the concurrent release of pathogens and manure particles during rainfall events.

SM2RAIN-CCI: a new global long-term rainfall data set derived from ESA CCI soil moisture

NASA Astrophysics Data System (ADS)

Ciabatta, Luca; Massari, Christian; Brocca, Luca; Gruber, Alexander; Reimer, Christoph; Hahn, Sebastian; Paulik, Christoph; Dorigo, Wouter; Kidd, Richard; Wagner, Wolfgang

2018-02-01

Accurate and long-term rainfall estimates are the main inputs for several applications, from crop modeling to climate analysis. In this study, we present a new rainfall data set (SM2RAIN-CCI) obtained from the inversion of the satellite soil moisture (SM) observations derived from the ESA Climate Change Initiative (CCI) via SM2RAIN (Brocca et al., 2014). Daily rainfall estimates are generated for an 18-year long period (1998-2015), with a spatial sampling of 0.25° on a global scale, and are based on the integration of the ACTIVE and the PASSIVE ESA CCI SM data sets.The quality of the SM2RAIN-CCI rainfall data set is evaluated by comparing it with two state-of-the-art rainfall satellite products, i.e. the Tropical Measurement Mission Multi-satellite Precipitation Analysis 3B42 real-time product (TMPA 3B42RT) and the Climate Prediction Center Morphing Technique (CMORPH), and one modeled data set (ERA-Interim). A quality check is carried out on a global scale at 1° of spatial sampling and 5 days of temporal sampling by comparing these products with the gauge-based Global Precipitation Climatology Centre Full Data Daily (GPCC-FDD) product. SM2RAIN-CCI shows relatively good results in terms of correlation coefficient (median value > 0.56), root mean square difference (RMSD, median value < 10.34 mm over 5 days) and bias (median value < -14.44 %) during the evaluation period. The validation has been carried out at original resolution (0.25°) over Europe, Australia and five other areas worldwide to test the capabilities of the data set to correctly identify rainfall events under different climate and precipitation regimes.The SM2RAIN-CCI rainfall data set is freely available at https://doi.org/10.5281/zenodo.846259.

Recent Rainfall and Aerosol Chemistry From Bermuda

NASA Astrophysics Data System (ADS)

Landing, W. M.; Shelley, R.; Kadko, D. C.

2014-12-01

This project was devoted to testing the use of Be-7 as a tracer for quantifying trace element fluxes from the atmosphere to the oceans. Rainfall and aerosol samples were collected between June 15, 2011 and July 27, 2013 at the Bermuda Institute of Ocean Sciences (BIOS) located near the eastern end of the island of Bermuda. Collectors were situated near ground level, clear of surrounding vegetation, at a meteorological monitoring station in front of the BIOS laboratory, about 10 m above sea level. This is a Bermuda Air Quality Program site used for ambient air quality monitoring. To quantify the atmospheric deposition of Be-7, plastic buckets were deployed for collection of fallout over ~3 week periods. Wet deposition was collected for trace element analysis using a specially modified "GEOTRACES" N-CON automated wet deposition collector. Aerosol samples were collected with a Tisch TE-5170V-BL high volume aerosol sampler, modified to collect 12 replicate samples on acid-washed 47mm diameter Whatman-41 filters, using procedures identical to those used for the US GEOTRACES aerosol program (Morton et al., 2013). Aerosol and rainfall samples were analyzed for total Na, Mg, Al, P, Sc, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, Rb, Sr, Zr, Cd, Sb, Ba, La, Ce, Nd, Pb, Th, and U using ICPMS. Confirming earlier data from Bermuda, strong seasonality in rainfall and aerosol loading and chemistry was observed, particularly for aerosol and rainfall Fe concentrations when Saharan dust arrives in July/August with SE trajectories.

The covariability of North American land-atmosphere coupling strength and rainfall characteristics in reanalyses

NASA Astrophysics Data System (ADS)

Ferguson, C. R.; Roundy, J. K.; Kim, W.

2016-12-01

The GEWEX North American Regional Hydroclimate Project (RHP): Water for the Food Baskets of the World initiative is aimed at: improving understanding of key processes—both natural and anthropogenic—that determine water availability, improving understanding of the independent and collective sensitivity of these processes to local and global change, and the integration of knowledge gained into the next model development cycle for the benefit of improved water availability forecasts. Considering that the agricultural sector accounts for three quarters of water withdrawals and suffers the brunt of drought-related financial damages, a rational RHP focal point is subseasonal-to-seasonal forecast skill. Forecasts on this timescale over the Great Plains food basket have shown particular sensitivity to land initial conditions (i.e., soil moisture, snow cover, and vegetative stress) and the realism of modeled land-atmosphere (L-A) coupling. L-A coupling strength denotes the degree to which the model's land scheme (i.e., soil column memory and surface flux partitioning) affect the atmospheric forecast scheme's daytime evolution of the convective boundary layer, including cloud development and precipitation. Prior studies have connected L-A coupling strength to the phase and amplitude of the diurnal precipitation cycle, as well as the evolution of heatwaves and drought. In this study, we apply three metrics of L-A coupling strength: soil moisture memory, the two-legged coupling metric, and the convective triggering potential-humidity index, to the 161-year NOAA-Cooperative Institute for Research in Environmental Sciences Twentieth Century Reanalysis (20CRV2c). Over the full period, we also analyze warm-season rainfall characteristics and subsequently perform statistical trend and change point analyses on both sets of results. We test the stationarity of both coupling and rainfall characteristics as well as the hypothesis that any detected shifts in coupling strength and afternoon rainfall frequency will coincide. Although the source data has inherent limitations that will be quantified and discussed, the results will be the first of their kind over such a long period of record and will provide key insights for the North American RHP.

Estimating the Risk of Domestic Water Source Contamination following Precipitation Events

PubMed Central

Eisenhauer, Ian F.; Hoover, Christopher M.; Remais, Justin V.; Monaghan, Andrew; Celada, Marco; Carlton, Elizabeth J.

2016-01-01

Climate change is expected to increase precipitation extremes, threatening water quality. In low resource settings, it is unclear which water sources are most vulnerable to contamination following rainfall events. We evaluated the relationship between rainfall and drinking water quality in southwest Guatemala where heavy rainfall is frequent and access to safe water is limited. We surveyed 59 shallow household wells, measured precipitation, and calculated simple hydrological variables. We compared Escherichia coli concentration at wells where recent rainfall had occurred versus had not occurred, and evaluated variability in the association between rainfall and E. coli concentration under different conditions using interaction models. Rainfall in the past 24 hours was associated with greater E. coli concentrations, with the strongest association between rainfall and fecal contamination at wells where pigs were nearby. Because of the small sample size, these findings should be considered preliminary, but provide a model to evaluate vulnerability to climate change. PMID:27114298

Bias adjustment of infrared-based rainfall estimation using Passive Microwave satellite rainfall data

NASA Astrophysics Data System (ADS)

Karbalaee, Negar; Hsu, Kuolin; Sorooshian, Soroosh; Braithwaite, Dan

2017-04-01

This study explores using Passive Microwave (PMW) rainfall estimation for spatial and temporal adjustment of Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Cloud Classification System (PERSIANN-CCS). The PERSIANN-CCS algorithm collects information from infrared images to estimate rainfall. PERSIANN-CCS is one of the algorithms used in the Integrated Multisatellite Retrievals for GPM (Global Precipitation Mission) estimation for the time period PMW rainfall estimations are limited or not available. Continued improvement of PERSIANN-CCS will support Integrated Multisatellite Retrievals for GPM for current as well as retrospective estimations of global precipitation. This study takes advantage of the high spatial and temporal resolution of GEO-based PERSIANN-CCS estimation and the more effective, but lower sample frequency, PMW estimation. The Probability Matching Method (PMM) was used to adjust the rainfall distribution of GEO-based PERSIANN-CCS toward that of PMW rainfall estimation. The results show that a significant improvement of global PERSIANN-CCS rainfall estimation is obtained.

Impact of an intense rainfall event on soil properties following a wildfire in a Mediterranean environment (North-East Spain).

PubMed

Francos, Marcos; Pereira, Paulo; Alcañiz, Meritxell; Mataix-Solera, Jorge; Úbeda, Xavier

2016-12-01

Intense rainfall events after severe wildfires can have an impact on soil properties, above all in the Mediterranean environment. This study seeks to examine the immediate impact and the effect after a year of an intense rainfall event on a Mediterranean forest affected by a high severity wildfire. The work analyses the following soil properties: soil aggregate stability, total nitrogen, total carbon, organic and inorganic carbon, the C/N ratio, carbonates, pH, electrical conductivity, extractable calcium, magnesium, sodium, potassium, available phosphorous and the sodium and potassium adsorption ratio (SPAR). We sampled soils in the burned area before, immediately after and one year after the rainfall event. The results showed that the intense rainfall event did not have an immediate impact on soil aggregate stability, but a significant difference was recorded one year after. The intense precipitation did not result in any significant changes in soil total nitrogen, total carbon, inorganic carbon, the C/N ratio and carbonates during the study period. Differences were only registered in soil organic carbon. The soil organic carbon content was significantly higher after the rainfall than in the other sampling dates. The rainfall event did increase soil pH, electrical conductivity, major cations, available phosphorous and the SPAR. One year after the fire, a significant decrease in soil aggregate stability was observed that can be attributed to high SPAR levels and human intervention, while the reduction in extractable elements can be attributed to soil leaching and vegetation consumption. Overall, the intense rainfall event, other post-fire rainfall events and human intervention did not have a detrimental impact on soil properties in all probability owing to the flat plot topography. Copyright © 2016 Elsevier B.V. All rights reserved.

The capacity of radar, crowdsourced personal weather stations and commercial microwave links to monitor small scale urban rainfall

NASA Astrophysics Data System (ADS)

Uijlenhoet, R.; de Vos, L. W.; Leijnse, H.; Overeem, A.; Raupach, T. H.; Berne, A.

2017-12-01

For the purpose of urban rainfall monitoring high resolution rainfall measurements are desirable. Typically C-band radar can provide rainfall intensities at km grid cells every 5 minutes. Opportunistic sensing with commercial microwave links yields rainfall intensities over link paths within cities. Additionally, recent developments have made it possible to obtain large amounts of urban in situ measurements from weather amateurs in near real-time. With a known high resolution simulated rainfall event the accuracy of these three techniques is evaluated, taking into account their respective existing layouts and sampling methods. Under ideal measurement conditions, the weather station networks proves to be most promising. For accurate estimation with radar, an appropriate choice for Z-R relationship is vital. Though both the microwave links and the weather station networks are quite dense, both techniques will underestimate rainfall if not at least one link path / station captures the high intensity rainfall peak. The accuracy of each technique improves when considering rainfall at larger scales, especially by increasing time intervals, with the steepest improvements found in microwave links.

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.

Hydrologic conditions and water quality of rainfall and storm runoff for two agricultural areas of the Oso Creek watershed, Nueces County, Texas, 2005-08

USGS Publications Warehouse

Ockerman, Darwin J.; Fernandez, Carlos J.

2010-01-01

The U.S. Geological Survey, in cooperation with the Texas State Soil and Water Conservation Board, Coastal Bend Bays and Estuaries Program, and Texas AgriLife Research and Extension Center at Corpus Christi, studied hydrologic conditions and water quality of rainfall and storm runoff of two primarily agricultural subwatersheds of the Oso Creek watershed in Nueces County, Texas. One area, the upper West Oso Creek subwatershed, is about 5,145 acres. The other area, a subwatershed drained by an unnamed tributary to Oso Creek (hereinafter, Oso Creek tributary), is about 5,287 acres. Rainfall and runoff (streamflow) were continuously monitored at the outlets of the two subwatersheds during the study period October 2005-September 2008. Seventeen rainfall samples were collected and analyzed for nutrients and major inorganic ions. Twenty-four composite runoff water-quality samples (12 at West Oso Creek, 12 at Oso Creek tributary) were collected and analyzed for nutrients, major inorganic ions, and pesticides. Twenty-six discrete suspended-sediment samples (12 West Oso Creek, 14 Oso Creek tributary) and 17 bacteria samples (10 West Oso Creek, 7 Oso Creek tributary) were collected and analyzed. These data were used to estimate, for selected constituents, rainfall deposition to and runoff loads and yields from the two subwatersheds. Quantities of fertilizers and pesticides applied in the two subwatersheds were compared with quantities of nutrients and pesticides in rainfall and runoff. For the study period, total rainfall was greater than average. Most of the runoff from the two subwatersheds occurred in response to a few specific storm periods. The West Oso Creek subwatershed produced more runoff during the study period than the Oso Creek tributary subwatershed, 13.95 inches compared with 9.45 inches. Runoff response was quicker and peak flows were higher in the West Oso Creek subwatershed than in the Oso Creek tributary subwatershed. Total nitrogen runoff yield for the 3-year study period averaged 2.62 pounds per acre per year from the West Oso Creek subwatershed and 0.839 pound per acre per year from the Oso Creek tributary subwatershed. Total phosphorus yields from the West Oso Creek and Oso Creek tributary subwatersheds for the 3-year period were 0.644 and 0.419 pound per acre per year, respectively. Runoff yields of nitrogen and phosphorus were relatively small compared to inputs of nitrogen in fertilizer and rainfall deposition. Average annual runoff yield of total nitrogen (subwatersheds combined) represents about 2.5 percent of nitrogen applied as fertilizer to cropland in the watershed and nitrogen entering the subwatersheds through rainfall deposition. Average annual runoff yield of total phosphorus (subwatersheds combined) represents about 4.0 percent of the phosphorus in applied fertilizer and rainfall deposition. Suspended-sediment yields from the West Oso Creek subwatershed were more than twice those from the Oso Creek tributary subwatershed. The average suspended-sediment yield from the West Oso Creek subwatershed was 522 pounds per acre per year and from the Oso Creek tributary subwatershed was 139 pounds per acre per year. Twenty-four herbicides and eight insecticides were detected in runoff samples collected at the two subwatershed outlets. At the West Oso Creek site, 19 herbicides and 4 insecticides were detected; at the Oso Creek tributary site, 18 herbicides and 6 insecticides were detected. Fourteen pesticides were detected in only one sample at low concentrations (near the laboratory reporting level). Atrazine and atrazine degradation byproduct 2-chloro-4-isopropylamino-6-amino-s-triazine (CIAT) were detected in all samples. Glyphosate and glyphosate byproduct aminomethylphosphonic acid (AMPA) were detected in all samples collected and analyzed during water years 2006-07 but were not included in analysis for samples collected in water year 2008. Of all pesticides detected in runoff, the highest runoff yields w

Determination of precipitation profiles from airborne passive microwave radiometric measurements

NASA Technical Reports Server (NTRS)

Kummerow, Christian; Hakkarinen, Ida M.; Pierce, Harold F.; Weinman, James A.

1991-01-01

This study presents the first quantitative retrievals of vertical profiles of precipitation derived from multispectral passive microwave radiometry. Measurements of microwave brightness temperature (Tb) obtained by a NASA high-altitude research aircraft are related to profiles of rainfall rate through a multichannel piecewise-linear statistical regression procedure. Statistics for Tb are obtained from a set of cloud radiative models representing a wide variety of convective, stratiform, and anvil structures. The retrieval scheme itself determines which cloud model best fits the observed meteorological conditions. Retrieved rainfall rate profiles are converted to equivalent radar reflectivity for comparison with observed reflectivities from a ground-based research radar. Results for two case studies, a stratiform rain situation and an intense convective thunderstorm, show that the radiometrically derived profiles capture the major features of the observed vertical structure of hydrometer density.

Rainfall, Streamflow, and Water-Quality Data During Stormwater Monitoring, Halawa Stream Drainage Basin, Oahu, Hawaii, July 1, 2000 to June 30, 2001

USGS Publications Warehouse

Presley, Todd K.

2001-01-01

The State of Hawaii Department of Transportation Stormwater Monitoring Program was implemented on January 1, 2001. The program includes the collection of rainfall, streamflow, and water-quality data at selected sites in the Halawa Stream drainage basin. Rainfall and streamflow data were collected from July 1, 2000 to June 30, 2001. Few storms during the year met criteria for antecedent dry conditions or provided enough runoff to sample. The storm of June 5, 2001 was sufficiently large to cause runoff. On June 5, 2001, grab samples were collected at five sites along North Halawa and Halawa Streams. The five samples were later analyzed for nutrients, trace metals, oil and grease, total petroleum hydrocarbons, fecal coliform, biological and chemical oxygen demands, total suspended solids, and total dissolved solids.

Skill of Predicting Heavy Rainfall Over India: Improvement in Recent Years Using UKMO Global Model

NASA Astrophysics Data System (ADS)

Sharma, Kuldeep; Ashrit, Raghavendra; Bhatla, R.; Mitra, A. K.; Iyengar, G. R.; Rajagopal, E. N.

2017-11-01

The quantitative precipitation forecast (QPF) performance for heavy rains is still a challenge, even for the most advanced state-of-art high-resolution Numerical Weather Prediction (NWP) modeling systems. This study aims to evaluate the performance of UK Met Office Unified Model (UKMO) over India for prediction of high rainfall amounts (>2 and >5 cm/day) during the monsoon period (JJAS) from 2007 to 2015 in short range forecast up to Day 3. Among the various modeling upgrades and improvements in the parameterizations during this period, the model horizontal resolution has seen an improvement from 40 km in 2007 to 17 km in 2015. Skill of short range rainfall forecast has improved in UKMO model in recent years mainly due to increased horizontal and vertical resolution along with improved physics schemes. Categorical verification carried out using the four verification metrics, namely, probability of detection (POD), false alarm ratio (FAR), frequency bias (Bias) and Critical Success Index, indicates that QPF has improved by >29 and >24% in case of POD and FAR. Additionally, verification scores like EDS (Extreme Dependency Score), EDI (Extremal Dependence Index) and SEDI (Symmetric EDI) are used with special emphasis on verification of extreme and rare rainfall events. These scores also show an improvement by 60% (EDS) and >34% (EDI and SEDI) during the period of study, suggesting an improved skill of predicting heavy rains.

Incident rainfall in Rome and its relation to biodeterioration of buildings

NASA Astrophysics Data System (ADS)

Caneva, G.; Gori, E.; Danin, A.

Intensity and distribution of incident rainfall in Rome, and degree of lithobiont cover of building walls, were estimated, and their correlation was discussed. Rainfall and wind data over 10 years for the Rome Meteorological Observatory of Torre Calandrelli (UCEA) were used to calculate the actual hydrocontribution received over walls at various exposures. The biological colonization by lithobionts was evaluated on a sample of 14 buildings in various places of the city, using a phytosociological scale for quantifying their total cover. During all seasons the rainfall shows a significant peak in the south and the southeast exposures, where the highest cover of lithobionts is found. These results show the role of incident rainfall in the climatic conditions of Rome as the main driving factor for the growth of lithobionts on walls where rainfall is their principal source of water.

Using Conditional Analysis to Investigate Spatial and Temporal patterns in Upland Rainfall

NASA Astrophysics Data System (ADS)

Sakamoto Ferranti, Emma Jayne; Whyatt, James Duncan; Timmis, Roger James

2010-05-01

The seasonality and characteristics of rainfall in the UK are altering under a changing climate. Summer rainfall is generally decreasing whereas winter rainfall is increasing, particularly in northern and western areas (Maraun et al., 2008) and recent research suggests these rainfall increases are amplified in upland areas (Burt and Ferranti, 2010). Conditional analysis has been used to investigate these rainfall patterns in Cumbria, an upland area in northwest England. Cumbria was selected as an example of a topographically diverse mid-latitude region that has a predominately maritime and westerly-defined climate. Moreover it has a dense network of more than 400 rain gauges that have operated for periods between 1900 and present day. Cumbria has experienced unprecedented flooding in the past decade and understanding the spatial and temporal changes in this and other upland regions is important for water resource and ecosystem management. The conditional analysis method examines the spatial and temporal variations in rainfall under different synoptic conditions and in different geographic sub-regions (Ferranti et al., 2009). A daily synoptic typing scheme, the Lamb Weather Catalogue, was applied to classify rainfall into different weather types, for example: south-westerly, westerly, easterly or cyclonic. Topographic descriptors developed using GIS were used to classify rain gauges into 6 directionally-dependant geographic sub-regions: coastal, windward-lowland, windward-upland, leeward-upland, leeward-lowland, secondary upland. Combining these classification methods enabled seasonal rainfall climatologies to be produced for specific weather types and sub-regions. Winter rainfall climatologies were constructed for all 6 sub-regions for 3 weather types - south-westerly (SW), westerly (W), and cyclonic (C); these weather types contribute more than 50% of total winter rainfall. The frequency of wet-days (>0.3mm), the total winter rainfall and the average wet day rainfall amount were analysed for each rainfall sub-region and weather type from 1961-2007 (Ferranti et al., 2010). The conditional analysis showed total rainfall under SW and W weather types to be increasing, with the greatest increases observed in the upland sub-regions. The increase in total SW rainfall is driven by a greater occurrence of SW rain days, and there has been little change to the average wet-day rainfall amount. The increase in total W rainfall is driven in part by an increase in the frequency of wet-days, but more significantly by an increase in the average wet-day rainfall amount. In contrast, total rainfall under C weather types has decreased. Further analysis will investigate how spring, summer and autumn rainfall climatologies have changed for the different weather types and sub-regions. Conditional analysis that combines GIS and synoptic climatology provides greater insights into the processes underlying readily available meteorological data. Dissecting Cumbrian rainfall data under different synoptic and geographic conditions showed the observed changes in winter rainfall are not uniform for the different weather types, nor for the different geographic sub-regions. These intricate details are often lost during coarser resolution analysis, and conditional analysis will provide a detailed synopsis of Cumbrian rainfall processes against which Regional Climate Model (RCM) performance can be tested. Conventionally RCMs try to simulate composite rainfall over many different weather types and sub-regions and by undertaking conditional validation the model performance for individual processes can be tested. This will help to target improvements in model performance, and ultimately lead to better simulation of rainfall in areas of complex topography. BURT, T. P. & FERRANTI, E. J. S. (2010) Changing patterns of heavy rainfall in upland areas: a case study from northern England. Atmospheric Environment, [in review]. FERRANTI, E. J. S., WHYATT, J. D. & TIMMIS, R. J. (2009) Development and application of topographic descriptors for conditional analysis of rainfall. Atmospheric Science Letters, 10, 177-184. FERRANTI, E. J. S., WHYATT, J. D., TIMMIS, R. J. & DAVIES, G. (2010) Using GIS to investigate spatial and temporal variations in upland rainfall. Transactions in GIS, [in press]. MARAUN, D., OSBORN, T. J. & GILLETT, N. P. (2008) United Kingdom daily precipitation intensity: improved early data, error estimates and an update from 2000 to 2006. International Journal of Climatology, 28, 833-842.

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.

Prolonged dry periods between rainfall events shorten the growth period of the resurrection plant Reaumuria soongorica.

PubMed

Zhang, Zhengzhong; Shan, Lishan; Li, Yi

2018-01-01

The resurrection plant Reaumuria soongorica is widespread across Asia, southern Europe, and North Africa and is considered to be a constructive keystone species in desert ecosystems, but the impacts of climate change on this species in desert ecosystems are unclear. Here, the morphological responses of R. soongorica to changes in rainfall quantity (30% reduction and 30% increase in rainfall quantity) and interval (50% longer drought interval between rainfall events) were tested. Stage-specific changes in growth were monitored by sampling at the beginning, middle, and end of the growing season. Reduced rainfall decreased the aboveground and total biomass, while additional precipitation generally advanced R. soongorica growth and biomass accumulation. An increased interval between rainfall events resulted in an increase in root biomass in the middle of the growing season, followed by a decrease toward the end. The response to the combination of increased rainfall quantity and interval was similar to the response to increased interval alone, suggesting that the effects of changes in rainfall patterns exert a greater influence than increased rainfall quantity. Thus, despite the short duration of this experiment, consequences of changes in rainfall regime on seedling growth were observed. In particular, a prolonged rainfall interval shortened the growth period, suggesting that climate change-induced rainfall variability may have significant effects on the structure and functioning of desert ecosystems.

Use of Satellite Remote Sensing of Cloud and Rainfall for Selected Operational Applications in the Fields of Applied Hydrology and Food Production.

NASA Astrophysics Data System (ADS)

Power, Clare

Available from UMI in association with The British Library. The material presented in this thesis takes the form of a series of discrete, but inter-related projects on subjects related to the use of satellite remote sensing techniques for selected applications in the fields of cloud, rainfall, vegetation and food production monitoring and assessment. Detailed literature reviews have been carried out on remote sensing techniques in these fields, in particular, for rainfall monitoring and the development of systems for food crop prediction from various rainfall, vegetation and crop monitoring algorithms. The second part of the thesis is devoted to a series of practical projects using five different and contrasting satellite rainfall monitoring techniques using visible and/or infrared imagery, three applied over the Sultanate of Oman and two over West Africa. The case studies applied over the Sultanate of Oman show a range of techniques from manual nephanalyses of Potential Rain Clouds and the derivation of a 20 year record of Tropical Cyclone tracks over the Arabian Sea, to the manual Bristol rainfall monitoring technique and its human-machine interactive successor BIAS, which are applicable to the analysis of short term extreme rainfall events. The remaining two techniques were developed simultaneously over West Africa. The first, namely, PERMIT (the Polar-orbiter Effective Rainfall Monitoring Technique), was developed by the Author, and the second, ADMIT (Agricultural Drought Monitoring Integrated Technique), by a colleague, Giles D'Souza. The development, testing on data from July and August 1985 and July 1986, and subsequent modification of the PERMIT technique is described. The 1986 Case Study results have been compared with the ADMIT results from the same data set, as part of a project funded by FAO to compare the performance of four Meteosat rainfall monitoring techniques (Snijders 1988). PERMIT was designed to be an economic, (in terms of satellite data and computer processing needs), automatic rainfall estimation technique suitable for use in environments where computer facilities are limited. Finally the PERMIT rainfall products have been compared with contemporaneous NOAA AVHRR Normalised Vegetation Index monthly composites. The relationships observed between these two satellite-derived products may contribute to the future development of a simple, low cost crop prediction scheme for developing countries. The main conclusion drawn from this research is that there is an urgent need for simple but effective rainfall and vegetation monitoring systems such as PERMIT, to be implemented operationally on low cost portable microcomputer systems which are readily installed in Developing Countries, where effective monitoring of such environmental elements can provide early warnings and reduce the impacts of drought inflicted famine disasters.

A real-time automated quality control of rain gauge data based on multiple sensors

NASA Astrophysics Data System (ADS)

qi, Y.; Zhang, J.

2013-12-01

Precipitation is one of the most important meteorological and hydrological variables. Automated rain gauge networks provide direct measurements of precipitation and have been used for numerous applications such as generating regional and national precipitation maps, calibrating remote sensing data, and validating hydrological and meteorological model predictions. Automated gauge observations are prone to a variety of error sources (instrument malfunction, transmission errors, format changes), and require careful quality controls (QC). Many previous gauge QC techniques were based on neighborhood checks within the gauge network itself and the effectiveness is dependent on gauge densities and precipitation regimes. The current study takes advantage of the multi-sensor data sources in the National Mosaic and Multi-Sensor QPE (NMQ/Q2) system and developes an automated gauge QC scheme based the consistency of radar hourly QPEs and gauge observations. Error characteristics of radar and gauge as a function of the radar sampling geometry, precipitation regimes, and the freezing level height are considered. The new scheme was evaluated by comparing an NMQ national gauge-based precipitation product with independent manual gauge observations. Twelve heavy rainfall events from different seasons and areas of the United States are selected for the evaluation, and the results show that the new NMQ product with QC'ed gauges has a more physically spatial distribution than the old product. And the new product agrees much better statistically with the independent gauges.

The Impact of Microphysics on Intensity and Structure of Hurricanes

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Shi, Jainn; Lang, Steve; Peters-Lidard, Christa

2006-01-01

During the past decade, both research and operational numerical weather prediction models, e.g. Weather Research and Forecast (WRF) model, have started using more complex microphysical schemes originally developed for high-resolution cloud resolving models (CRMs) with a 1-2 km or less horizontal resolutions. WFW is a next-generation mesoscale forecast model and assimilation system that has incorporated modern software framework, advanced dynamics, numeric and data assimilation techniques, a multiple moveable nesting capability, and improved physical packages. WFW model can be used for a wide range of applications, from idealized research to operational forecasting, with an emphasis on horizontal grid sizes in the range of 1-10 km. The current WRF includes several different microphysics options such as Lin et al. (1983), WSM 6-class and Thompson microphysics schemes. We have recently implemented three sophisticated cloud microphysics schemes into WRF. The cloud microphysics schemes have been extensively tested and applied for different mesoscale systems in different geographical locations. The performances of these schemes have been compared to those from other WRF microphysics options. We are performing sensitivity tests in using WW to examine the impact of six different cloud microphysical schemes on hurricane track, intensity and rainfall forecast. We are also performing the inline tracer calculation to comprehend the physical processes @e., boundary layer and each quadrant in the boundary layer) related to the development and structure of hurricanes.

Concentrations of Glyphosate, Its Degradation Product, Aminomethylphosphonic Acid, and Glufosinate in Ground- and Surface-Water, Rainfall, and Soil Samples Collected in the United States, 2001-06

USGS Publications Warehouse

Scribner, Elisabeth A.; Battaglin, William A.; Gilliom, Robert J.; Meyer, Michael T.

2007-01-01

The U.S. Geological Survey conducted a number of studies from 2001 through 2006 to investigate and document the occurrence, fate, and transport of glyphosate, its degradation product, aminomethylphosphonic acid (AMPA), and glufosinate in 2,135 ground- and surface-water samples, 14 rainfall samples, and 193 soil samples. Analytical methods were developed to detect and measure glyphosate, AMPA, and glufosinate in water, rainfall, and soil. Results show that AMPA was detected more frequently and occurred at similar or higher concentrations than the parent compound, glyphosate, whereas glufosinate was seldom found in the environment. Glyphosate and AMPA were detected more frequently in surface water than in ground water. Trace levels of glyphosate and AMPA may persist in the soil from year to year. The methods and data described in this report are useful to researchers and regulators interested in the occurrence, fate, and transport of glyphosate and AMPA in the environment.

Spatial Interpolation of Rain-field Dynamic Time-Space Evolution in Hong Kong

NASA Astrophysics Data System (ADS)

Liu, P.; Tung, Y. K.

2017-12-01

Accurate and reliable measurement and prediction of spatial and temporal distribution of rain-field over a wide range of scales are important topics in hydrologic investigations. In this study, geostatistical treatment of precipitation field is adopted. To estimate the rainfall intensity over a study domain with the sample values and the spatial structure from the radar data, the cumulative distribution functions (CDFs) at all unsampled locations were estimated. Indicator Kriging (IK) was used to estimate the exceedance probabilities for different pre-selected cutoff levels and a procedure was implemented for interpolating CDF values between the thresholds that were derived from the IK. Different interpolation schemes of the CDF were proposed and their influences on the performance were also investigated. The performance measures and visual comparison between the observed rain-field and the IK-based estimation suggested that the proposed method can provide fine results of estimation of indicator variables and is capable of producing realistic image.

Role of a cumulus parameterization scheme in simulating atmospheric circulation and rainfall in the nine-layer Goddard Laboratory for Atmospheres General Circulation Model

NASA Technical Reports Server (NTRS)

Sud, Y. C.; Chao, Winston C.; Walker, G. K.

1992-01-01

The influence of a cumulus convection scheme on the simulated atmospheric circulation and hydrologic cycle is investigated by means of a coarse version of the GCM. Two sets of integrations, each containing an ensemble of three summer simulations, were produced. The ensemble sets of control and experiment simulations are compared and differentially analyzed to determine the influence of a cumulus convection scheme on the simulated circulation and hydrologic cycle. The results show that cumulus parameterization has a very significant influence on the simulation circulation and precipitation. The upper-level condensation heating over the ITCZ is much smaller for the experiment simulations as compared to the control simulations; correspondingly, the Hadley and Walker cells for the control simulations are also weaker and are accompanied by a weaker Ferrel cell in the Southern Hemisphere. Overall, the difference fields show that experiment simulations (without cumulus convection) produce a cooler and less energetic atmosphere.

The implementation of reverse Kessler warm rain scheme for radar reflectivity assimilation using a nudging approach in New Zealand

NASA Astrophysics Data System (ADS)

Zhang, Sijin; Austin, Geoff; Sutherland-Stacey, Luke

2014-05-01

Reverse Kessler warm rain processes were implemented within the Weather Research and Forecasting Model (WRF) and coupled with a Newtonian relaxation, or nudging technique designed to improve quantitative precipitation forecasting (QPF) in New Zealand by making use of observed radar reflectivity and modest computing facilities. One of the reasons for developing such a scheme, rather than using 4D-Var for example, is that radar VAR scheme in general, and 4D-Var in particular, requires computational resources beyond the capability of most university groups and indeed some national forecasting centres of small countries like New Zealand. The new scheme adjusts the model water vapor mixing ratio profiles based on observed reflectivity at each time step within an assimilation time window. The whole scheme can be divided into following steps: (i) The radar reflectivity is firstly converted to rain water, and (ii) then the rain water is used to derive cloud water content according to the reverse Kessler scheme; (iii) The cloud water content associated water vapor mixing ratio is then calculated based on the saturation adjustment processes; (iv) Finally the adjusted water vapor is nudged into the model and the model background is updated. 13 rainfall cases which occurred in the summer of 2011/2012 in New Zealand were used to evaluate the new scheme, different forecast scores were calculated and showed that the new scheme was able to improve precipitation forecasts on average up to around 7 hours ahead depending on different verification thresholds.

High-Resolution NU-WRF Simulations of a Deep Convective-Precipitation System During MC3E. Part 1; Comparisons Between Goddard Microphysics Schemes and Observations

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Wu, Di; Lang, Stephen; Chern, Jiundar; Peters-Lidard, Christa; Fridlind, Ann; Matsui, Toshihisa

2015-01-01

The Goddard microphysics scheme was recently improved by adding a 4th ice class (frozen dropshail). This new 4ICE scheme was implemented and tested in the Goddard Cumulus Ensemble model (GCE) for an intense continental squall line and a moderate,less-organized continental case. Simulated peak radar reflectivity profiles were improved both in intensity and shape for both cases as were the overall reflectivity probability distributions versus observations. In this study, the new Goddard 4ICE scheme is implemented into the regional-scale NASA Unified - Weather Research and Forecasting model (NU-WRF) and tested on an intense mesoscale convective system that occurred during the Midlatitude Continental Convective Clouds Experiment (MC3E). The NU42WRF simulated radar reflectivities, rainfall intensities, and vertical and horizontal structure using the new 4ICE scheme agree as well as or significantly better with observations than when using previous versions of the Goddard 3ICE (graupel or hail) schemes. In the 4ICE scheme, the bin microphysics-based rain evaporation correction produces more erect convective cores, while modification of the unrealistic collection of ice by dry hail produces narrow and intense cores, allowing more slow-falling snow to be transported rearward. Together with a revised snow size mapping, the 4ICE scheme produces a more horizontally stratified trailing stratiform region with a broad, more coherent light rain area. In addition, the NU-WRF 4ICE simulated radar reflectivity distributions are consistent with and generally superior to those using the GCE due to the less restrictive open lateral boundaries

Grid-cell-based crop water accounting for the famine early warning system

USGS Publications Warehouse

Verdin, J.; Klaver, R.

2002-01-01

Rainfall monitoring is a regular activity of food security analysts for sub-Saharan Africa due to the potentially disastrous impact of drought. Crop water accounting schemes are used to track rainfall timing and amounts relative to phenological requirements, to infer water limitation impacts on yield. Unfortunately, many rain gauge reports are available only after significant delays, and the gauge locations leave large gaps in coverage. As an alternative, a grid-cell-based formulation for the water requirement satisfaction index (WRSI) was tested for maize in Southern Africa. Grids of input variables were obtained from remote sensing estimates of rainfall, meteorological models, and digital soil maps. The spatial WRSI was computed for the 1996–97 and 1997–98 growing seasons. Maize yields were estimated by regression and compared with a limited number of reports from the field for the 1996–97 season in Zimbabwe. Agreement at a useful level (r = 0·80) was observed. This is comparable to results from traditional analysis with station data. The findings demonstrate the complementary role that remote sensing, modelling, and geospatial analysis can play in an era when field data collection in sub-Saharan Africa is suffering an unfortunate decline.

Impacts of changing rainfall regime on the demography of tropical birds

NASA Astrophysics Data System (ADS)

Brawn, Jeffrey D.; Benson, Thomas J.; Stager, Maria; Sly, Nicholas D.; Tarwater, Corey E.

2017-02-01

Biodiversity in tropical regions is particularly high and may be highly sensitive to climate change. Unfortunately, a lack of long-term data hampers understanding of how tropical species, especially animals, may react to projected environmental changes. The amount and timing of rainfall is key to the function of tropical ecosystems and, although specific model predictions differ, there is general agreement that rainfall regimes will change over large areas of the tropics. Here, we estimate associations between dry season length (DSL) and the population biology of 20 bird species sampled in central Panama over a 33-year period. Longer dry seasons decreased the population growth rates and viability of nearly one-third of the species sampled. Simulations with modest increases in DSL suggest that consistently longer dry seasons will change the structure of tropical bird communities. Such change may occur even without direct loss of habitat--a finding with fundamental implications for conservation planning. Systematic changes in rainfall regime may threaten some populations and communities of tropical animals even in large tracts of protected habitat. These findings suggest the need for collaboration between climate scientists and conservation biologists to identify areas where rainfall regimes will be able to plausibly maintain wildlife populations.

Characterizing the interaction of groundwater and surface water in the karst aquifer of Fangshan, Beijing (China)

NASA Astrophysics Data System (ADS)

Chu, Haibo; Wei, Jiahua; Wang, Rong; Xin, Baodong

2017-03-01

Correct understanding of groundwater/surface-water (GW-SW) interaction in karst systems is of greatest importance for managing the water resources. A typical karst region, Fangshan in northern China, was selected as a case study. Groundwater levels and hydrochemistry analyses, together with isotope data based on hydrogeological field investigations, were used to assess the GW-SW interaction. Chemistry data reveal that water type and the concentration of cations in the groundwater are consistent with those of the surface water. Stable isotope ratios of all samples are close to the local meteoric water line, and the 3H concentrations of surface water and groundwater samples are close to that of rainfall, so isotopes also confirm that karst groundwater is recharged by rainfall. Cross-correlation analysis reveals that rainfall leads to a rise in groundwater level with a lag time of 2 months and groundwater exploitation leads to a fall within 1 month. Spectral analysis also reveals that groundwater level, groundwater exploitation and rainfall have significantly similar response periods, indicating their possible inter-relationship. Furthermore, a multiple nonlinear regression model indicates that groundwater level can be negatively correlated with groundwater exploitation, and positively correlated with rainfall. The overall results revealed that groundwater level has a close correlation with groundwater exploitation and rainfall, and they are indicative of a close hydraulic connection and interaction between surface water and groundwater in this karst system.

New, Improved Bulk-microphysical Schemes for Studying Precipitation Processes in WRF. Part 1; Comparisons with Other Schemes

NASA Technical Reports Server (NTRS)

Tao, W.-K.; Shi, J.; Chen, S. S> ; Lang, S.; Hong, S.-Y.; Thompson, G.; Peters-Lidard, C.; Hou, A.; Braun, S.;

Water management challenges at Mushandike irrigation scheme in Runde catchment, Zimbabwe

NASA Astrophysics Data System (ADS)

Malanco, Jose A.; Makurira, Hodson; Kaseke, Evans; Gumindoga, Webster

2018-05-01

Mushandike Irrigation Scheme, constructed in 1939, is located in Masvingo District and is one of the oldest irrigation schemes in Zimbabwe. Since 2002, the scheme has experienced severe water shortages resulting in poor crop yields. The low crop yields have led to loss of income to the smallholder farmers who constitute the irrigation scheme leading to water conflicts. The water stress at the scheme has been largely attributed to climate change and the uncontrolled expansion of the land under irrigation which is currently about 1000 ha against a design area of 613 ha. This study sought to determine the actual causes of water shortage at Mushandike Irrigation Scheme. Hydro-climatic data was analysed to establish if the Mushandike River system generates enough water to guarantee the calculated annual yield of the dam. Irrigation demands and efficiencies were compared against water availability and dam releases to establish if there is any deficit. The Spearman's Rank Correlation results of 0.196 for rainfall and 0.48 for evaporation confirmed positive but insignificant long-term changes in hydro-climatic conditions in the catchment. Water budgets established that the yield of the dam of 9.2 × 106 m3 year-1 is sufficient to support the expanded area of 1000 ha provided in-field water management efficiencies are adopted. The study concludes that water shortages currently experienced at the scheme are a result of inefficient water management (e.g. over-abstraction from the dam beyond the firm yield, adoption of inefficient irrigation methods and high channel losses in the canal system) and are not related to hydro-climatic conditions. The study also sees no value in considering inter-basin water transfer to cushion the losses being experienced at the scheme.

Simulation of the West African Monsoon using the MIT Regional Climate Model

NASA Astrophysics Data System (ADS)

Im, Eun-Soon; Gianotti, Rebecca L.; Eltahir, Elfatih A. B.

2013-04-01

We test the performance of the MIT Regional Climate Model (MRCM) in simulating the West African Monsoon. MRCM introduces several improvements over Regional Climate Model version 3 (RegCM3) including coupling of Integrated Biosphere Simulator (IBIS) land surface scheme, a new albedo assignment method, a new convective cloud and rainfall auto-conversion scheme, and a modified boundary layer height and cloud scheme. Using MRCM, we carried out a series of experiments implementing two different land surface schemes (IBIS and BATS) and three convection schemes (Grell with the Fritsch-Chappell closure, standard Emanuel, and modified Emanuel that includes the new convective cloud scheme). Our analysis primarily focused on comparing the precipitation characteristics, surface energy balance and large scale circulations against various observations. We document a significant sensitivity of the West African monsoon simulation to the choices of the land surface and convection schemes. In spite of several deficiencies, the simulation with the combination of IBIS and modified Emanuel schemes shows the best performance reflected in a marked improvement of precipitation in terms of spatial distribution and monsoon features. In particular, the coupling of IBIS leads to representations of the surface energy balance and partitioning that are consistent with observations. Therefore, the major components of the surface energy budget (including radiation fluxes) in the IBIS simulations are in better agreement with observation than those from our BATS simulation, or from previous similar studies (e.g Steiner et al., 2009), both qualitatively and quantitatively. The IBIS simulations also reasonably reproduce the dynamical structure of vertically stratified behavior of the atmospheric circulation with three major components: westerly monsoon flow, African Easterly Jet (AEJ), and Tropical Easterly Jet (TEJ). In addition, since the modified Emanuel scheme tends to reduce the precipitation amount, it improves the precipitation over regions suffering from systematic wet bias.

Design of the primary pre-TRMM and TRMM ground truth site

NASA Technical Reports Server (NTRS)

Garstang, Michael

1988-01-01

The primary objective of the Tropical Rain Measuring Mission (TRMM) were to: integrate the rain gage measurements with radar measurements of rainfall using the KSFC/Patrick digitized radar and associated rainfall network; delineate the major rain bearing systems over Florida using the Weather Service reported radar/rainfall distributions; combine the integrated measurements with the delineated rain bearing systems; use the results of the combined measurements and delineated rain bearing systems to represent patterns of rainfall which actually exist and contribute significantly to the rainfall to test sampling strategies and based on the results of these analyses decide upon the ground truth network; and complete the design begun in Phase 1 of a multi-scale (space and time) surface observing precipitation network centered upon KSFC. Work accomplished and in progress is discussed.

Applying Customized Climate Advisory Information to Translate Extreme Rainfall Events into Farming Options in the Sudan-Sahel of West Africa

NASA Astrophysics Data System (ADS)

Salack, S.; Worou, N. O.; Sanfo, S.; Nikiema, M. P.; Boubacar, I.; Paturel, J. E.; Tondoh, E. J.

2017-12-01

In West Africa, the risk of food insecurity linked to the low productivity of small holder farming increases as a result of rainfall extremes. In its recent evolution, the rainy season in the Sudan-Sahel zone presents mixed patterns of extreme climatic events. In addition to intense rain events, the distribution of events is associated with pockets of intra-seasonal long dry spells. The negative consequences of these mixed patterns are obvious on the farm: soil water logging, erosion of arable land, dwartness and dessication of crops, and loss in production. The capacity of local farming communities to respond accordingly to rainfall extreme events is often constrained by lack of access to climate information and advisory on smart crop management practices that can help translate extreme rainfall events into farming options. The objective of this work is to expose the framework and the pre-liminary results of a scheme that customizes climate-advisory information package delivery to subsistence farmers in Bakel (Senegal), Ouahigouya & Dano (Burkina Faso) and Bolgatanga (Ghana) for sustainable family agriculture. The package is based on the provision of timely climate information (48-hours, dekadal & seasonal) embedded with smart crop management practices to explore and exploite the potential advantage of intense rainfall and extreme dry spells in millet, maize, sorghum and cowpea farming communities. It is sent via mobile phones and used on selected farms (i.e agro-climatic farm schools) on which some small on-farm infrastructure were built to alleviate negative impacts of weather. Results provide prominent insight on how co-production of weather/climate information, customized access and guidiance on its use can induce fast learning (capacity building of actors), motivation for adaptation, sustainability, potential changes in cropping system, yields and family income in the face of a rainfall extremes at local scales of Sudan-Sahel of West Africa. Keywords: Climate Information, Smart Practices, Farming Options, Agro-Climatic Farm Schools, Sudan-Sahel

The Aggregate Description of Semi-Arid Vegetation with Precipitation-Generated Soil Moisture Heterogeneity

NASA Technical Reports Server (NTRS)

White, Cary B.; Houser, Paul R.; Arain, Altaf M.; Yang, Zong-Liang; Syed, Kamran; Shuttleworth, W. James

1997-01-01

Meteorological measurements in the Walnut Gulch catchment in Arizona were used to synthesize a distributed, hourly-average time series of data across a 26.9 by 12.5 km area with a grid resolution of 480 m for a continuous 18-month period which included two seasons of monsoonal rainfall. Coupled surface-atmosphere model runs established the acceptability (for modelling purposes) of assuming uniformity in all meteorological variables other than rainfall. Rainfall was interpolated onto the grid from an array of 82 recording rain gauges. These meteorological data were used as forcing variables for an equivalent array of stand-alone Biosphere-Atmosphere Transfer Scheme (BATS) models to describe the evolution of soil moisture and surface energy fluxes in response to the prevalent, heterogeneous pattern of convective precipitation. The calculated area-average behaviour was compared with that given by a single aggregate BATS simulation forced with area-average meteorological data. Heterogeneous rainfall gives rise to significant but partly compensating differences in the transpiration and the intercepted rainfall components of total evaporation during rain storms. However, the calculated area-average surface energy fluxes given by the two simulations in rain-free conditions with strong heterogeneity in soil moisture were always close to identical, a result which is independent of whether default or site-specific vegetation and soil parameters were used. Because the spatial variability in soil moisture throughout the catchment has the same order of magnitude as the amount of rain failing in a typical convective storm (commonly 10% of the vegetation's root zone saturation) in a semi-arid environment, non-linearitv in the relationship between transpiration and the soil moisture available to the vegetation has limited influence on area-average surface fluxes.

The added value of convection permitting simulations of extreme precipitation events over the eastern Mediterranean

NASA Astrophysics Data System (ADS)

Zittis, G.; Bruggeman, A.; Camera, C.; Hadjinicolaou, P.; Lelieveld, J.

2017-07-01

Climate change is expected to substantially influence precipitation amounts and distribution. To improve simulations of extreme rainfall events, we analyzed the performance of different convection and microphysics parameterizations of the WRF (Weather Research and Forecasting) model at very high horizontal resolutions (12, 4 and 1 km). Our study focused on the eastern Mediterranean climate change hot-spot. Five extreme rainfall events over Cyprus were identified from observations and were dynamically downscaled from the ERA-Interim (EI) dataset with WRF. We applied an objective ranking scheme, using a 1-km gridded observational dataset over Cyprus and six different performance metrics, to investigate the skill of the WRF configurations. We evaluated the rainfall timing and amounts for the different resolutions, and discussed the observational uncertainty over the particular extreme events by comparing three gridded precipitation datasets (E-OBS, APHRODITE and CHIRPS). Simulations with WRF capture rainfall over the eastern Mediterranean reasonably well for three of the five selected extreme events. For these three cases, the WRF simulations improved the ERA-Interim data, which strongly underestimate the rainfall extremes over Cyprus. The best model performance is obtained for the January 1989 event, simulated with an average bias of 4% and a modified Nash-Sutcliff of 0.72 for the 5-member ensemble of the 1-km simulations. We found overall added value for the convection-permitting simulations, especially over regions of high-elevation. Interestingly, for some cases the intermediate 4-km nest was found to outperform the 1-km simulations for low-elevation coastal parts of Cyprus. Finally, we identified significant and inconsistent discrepancies between the three, state of the art, gridded precipitation datasets for the tested events, highlighting the observational uncertainty in the region.

The Impact of TRMM on Mesoscale Model Simulation of Super Typhoon Paka

NASA Technical Reports Server (NTRS)

Tao, W.-K.; Jia, Y.; Halverson, J.; Hou, A.; Olson, W.; Rodgers, E.; Simpson, J.

1999-01-01

Tropical cyclone Paka formed during the first week of December 1997 and underwent three periods of rapid intensification over the following two weeks. During one of these periods, which initiated early on December 10, Paka's Dvorak-measured windspeed increased from 23 to 60 m/s over a 48-hr period. On December 18, during the last rapid deepening episode, Paka became a supertyphoon with a maximum wind speed of about 80 m/s. In this study, the Penn State/NCAR Mesoscale Model (MM5) with improved physics (i.e., cloud microphysics, radiation, land-soil-vegetation-surface processes, and TOGA COARE flux scheme) and a multiple level nesting technique (135, 45 and 15 km horizontal resolution) will be used to simulate supertyphoon Paka. We performed two runs initialized with Goddard Earth Observing System (GEOS) data sets. The first GEOS data set does not incorporate either TRMM (tropical rainfall measuring mission satellite) or SSM/I (sensor microwave imager) observed rainfall fields into the GEOS's assimilation system while the second one does. Preliminary results show that the MM5 simulated surface pressure deepened by more than 25 mb (45 km resolution domain) in the run initialized with the GEOS data set incorporating TRMM and SSM/I derived rainfall, compared to the one initialized without. However, the track and precipitation patterns are quite similar between the runs. In our presentation, we will show the impact of TRMM rainfall upon the MM5 simulation of Paka at various horizontal resolutions. We will also examine the physical processes associated with initial explosive development by comparing MM5 simulated rainfall and latent heat release. In addition, budget (vorticity, PV, momentum and heat) calculations and sensitivity tests will be performed to examine the upper-tropospheric and SST mechanisms responsible for the explosive development of Paka.

Effects of seasonal variations on antioxidant activity of pink guava fruits

NASA Astrophysics Data System (ADS)

Ahmad, Haniza; Abdullah, Aminah

2014-09-01

This study aimed to evaluate the effects of seasonal variations during rainy and hot season on antioxidant activity of pink guava fruits in approximately one year duration specifically on November 2012, December 2012, January 2013, March 2013, April 2013, May 2013, July 2013, August 2013 and November 2013. Fruit samples (Sungkai and Semenyih variants) were collected from Sime Darby Beverages plantation located in Sitiawan. The fruits were samples for 9 times from Nov 2012 to Nov 2013 except Feb 2013, Jun 2013, Sept 2013 and Oct 2013. Fruits were peeled, seeded and blended into uniform puree. Samples were then extracted for its antioxidant activity determination using 50% acetone. Antioxidant activity was evaluated using total phenolic compounds (TPC) assay, ferric-reducing antioxidant power assay (FRAP) and 1,1-diphenyl1-2-picrylhydrazyl free radical-scavenging capacity (DPPH). Analysis was conducted using 96-well microplate spectrophotometer UV. The highest TPC result was Semenyih var recorded 2192.80 mg GAE/100g FW whilst Sungkai var 1595.98 mg GAE/100g FW both on July 2013 with rainfall was at the least (45mm) and the lowest for Sungkai var was 792.75 mg GAE/100g FW and 1032.41 mg GAE/100g FW for Semenyih var, both on Nov 2012 with 185mm rainfall. There were significant negative correlation between TPC and rainfall (mm) for both Semenyih var (r = - 0.699, p<0.005, r2 = 0.489) and Sungkai var (r = -0.72, p<0.05, r2 = 0.531). The highest FRAP result (mg TE/100g FW) was 1677.74 for Semenyih var (Aug 2013, rainfall = 160.5mm) and the highest FRAP for Sungkai var was 1104.60 (Jul 2013, rainfall = 45.0mm) whereas the lowest for Semenyih and Sungkai var was 1090.22 (Mar 2013, rainfall = 97.5mm) and 767.88 (Nov 2012, rainfall = 185.50) respectively. There was weak negative correlation between FRAP and rainfall(mm) for both Sungkai var (r = - 0.324, p<0.05, r2 = 0.105) and Semenyih var (r = - 0.362, p<0.05, r2 = 0.132). The highest DPPH for Semenyih var was 88.40% (Aug 2013, rainfall = 160.50mm) whilst Sungkai var was 79.71% (July 2013, rainfall = 45.0mm). There was no significant difference in correlation coefficient of DPPH and rainfall (mm). Meanwhile, there was significant correlation between TPC and FRAP (r = 0.794, p<0.05, r2 = 0.629), TPC and DPPH (r = 0.901,p<0.05, r2= 0.812) and FRAP and DPPH (r = 0.889, p<0.05, r2 = 0.792).

The Impact of Aerosols on Cloud and Precipitation Processes: Cloud-Resolving Model Simulations

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Li, X.; Khain, A.; Simpson, S.

2005-01-01

Cloud microphysics are inevitable affected by the smoke particle (CCN, cloud condensation nuclei) size distributions below the clouds, Therefore, size distributions parameterized as spectral bin microphysics are needed to explicitly study the effect of atmospheric aerosol concentration on cloud development, rainfall production, and rainfall rates for convective clouds. Recently, a detailed spectral-bin microphysical scheme was implemented into the the Goddard Cumulus Ensemble (GCE) model. The formulation for the explicit spectral-bim microphysical processes is based on solving stochastic kinetic equations for the size distribution functions of water droplets (i.e., cloud droplets and raindrops), and several types of ice particles [i.e., pristine ice crystals (columnar and plate-like), snow (dendrites and aggregates), graupel and frozen drops/hail]. Each type is described by a special size distribution function containing many categories (i.e., 33 bins). Atmospheric aerosols are also described using number density size-distribution functions.

A parametric approach for simultaneous bias correction and high-resolution downscaling of climate model rainfall

NASA Astrophysics Data System (ADS)

Mamalakis, Antonios; Langousis, Andreas; Deidda, Roberto; Marrocu, Marino

2017-03-01

Distribution mapping has been identified as the most efficient approach to bias-correct climate model rainfall, while reproducing its statistics at spatial and temporal resolutions suitable to run hydrologic models. Yet its implementation based on empirical distributions derived from control samples (referred to as nonparametric distribution mapping) makes the method's performance sensitive to sample length variations, the presence of outliers, the spatial resolution of climate model results, and may lead to biases, especially in extreme rainfall estimation. To address these shortcomings, we propose a methodology for simultaneous bias correction and high-resolution downscaling of climate model rainfall products that uses: (a) a two-component theoretical distribution model (i.e., a generalized Pareto (GP) model for rainfall intensities above a specified threshold u*, and an exponential model for lower rainrates), and (b) proper interpolation of the corresponding distribution parameters on a user-defined high-resolution grid, using kriging for uncertain data. We assess the performance of the suggested parametric approach relative to the nonparametric one, using daily raingauge measurements from a dense network in the island of Sardinia (Italy), and rainfall data from four GCM/RCM model chains of the ENSEMBLES project. The obtained results shed light on the competitive advantages of the parametric approach, which is proved more accurate and considerably less sensitive to the characteristics of the calibration period, independent of the GCM/RCM combination used. This is especially the case for extreme rainfall estimation, where the GP assumption allows for more accurate and robust estimates, also beyond the range of the available data.

Sampling design optimisation for rainfall prediction using a non-stationary geostatistical model

NASA Astrophysics Data System (ADS)

Wadoux, Alexandre M. J.-C.; Brus, Dick J.; Rico-Ramirez, Miguel A.; Heuvelink, Gerard B. M.

2017-09-01

The accuracy of spatial predictions of rainfall by merging rain-gauge and radar data is partly determined by the sampling design of the rain-gauge network. Optimising the locations of the rain-gauges may increase the accuracy of the predictions. Existing spatial sampling design optimisation methods are based on minimisation of the spatially averaged prediction error variance under the assumption of intrinsic stationarity. Over the past years, substantial progress has been made to deal with non-stationary spatial processes in kriging. Various well-documented geostatistical models relax the assumption of stationarity in the mean, while recent studies show the importance of considering non-stationarity in the variance for environmental processes occurring in complex landscapes. We optimised the sampling locations of rain-gauges using an extension of the Kriging with External Drift (KED) model for prediction of rainfall fields. The model incorporates both non-stationarity in the mean and in the variance, which are modelled as functions of external covariates such as radar imagery, distance to radar station and radar beam blockage. Spatial predictions are made repeatedly over time, each time recalibrating the model. The space-time averaged KED variance was minimised by Spatial Simulated Annealing (SSA). The methodology was tested using a case study predicting daily rainfall in the north of England for a one-year period. Results show that (i) the proposed non-stationary variance model outperforms the stationary variance model, and (ii) a small but significant decrease of the rainfall prediction error variance is obtained with the optimised rain-gauge network. In particular, it pays off to place rain-gauges at locations where the radar imagery is inaccurate, while keeping the distribution over the study area sufficiently uniform.

Quantifying Uncertainty in Instantaneous Orbital Data Products of TRMM over Indian Subcontinent

NASA Astrophysics Data System (ADS)

Jayaluxmi, I.; Nagesh, D.

2013-12-01

In the last 20 years, microwave radiometers have taken satellite images of earth's weather proving to be a valuable tool for quantitative estimation of precipitation from space. However, along with the widespread acceptance of microwave based precipitation products, it has also been recognized that they contain large uncertainties. While most of the uncertainty evaluation studies focus on the accuracy of rainfall accumulated over time (e.g., season/year), evaluation of instantaneous rainfall intensities from satellite orbital data products are relatively rare. These instantaneous products are known to potentially cause large uncertainties during real time flood forecasting studies at the watershed scale. Especially over land regions, where the highly varying land surface emissivity offer a myriad of complications hindering accurate rainfall estimation. The error components of orbital data products also tend to interact nonlinearly with hydrologic modeling uncertainty. Keeping these in mind, the present study fosters the development of uncertainty analysis using instantaneous satellite orbital data products (version 7 of 1B11, 2A25, 2A23) derived from the passive and active sensors onboard Tropical Rainfall Measuring Mission (TRMM) satellite, namely TRMM microwave imager (TMI) and Precipitation Radar (PR). The study utilizes 11 years of orbital data from 2002 to 2012 over the Indian subcontinent and examines the influence of various error sources on the convective and stratiform precipitation types. Analysis conducted over the land regions of India investigates three sources of uncertainty in detail. These include 1) Errors due to improper delineation of rainfall signature within microwave footprint (rain/no rain classification), 2) Uncertainty offered by the transfer function linking rainfall with TMI low frequency channels and 3) Sampling errors owing to the narrow swath and infrequent visits of TRMM sensors. Case study results obtained during the Indian summer monsoon months of June-September are presented using contingency table statistics, performance diagram, scatter plots and probability density functions. Our study demonstrates that theory of copula can be efficiently used to represent the highly non linear dependency structure of rainfall with respect to TMI low frequency channels of 19, 21, 37 GHz. This questions the exclusive usage of high frequency 85 GHz channel for TMI overland rainfall retrieval algorithms. Further, the PR sampling errors revealed using a statistical bootstrap technique was found to incur relative sampling errors <30% (for 2 degree grids) over India whose magnitudes were biased towards stratiform rainfall type and sampling technique employed. These findings clearly document that proper characterization of error structure offered by TMI and PR has wider implications for decision making prior to incorporating the resulting orbital products for basin scale hydrologic modeling.

Impact of low intensity summer rainfall on E. coli-discharge event dynamics with reference to sample acquisition and storage.

PubMed

Oliver, David M; Porter, Kenneth D H; Heathwaite, A Louise; Zhang, Ting; Quilliam, Richard S

2015-07-01

Understanding the role of different rainfall scenarios on faecal indicator organism (FIO) dynamics under variable field conditions is important to strengthen the evidence base on which regulators and land managers can base informed decisions regarding diffuse microbial pollution risks. We sought to investigate the impact of low intensity summer rainfall on Escherichia coli-discharge (Q) patterns at the headwater catchment scale in order to provide new empirical data on FIO concentrations observed during baseflow conditions. In addition, we evaluated the potential impact of using automatic samplers to collect and store freshwater samples for subsequent microbial analysis during summer storm sampling campaigns. The temporal variation of E. coli concentrations with Q was captured during six events throughout a relatively dry summer in central Scotland. The relationship between E. coli concentration and Q was complex with no discernible patterns of cell emergence with Q that were repeated across all events. On several occasions, an order of magnitude increase in E. coli concentrations occurred even with slight increases in Q, but responses were not consistent and highlighted the challenges of attempting to characterise temporal responses of E. coli concentrations relative to Q during low intensity rainfall. Cross-comparison of E. coli concentrations determined in water samples using simultaneous manual grab and automated sample collection was undertaken with no difference in concentrations observed between methods. However, the duration of sample storage within the autosampler unit was found to be more problematic in terms of impacting on the representativeness of microbial water quality, with unrefrigerated autosamplers exhibiting significantly different concentrations of E. coli relative to initial samples after 12-h storage. The findings from this study provide important empirical contributions to the growing evidence base in the field of catchment microbial dynamics.

TRMM- and GPM-based precipitation analysis and modelling in the Tropical Andes

NASA Astrophysics Data System (ADS)

Manz, Bastian; Buytaert, Wouter; Zulkafli, Zed; Onof, Christian

2016-04-01

Despite wide-spread applications of satellite-based precipitation products (SPPs) throughout the TRMM-era, the scarcity of ground-based in-situ data (high density gauge networks, rainfall radar) in many hydro-meteorologically important regions, such as tropical mountain environments, has limited our ability to evaluate both SPPs and individual satellite-based sensors as well as accurately model or merge rainfall at high spatial resolutions, particularly with respect to extremes. This has restricted both the understanding of sensor behaviour and performance controls in such regions as well as the accuracy of precipitation estimates and respective hydrological applications ranging from water resources management to early warning systems. Here we report on our recent research into precipitation analysis and modelling using various TRMM and GPM products (2A25, 3B42 and IMERG) in the tropical Andes. In an initial study, 78 high-frequency (10-min) recording gauges in Colombia and Ecuador are used to generate a ground-based validation dataset for evaluation of instantaneous TRMM Precipitation Radar (TPR) overpasses from the 2A25 product. Detection ability, precipitation time-series, empirical distributions and statistical moments are evaluated with respect to regional climatological differences, seasonal behaviour, rainfall types and detection thresholds. Results confirmed previous findings from extra-tropical regions of over-estimation of low rainfall intensities and under-estimation of the highest 10% of rainfall intensities by the TPR. However, in spite of evident regionalised performance differences as a function of local climatological regimes, the TPR provides an accurate estimate of climatological annual and seasonal rainfall means. On this basis, high-resolution (5 km) climatological maps are derived for the entire tropical Andes. The second objective of this work is to improve the local precipitation estimation accuracy and representation of spatial patterns of extreme rainfall probabilities over the region. For this purpose, an ensemble of high-resolution rainfall fields is generated by stochastic simulation using space-time averaged, coarse-scale (daily, 0.25°) satellite-based rainfall inputs (TRMM 3B42/ -RT) and the high-resolution climatological information derived from the TPR as spatial disaggregation proxies. For evaluation and merging, gridded ground-based rainfall fields are generated from gauge data using sequential simulation. Satellite and ground-based ensembles are subsequently merged using an inverse error weighting scheme. The model was tested over a case study in the Colombian Andes with optional coarse-scale bias correction prior to disaggregation and merging. The resulting outputs were assessed in the context of Generalized Extreme Value theory and showed improved estimation of extreme rainfall probabilities compared to the original TMPA inputs. Initial findings using GPM-IMERG inputs are also presented.

Rainfall, Streamflow, and Water-Quality Data During Stormwater Monitoring, Halawa Stream Drainage Basin, Oahu, Hawaii, July 1, 2003 to June 30, 2004

USGS Publications Warehouse

Young, Stacie T.M.; Ball, Marcael T.J.

2004-01-01

Storm runoff water-quality samples were collected as part of the State of Hawaii Department of Transportation Stormwater Monitoring Program. This program is designed to assess the effects of highway runoff and urban runoff on Halawa Stream. For this program, rainfall data were collected at two sites, continuous streamflow data at three sites, and water-quality data at five sites, which include the three streamflow sites. This report summarizes rainfall, streamflow, and water-quality data collected between July 1, 2003 and June 30, 2004. A total of 30 samples was collected over four storms during July 1, 2003 to June 30, 2004. In general, an attempt was made to collect grab samples nearly simultaneously at all five sites, and flow-weighted time-composite samples were collected at the three sites equipped with automatic samplers. However, all four storms were partially sampled because either not all stations were sampled or only grab samples were collected. Samples were analyzed for total suspended solids, total dissolved solids, nutrients, chemical oxygen demand, and selected trace metals (cadmium, copper, lead, and zinc). Grab samples were additionally analyzed for oil and grease, total petroleum hydrocarbons, fecal coliform, and biological oxygen demand. Quality-assurance/quality-control samples, collected during storms and during routine maintenance, were also collected to verify analytical procedures and check the effectiveness of equipment-cleaning procedures.

Statistical Evaluation of Combined Daily Gauge Observations and Rainfall Satellite Estimations over Continental South America

NASA Technical Reports Server (NTRS)

Vila, Daniel; deGoncalves, Luis Gustavo; Toll, David L.; Rozante, Jose Roberto

2008-01-01

This paper describes a comprehensive assessment of a new high-resolution, high-quality gauge-satellite based analysis of daily precipitation over continental South America during 2004. This methodology is based on a combination of additive and multiplicative bias correction schemes in order to get the lowest bias when compared with the observed values. Inter-comparisons and cross-validations tests have been carried out for the control algorithm (TMPA real-time algorithm) and different merging schemes: additive bias correction (ADD), ratio bias correction (RAT) and TMPA research version, for different months belonging to different seasons and for different network densities. All compared merging schemes produce better results than the control algorithm, but when finer temporal (daily) and spatial scale (regional networks) gauge datasets is included in the analysis, the improvement is remarkable. The Combined Scheme (CoSch) presents consistently the best performance among the five techniques. This is also true when a degraded daily gauge network is used instead of full dataset. This technique appears a suitable tool to produce real-time, high-resolution, high-quality gauge-satellite based analyses of daily precipitation over land in regional domains.

A Fresh Start for Flood Estimation in Ungauged UK Catchments

NASA Astrophysics Data System (ADS)

Giani, Giulia; Woods, Ross

2017-04-01

The standard regression-based method for estimating the median annual flood in ungauged UK catchments has a high standard error (95% confidence interval is +/- a factor of 2). This is also the dominant source of uncertainty in statistical estimates of the 100-year flood. Similarly large uncertainties have been reported elsewhere. These large uncertainties make it difficult to do reliable flood design estimates for ungauged catchments. If the uncertainty could be reduced, flood protection schemes could be made significantly more cost-effective. Here we report on attempts to develop a new practical method for flood estimation in ungauged UK catchments, by making more use of knowledge about rainfall-runoff processes. Building on recent research on the seasonality of flooding, we first classify more than 1000 UK catchments into groups according to the seasonality of extreme rainfall and floods, and infer possible causal mechanisms for floods (e.g. Berghuijs et al, Geophysical Research Letters, 2016). For each group we are developing simplified rainfall-runoff-routing relationships (e.g. Viglione et al, Journal of Hydrology, 2010) which can account for spatial and temporal variability in rainfall and flood processes, as well as channel network routing effects. An initial investigation by Viglione et al suggested that the relationship between rainfall amount and flood peak could be summarised through a dimensionless response number that represents the product of the event runoff coefficient and a measure of hydrograph peakedness. Our hypothesis is that this approach is widely applicable, and can be used as the basis for flood estimation. Using subdaily and daily rainfall-runoff data for more than 1000 catchments, we identify a subset of catchments in the west of the UK where floods are generated predominantly in winter through the coincidence of heavy rain and low soil moisture deficits. Floods in these catchments can reliably be simulated with simple rainfall-runoff models, so it is reasonable to expect simple flood estimators. We will report on tests of the several components of the dimensionless response number hypothesis for these catchments.

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.

The effect of sampling scheme in the survey of atmospheric deposition of heavy metals in Albania by using moss biomonitoring.

PubMed

Qarri, Flora; Lazo, Pranvera; Bekteshi, Lirim; Stafilov, Trajce; Frontasyeva, Marina; Harmens, Harry

2015-02-01

The atmospheric deposition of heavy metals in Albania was investigated by using a carpet-forming moss species (Hypnum cupressiforme) as bioindicator. Sampling was done in the dry seasons of autumn 2010 and summer 2011. Two different sampling schemes are discussed in this paper: a random sampling scheme with 62 sampling sites distributed over the whole territory of Albania and systematic sampling scheme with 44 sampling sites distributed over the same territory. Unwashed, dried samples were totally digested by using microwave digestion, and the concentrations of metal elements were determined by inductively coupled plasma atomic emission spectroscopy (ICP-AES) and AAS (Cd and As). Twelve elements, such as conservative and trace elements (Al and Fe and As, Cd, Cr, Cu, Ni, Mn, Pb, V, Zn, and Li), were measured in moss samples. Li as typical lithogenic element is also included. The results reflect local emission points. The median concentrations and statistical parameters of elements were discussed by comparing two sampling schemes. The results of both sampling schemes are compared with the results of other European countries. Different levels of the contamination valuated by the respective contamination factor (CF) of each element are obtained for both sampling schemes, while the local emitters identified like iron-chromium metallurgy and cement industry, oil refinery, mining industry, and transport have been the same for both sampling schemes. In addition, the natural sources, from the accumulation of these metals in mosses caused by metal-enriched soil, associated with wind blowing soils were pointed as another possibility of local emitting factors.

Why sampling scheme matters: the effect of sampling scheme on landscape genetic results

Treesearch

Michael K. Schwartz; Kevin S. McKelvey

2008-01-01

There has been a recent trend in genetic studies of wild populations where researchers have changed their sampling schemes from sampling pre-defined populations to sampling individuals uniformly across landscapes. This reflects the fact that many species under study are continuously distributed rather than clumped into obvious "populations". Once individual...

Hydrologic conditions and quality of rainfall and storm runoff for two agricultural areas of the Oso Creek Watershed, Nueces County, Texas, 2005-07

USGS Publications Warehouse

Ockerman, Darwin J.

2008-01-01

The U.S. Geological Survey, in cooperation with the Texas State Soil and Water Conservation Board, Coastal Bend Bays and Estuaries Program, and Texas AgriLife Research and Extension Center at Corpus Christi, studied hydrologic conditions and quality of rainfall and storm runoff of two (primarily) agricultural areas (subwatersheds) of the Oso Creek watershed in Nueces County, Texas. One area, the upper West Oso Creek subwatershed, is 5,145 acres. The other area, a subwatershed drained by an unnamed Oso Creek tributary (hereinafter, Oso Creek tributary), is 5,287 acres. Rainfall and runoff (streamflow) were continuously monitored at the outlets of the two subwatersheds during October 2005-September 2007. Fourteen rainfall samples were collected and analyzed for nutrients and major inorganic ions. Nineteen composite runoff samples (10 West Oso Creek, nine Oso Creek tributary) were collected and analyzed for nutrients, major inorganic ions, and pesticides. Twenty-two discrete suspended-sediment samples (10 West Oso Creek, 12 Oso Creek tributary) and 13 bacteria samples (eight West Oso Creek, five Oso Creek tributary) were collected and analyzed. These data were used to estimate, for selected constituents, rainfall deposition to and runoff loads and yields from the study subwatersheds. Quantities of fertilizers and pesticides applied in the subwatersheds were compared with quantities of nutrients and pesticides in rainfall and runoff. For the study period, total rainfall was greater than average. Most of the runoff at both subwatershed outlet sites occurred in response to a few specific storm periods. The West Oso Creek subwatershed produced more runoff during the study period than the Oso Creek tributary subwatershed, 10.83 inches compared with 7.28 inches. Runoff response was quicker and peak flows were higher in the West Oso Creek subwatershed than in the Oso Creek tributary subwatershed. Total nitrogen runoff yield for the 2-year study period averaged 2.61 pounds per acre per year from the West Oso Creek subwatershed and 0.966 pound per acre per year from the Oso Creek tributary subwatershed. Total phosphorus yields from the West Oso Creek and the Oso Creek tributary subwatersheds for the 2-year period were 0.776 and 0.498 pound per acre per year. Runoff yields of nitrogen and phosphorus were relatively small compared to inputs of nitrogen in fertilizer and rainfall deposition. Average annual runoff yield of total nitrogen (subwatersheds combined) represents about 2.4 percent of nitrogen applied as fertilizer and nitrogen entering the subwatersheds through rainfall deposition. Average annual runoff yield of total phosphorus (subwatersheds combined) represents about 4.4 percent of the phosphorus in applied fertilizer and rainfall deposition. Suspended-sediment yields from the West Oso Creek subwatershed were more than twice those from the Oso Creek tributary subwatershed. The average suspended-sediment yield from the West Oso Creek subwatershed was 582 pounds per acre per year. The average suspended-sediment yield from the Oso Creek tributary subwatershed was 257 pounds per acre per year. Twenty-two herbicides and eight insecticides were detected in runoff samples collected from the two subwatershed outlet sites. At the West Oso Creek site, 18 herbicides and four insecticides were detected, and at the Oso Creek tributary site, 17 herbicides and six insecticides. Seventeen pesticides were detected in only one sample at low concentrations (near the laboratory reporting level). Atrazine, atrazine degradation byproducts 2-chloro-4-isopropylamino-6-amino-s-triazine (CIAT) and 2-hydroxy-4-isopropylamino-6-ethylamino-s-triazine (OIET), glyphosate, and glyphosate byproduct aminomethylphosphonic acid (AMPA) were detected in all samples. Of all pesticides detected in runoff, the highest runoff yields were for glyphosate, 0.013 pound per acre per year for the West Oso Creek subwatershed and 0.001 pound per acre per year for the Oso Creek t

Trends and spatial distribution of annual and seasonal rainfall in Ethiopia

USGS Publications Warehouse

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

2008-01-01

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

HOW STRONG IS THE RELATIONSHIP BETWEEN RAINFALL VARIABILITY AND CAATINGA PRODUCTIVITY? A CASE STUDY UNDER A CHANGING CLIMATE.

PubMed

Salimon, Cleber; Anderson, Liana

2017-05-22

Despite the knowledge of the influence of rainfall on vegetation dynamics in semiarid tropical Brazil, few studies address and explore quantitatively the various aspects of this relationship. Moreover, Northeast Brazil is expected to have its rainfall reduced by as much as 60% until the end of the 21st Century, under scenario AII of the IPCC Report 2010. We sampled and analyzed satellite-derived monthly rainfall and a vegetation index data for 40 sites with natural vegetation cover in Paraíba State, Brazil from 2001 to 2012. In addition, the anomalies for both variables were calculated. Rainfall variation explained as much as 50% of plant productivity, using the vegetation index as a proxy, and rainfall anomaly explained 80% of the vegetation productivity anomaly. In an extreme dry year (2012), with 65% less rainfall than average for the period 2001-2012, the vegetation index decreased by 25%. If such decrease persists in a long term trend in rainfall reduction, this could lead to a disruption in this ecosystem functioning and the dominant vegetation could become even more xeric or desert-like, bringing serious environmental, social and economical impacts.

Extreme Monsoon Rainfall Signatures Preserved in the Invasive Terrestrial Gastropod Lissachatina fulica

NASA Astrophysics Data System (ADS)

Ghosh, Prosenjit; Rangarajan, Ravi; Thirumalai, Kaustubh; Naggs, Fred

2017-11-01

Indian summer monsoon (ISM) rainfall lasts for a period of 4 months with large variations recorded in terms of rainfall intensity during its period between June and September. Proxy reconstructions of past ISM rainfall variability are required due to the paucity of long instrumental records. However, reconstructing subseasonal rainfall is extremely difficult using conventional hydroclimate proxies due to inadequate sample resolution. Here, we demonstrate the utility of the stable oxygen isotope composition of gastropod shells in reconstructing past rainfall on subseasonal timescales. We present a comparative isotopic study on present day rainwater and stable isotope ratios of precipitate found in the incremental growth bands of giant African land snail Lissachatina fulica (Bowdich) from modern day (2009) and in the historical past (1918). Isotopic signatures present in the growth bands allowed for the identification of ISM rainfall variability in terms of its active and dry spells in the modern as well as past gastropod record. Our results demonstrate the utility of gastropod growth band stable isotope ratios in semiquantitative reconstructions of seasonal rainfall patterns. High resolution climate records extracted from gastropod growth band stable isotopes (museum and archived specimens) can expand the scope for understanding past subseasonal-to-seasonal climate variability.

Rainfall, Streamflow, and Water-Quality Data During Stormwater Monitoring, Halawa Stream Drainage Basin, Oahu, Hawaii, July 1, 2006 to June 30, 2007

USGS Publications Warehouse

Young, Stacie T.M.; Jamison, Marcael T.J.

2007-01-01

Storm runoff water-quality samples were collected as part of the State of Hawaii Department of Transportation Stormwater Monitoring Program. This program is designed to assess the effects of highway runoff and urban runoff on Halawa Stream. For this program, rainfall data were collected at two stations, continuous streamflow data at three stations, and water-quality data at five stations, which include the two continuous streamflow stations. This report summarizes rainfall, streamflow, and water-quality data collected between July 1, 2006 and June 30, 2007. A total of 13 samples was collected over two storms during July 1, 2006 to June 30, 2007. The goal was to collect grab samples nearly simultaneously at all five stations and flow-weighted time-composite samples at the three stations equipped with automatic samplers. Samples were analyzed for total suspended solids, total dissolved solids, nutrients, chemical oxygen demand, and selected trace metals (cadmium, chromium, copper, lead, nickel, and zinc). Additionally, grab samples were analyzed for oil and grease, total petroleum hydrocarbons, fecal coliform, and biological oxygen demand. Quality-assurance/quality-control samples were also collected during storms and during routine maintenance to verify analytical procedures and check the effectiveness of equipment-cleaning procedures.

Vegetation Variability And Its Effect On Monsoon Rainfall Over South East Asia: Observational and Modeling Results

NASA Astrophysics Data System (ADS)

Sarkar, S.; Peters-Lidard, C.; Chiu, L.; Kafatos, M.

2005-12-01

Increasing population and urbanization have created stress on developing nations. The quickly shifting patterns of vegetation change in different parts of the world have given rise to the pertinent question of feedback on the climate prevailing on local to regional scales. It is now known with some certainty, that vegetation changes can affect the climate by influencing the heat and water balance. The hydrological cycle particularly is susceptible to changes in vegetation. The Monsoon rainfall forms a vital link in the hydrological cycle prevailing over South East Asia This work examines the variability of vegetation over South East Asia and assesses its impact on the monsoon rainfall. We explain the role of changing vegetation and show how this change has affected the heat and energy balance. We demonstrate the role of vegetation one season earlier in influencing rainfall intensity over specific areas in South East Asia and show the ramification of vegetation change on the summer rainfall behavior. The vegetation variability study specifically focuses on India and China, two of the largest and most populous nations. We have done an assessment to find out the key meteorological and human induced parameters affecting vegetation over the study area through a spatial analysis of monthly NDVI values. This study highlights the role of monsoon rainfall, regional climate dynamics and large scale human induced pollution to be the crucial factors governing the vegetation and vegetation distribution. The vegetation is seen to follow distinct spatial patterns that have been found to be crucial in its eventual impact on monsoon rainfall. We have carried out a series of sensitivity experiments using a land surface hydrologic modeling scheme. The vital energy and water balance parameters are identified and the daily climatological cycles are examined for possible change in behavior for different boundary conditions. It is found that the change from native deciduous forest vegetation to crop land affects monsoon rainfall in two ways: 1) The presence of cropland increases the sensible heat release from ground, increasing the chances for development of forced convection; 2) Large scale irrigation associated with spring crop development creates a moister lower boundary layer thus inducing more moist instability and free convection in the succeeding season.

A downscaling method for the assessment of local climate change

NASA Astrophysics Data System (ADS)

Bruno, E.; Portoghese, I.; Vurro, M.

2009-04-01

The use of complimentary models is necessary to study the impact of climate change scenarios on the hydrological response at different space-time scales. However, the structure of GCMs is such that their space resolution (hundreds of kilometres) is too coarse and not adequate to describe the variability of extreme events at basin scale (Burlando and Rosso, 2002). To bridge the space-time gap between the climate scenarios and the usual scale of the inputs for hydrological prediction models is a fundamental requisite for the evaluation of climate change impacts on water resources. Since models operate a simplification of a complex reality, their results cannot be expected to fit with climate observations. Identifying local climate scenarios for impact analysis implies the definition of more detailed local scenario by downscaling GCMs or RCMs results. Among the output correction methods we consider the statistical approach by Déqué (2007) reported as a ‘Variable correction method' in which the correction of model outputs is obtained by a function build with the observation dataset and operating a quantile-quantile transformation (Q-Q transform). However, in the case of daily precipitation fields the Q-Q transform is not able to correct the temporal property of the model output concerning the dry-wet lacunarity process. An alternative correction method is proposed based on a stochastic description of the arrival-duration-intensity processes in coherence with the Poissonian Rectangular Pulse scheme (PRP) (Eagleson, 1972). In this proposed approach, the Q-Q transform is applied to the PRP variables derived from the daily rainfall datasets. Consequently the corrected PRP parameters are used for the synthetic generation of statistically homogeneous rainfall time series that mimic the persistency of daily observations for the reference period. Then the PRP parameters are forced through the GCM scenarios to generate local scale rainfall records for the 21st century. The statistical parameters characterizing daily storm occurrence, storm intensity and duration needed to apply the PRP scheme are considered among STARDEX collection of extreme indices.

Impact of Multiple Environmental Stresses on Wetland Vegetation Dynamics

NASA Astrophysics Data System (ADS)

Muneepeerakul, C. P.; Tamea, S.; Muneepeerakul, R.; Miralles-Wilhelm, F. R.; Rinaldo, A.; Rodriguez-Iturbe, I.

2009-12-01

This research quantifies the impacts of climate change on the dynamics of wetland vegetation under the effect of multiple stresses, such as drought, water-logging, shade and nutrients. The effects of these stresses are investigated through a mechanistic model that captures the co-evolving nature between marsh emergent plant species and their resources (water, nitrogen, light, and oxygen). The model explicitly considers the feedback mechanisms between vegetation, light and nitrogen dynamics as well as the specific dynamics of plant leaves, rhizomes, and roots. Each plant species is characterized by three independent traits, namely leaf nitrogen (N) content, specific leaf area, and allometric carbon (C) allocation to rhizome storage, which govern the ability to gain and maintain resources as well as to survive in a particular multi-stressed environment. The modeling of plant growth incorporates C and N into the construction of leaves and roots, whose amount of new biomass is determined by the dynamic plant allocation scheme. Nitrogen is internally recycled between pools of plants, litter, humus, microbes, and mineral N. The N dynamics are modeled using a parallel scheme, with the major modifications being the calculation of the aerobic and anoxic periods and the incorporation of the anaerobic processes. A simple hydrologic model with stochastic rainfall is used to describe the water level dynamics and the soil moisture profile. Soil water balance is evaluated at the daily time scale and includes rainfall, evapotranspiration and lateral flow to/from an external water body, with evapotranspiration loss equal to the potential value, governed by the daily average condition of atmospheric water demand. The resulting feedback dynamics arising from the coupled system of plant-soil-microbe are studied in details and species’ fitnesses in the 3-D trait space are compared across various rainfall patterns with different mean and fluctuations. The model results are then compared with those from experiments and field studies reported in the literature, providing insights about the physiological features that enable plants to thrive in different wetland environments and climate regimes.

Occurrence and Transport of Agricultural Chemicals in Leary Weber Ditch Basin, Hancock County, Indiana, 2003-04

USGS Publications Warehouse

Baker, Nancy T.; Stone, Wesley W.; Wilson, John T.; Meyer, Michael T.

2006-01-01

Leary Weber Ditch Basin, Hancock County, Indiana, is one of seven first-order basins selected from across the United States as part of the Agricultural Chemicals: Source, Transport, and Fate study conducted by the National Water-Quality Assessment Program of the U.S. Geological Survey. The nationwide study was designed to increase the understanding of the links between the sources of water and agricultural chemicals (nutrients and pesticides) and the transport and fate of these chemicals through the environment. Agricultural chemicals were detected in Leary Weber Ditch and in every associated hydrologic compartment sampled during 2003 and 2004. Pesticides were detected more frequently in samples collected from overland flow and from the ditch itself and less frequently in ground-water samples. The lowest concentrations of pesticides and nutrients were detected in samples of rain, soil water, and ground water. The highest concentrations of pesticides and nutrients were detected in samples of tile-drain water, overland flow, and water from Leary Weber Ditch. Samples collected from the tile drain, overland flow and Leary Weber Ditch soon after chemical applications to the fields and coincident with rainfall and increased streamflow had higher concentrations of pesticides and nutrients than samples collected a longer time after the chemicals were applied. A mass-balance mixing analysis based on potassium concentrations indicated that tile drains are the primary contributor of water to Leary Weber Ditch, but overland flow is also an important contributor during periods of high-intensity rainfall. When maximum rainfall intensity was 0.5 inches per hour or lower, overland flow contributed about 10 percent and tile drains contributed about 90 percent of the flow to Leary Weber Ditch. When maximum rainfall intensity was 0.75 inches per hour or greater, overland flow contributed about 40 percent and tile drains contributed about 60 percent of the flow to the ditch. Ground-water flow to Leary Weber Ditch was negligible. Tile drains are an important agricultural-chemical transport path to Leary Weber Ditch, based on the hydrologic contributions of overland flow and tile drains to the ditch. Overland flow is also an important agricultural-chemical transport pathway during high-intensity rainfall; however, storms with high-intensity rainfall are sporadic throughout the year. Tile drains and the soil water moving to the tile drains are the primary transport pathway for agricultural-chemical transport to Leary Weber Ditch during most storms as well as between storms.

Global Warming Induced Changes in Rainfall Characteristics in IPCC AR5 Models

NASA Technical Reports Server (NTRS)

Lau, William K. M.; Wu, Jenny, H.-T.; Kim, Kyu-Myong

2012-01-01

Changes in rainfall characteristic induced by global warming are examined from outputs of IPCC AR5 models. Different scenarios of climate warming including a high emissions scenario (RCP 8.5), a medium mitigation scenario (RCP 4.5), and 1% per year CO2 increase are compared to 20th century simulations (historical). Results show that even though the spatial distribution of monthly rainfall anomalies vary greatly among models, the ensemble mean from a sizable sample (about 10) of AR5 models show a robust signal attributable to GHG warming featuring a shift in the global rainfall probability distribution function (PDF) with significant increase (>100%) in very heavy rain, reduction (10-20% ) in moderate rain and increase in light to very light rains. Changes in extreme rainfall as a function of seasons and latitudes are also examined, and are similar to the non-seasonal stratified data, but with more specific spatial dependence. These results are consistent from TRMM and GPCP rainfall observations suggesting that extreme rainfall events are occurring more frequently with wet areas getting wetter and dry-area-getting drier in a GHG induced warmer climate.

Spatial variability of extreme rainfall at radar subpixel scale

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

Describing soil surface microrelief by crossover length and fractal dimension

NASA Astrophysics Data System (ADS)

Vidal Vázquez, E.; Miranda, J. G. V.; Paz González, A.

2007-05-01

Accurate description of soil surface topography is essential because different tillage tools produce different soil surface roughness conditions, which in turn affects many processes across the soil surface boundary. Advantages of fractal analysis in soil microrelief assessment have been recognised but the use of fractal indices in practice remains challenging. There is also little information on how soil surface roughness decays under natural rainfall conditions. The objectives of this work were to investigate the decay of initial surface roughness induced by natural rainfall under different soil tillage systems and to compare the performances of a classical statistical index and fractal microrelief indices. Field experiments were performed on an Oxisol at Campinas, São Paulo State (Brazil). Six tillage treatments, namely, disc harrow, disc plow, chisel plow, disc harrow + disc level, disc plow + disc level and chisel plow + disc level were tested. Measurements were made four times, firstly just after tillage and subsequently with increasing amounts of natural rainfall. Duplicated measurements were taken per treatment and date, yielding a total of 48 experimental surfaces. The sampling scheme was a square grid with 25×25 mm point spacing and the plot size was 1350×1350 mm, so that each data set consisted of 3025 individual elevation points. Statistical and fractal indices were calculated both for oriented and random roughness conditions, i.e. after height reading have been corrected for slope and for slope and tillage tool marks. The main drawback of the standard statistical index random roughness, RR, lies in its no spatial nature. The fractal approach requires two indices, fractal dimension, D, which describes how roughness changes with scale, and crossover length, l, specifying the variance of surface microrelief at a reference scale. Fractal parameters D and l, were estimated by two independent self-affine models, semivariogram (SMV) and local root mean square (RMS). Both algorithms, SMV and RMS, gave equivalent results for D and l indices, irrespective of trend removal procedure, even if some bias was present which is in accordance with previous work. Treatments with two tillage operations had the greatest D values, irrespective of evolution stage under rainfall and trend removal procedure. Primary tillage had the greatest initial values of RR and l. Differences in D values between treatments with primary tillage and those with two successive tillage operations were significant for oriented but not for random conditions. The statistical index RR and the fractal indices l and D decreased with increasing cumulative rainfall following different patterns. The l and D decay from initial value was very sharp after the first 24.4 mm cumulative rainfall. For five out of six tillage treatments a significant relationship between D and l was found for the random microrelief conditions allowing a covariance analysis. It was concluded that using RR or l together with D best allow joint description of vertical and horizontal soil roughness variations.

Automated reconstruction of rainfall events responsible for shallow landslides

NASA Astrophysics Data System (ADS)

Vessia, G.; Parise, M.; Brunetti, M. T.; Peruccacci, S.; Rossi, M.; Vennari, C.; Guzzetti, F.

2014-04-01

Over the last 40 years, many contributions have been devoted to identifying the empirical rainfall thresholds (e.g. intensity vs. duration ID, cumulated rainfall vs. duration ED, cumulated rainfall vs. intensity EI) for the initiation of shallow landslides, based on local as well as worldwide inventories. Although different methods to trace the threshold curves have been proposed and discussed in literature, a systematic study to develop an automated procedure to select the rainfall event responsible for the landslide occurrence has rarely been addressed. Nonetheless, objective criteria for estimating the rainfall responsible for the landslide occurrence (effective rainfall) play a prominent role on the threshold values. In this paper, two criteria for the identification of the effective rainfall events are presented: (1) the first is based on the analysis of the time series of rainfall mean intensity values over one month preceding the landslide occurrence, and (2) the second on the analysis of the trend in the time function of the cumulated mean intensity series calculated from the rainfall records measured through rain gauges. The two criteria have been implemented in an automated procedure written in R language. A sample of 100 shallow landslides collected in Italy by the CNR-IRPI research group from 2002 to 2012 has been used to calibrate the proposed procedure. The cumulated rainfall E and duration D of rainfall events that triggered the documented landslides are calculated through the new procedure and are fitted with power law in the (D,E) diagram. The results are discussed by comparing the (D,E) pairs calculated by the automated procedure and the ones by the expert method.

Rainfall, Streamflow, and Water-Quality Data During Stormwater Monitoring, Halawa Stream Drainage Basin, Oahu, Hawaii, July 1, 2002 to June 30, 2003

USGS Publications Warehouse

Young, Stacie T.M.; Ball, Marcael T.J.

2003-01-01

Storm runoff water-quality samples were collected as part of the State of Hawaii Department of Transportation Stormwater Monitoring Program. This program is designed to assess the effects of highway runoff and urban runoff on Halawa Stream. For this program, rainfall data was collected at two sites, continuous streamflow data at three sites, and water-quality data at five sites, which include the three streamflow sites. This report summarizes rainfall, streamflow, and water-quality data collected between July 1, 2002 to June 30, 2003. A total of 28 samples were collected over five storms during July 1, 2002 to June 30, 2003. For two of the five storms, five grab samples and three flow-weighted timecomposite samples were collected. Grab samples were collected nearly simultaneously at all five sites, and flow-weighted timecomposite samples were collected at the three sites equipped with automatic samplers. The other three storms were partially sampled, where only flow-weighted time-composite samples were collected and/or not all stations were sampled. Samples were analyzed for total suspended solids, total dissolved solids, nutrients, chemical oxygen demand, and selected trace metals (cadmium, copper, lead, and zinc). Grab samples were additionally analyzed for oil and grease, total petroleum hydrocarbons, fecal coliform, and biological oxygen demand. Quality-assurance/qualitycontrol samples, collected during storms and during routine maintenance, were also collected to verify analytical procedures and insure proper cleaning of equipment.

Exploration of a Dynamic Merging Scheme for Precipitation Estimation over a Small Urban Catchment

NASA Astrophysics Data System (ADS)

Al-Azerji, Sherien; Rico-Ramirez, Miguel, ,, Dr.; Han, Dawei, ,, Prof.

2016-04-01

The accuracy of quantitative precipitation estimation is of significant importance for urban areas due to the potentially damaging consequences that can result from pluvial flooding. Improved accuracy could be accomplished by merging rain gauge measurements with weather radar data through different merging methods. Several factors may affect the accuracy of the merged data, and the gauge density used for merging is one of the most important. However, if there are no gauges inside the research area, then a gauge network outside the research area can be used for the merging. Generally speaking, the denser the rain gauge network is, the better the merging results that can be achieved. However, in practice, the rain gauge network around the research area is fixed, and the research question is about the optimal merging area. The hypothesis is that if the merging area is too small, there are fewer gauges for merging and thus the result would be poor. If the merging area is too large, gauges far away from the research area can be included in merging. However, due to their large distances, those gauges far away from the research area provide little relevant information to the study and may even introduce noise in merging. Therefore, an optimal merging area that produces the best merged rainfall estimation in the research area could exist. To test this hypothesis, the distance from the centre of the research area and the number of merging gauges around the research area were gradually increased and merging with a new domain of radar data was then performed. The performance of the new merging scheme was compared with a gridded interpolated rainfall from four experimental rain gauges installed inside the research area for validation. The result of this analysis shows that there is indeed an optimum distance from the centre of research area and consequently an optimum number of rain gauges that produce the best merged rainfall data inside the research area. This study is of important and practical value for estimating rainfall in an urban catchment (when there are no gauges available inside the catchment) by merging weather radar with rain gauge data from outside of the catchment. This has not been reported in any literature before now.

Improving operational flood ensemble prediction by the assimilation of satellite soil moisture: comparison between lumped and semi-distributed schemes

NASA Astrophysics Data System (ADS)

Alvarez-Garreton, C.; Ryu, D.; Western, A. W.; Su, C.-H.; Crow, W. T.; Robertson, D. E.; Leahy, C.

2014-09-01

Assimilation of remotely sensed soil moisture data (SM-DA) to correct soil water stores of rainfall-runoff models has shown skill in improving streamflow prediction. In the case of large and sparsely monitored catchments, SM-DA is a particularly attractive tool. Within this context, we assimilate active and passive satellite soil moisture (SSM) retrievals using an ensemble Kalman filter to improve operational flood prediction within a large semi-arid catchment in Australia (>40 000 km2). We assess the importance of accounting for channel routing and the spatial distribution of forcing data by applying SM-DA to a lumped and a semi-distributed scheme of the probability distributed model (PDM). Our scheme also accounts for model error representation and seasonal biases and errors in the satellite data. Before assimilation, the semi-distributed model provided more accurate streamflow prediction (Nash-Sutcliffe efficiency, NS = 0.77) than the lumped model (NS = 0.67) at the catchment outlet. However, this did not ensure good performance at the "ungauged" inner catchments. After SM-DA, the streamflow ensemble prediction at the outlet was improved in both the lumped and the semi-distributed schemes: the root mean square error of the ensemble was reduced by 27 and 31%, respectively; the NS of the ensemble mean increased by 7 and 38%, respectively; the false alarm ratio was reduced by 15 and 25%, respectively; and the ensemble prediction spread was reduced while its reliability was maintained. Our findings imply that even when rainfall is the main driver of flooding in semi-arid catchments, adequately processed SSM can be used to reduce errors in the model soil moisture, which in turn provides better streamflow ensemble prediction. We demonstrate that SM-DA efficacy is enhanced when the spatial distribution in forcing data and routing processes are accounted for. At ungauged locations, SM-DA is effective at improving streamflow ensemble prediction, however, the updated prediction is still poor since SM-DA does not address systematic errors in the model.

Bias correction of satellite-based rainfall data

NASA Astrophysics Data System (ADS)

Bhattacharya, Biswa; Solomatine, Dimitri

2015-04-01

Limitation in hydro-meteorological data availability in many catchments limits the possibility of reliable hydrological analyses especially for near-real-time predictions. However, the variety of satellite based and meteorological model products for rainfall provides new opportunities. Often times the accuracy of these rainfall products, when compared to rain gauge measurements, is not impressive. The systematic differences of these rainfall products from gauge observations can be partially compensated by adopting a bias (error) correction. Many of such methods correct the satellite based rainfall data by comparing their mean value to the mean value of rain gauge data. Refined approaches may also first find out a suitable time scale at which different data products are better comparable and then employ a bias correction at that time scale. More elegant methods use quantile-to-quantile bias correction, which however, assumes that the available (often limited) sample size can be useful in comparing probabilities of different rainfall products. Analysis of rainfall data and understanding of the process of its generation reveals that the bias in different rainfall data varies in space and time. The time aspect is sometimes taken into account by considering the seasonality. In this research we have adopted a bias correction approach that takes into account the variation of rainfall in space and time. A clustering based approach is employed in which every new data point (e.g. of Tropical Rainfall Measuring Mission (TRMM)) is first assigned to a specific cluster of that data product and then, by identifying the corresponding cluster of gauge data, the bias correction specific to that cluster is adopted. The presented approach considers the space-time variation of rainfall and as a result the corrected data is more realistic. Keywords: bias correction, rainfall, TRMM, satellite rainfall

Assessment of rain water chemistry in the Lucknow metropolitan city

NASA Astrophysics Data System (ADS)

Sharma, Purnima; Rai, Vibhuti

2018-05-01

Lucknow metropolitan city is one of the most populated cities of India, which have been facing many problems such as chaotic urbanization, overpopulation, water scarcity, waterlogging, etc., among these water scarcity is one of the important problem. Rain water harvesting is a futuristic tool for mitigation of water scarcity problem through conservation and storage of rain water. This rain water can be used for all purposes by human beings, thus it is necessary to check the chemistry of rain water. The rain water samples were collected from the five zones of Lucknow city. For the comparative study, water samples have been collected from two different dates first from first rainfall and second after 3 days of interval in the second rainfall. The heavy metal concentrations were found in both first and second rainfall water samples in all zones of Lucknow city. The concentration of chromium, cadmium and lead were found to be sufficiently high in several samples. These heavy metals show the concentration above the permissible limit as set by WHO, which can cause various adverse health impacts.

Application of spatial Poisson process models to air mass thunderstorm rainfall

NASA Technical Reports Server (NTRS)

Eagleson, P. S.; Fennessy, N. M.; Wang, Qinliang; Rodriguez-Iturbe, I.

1987-01-01

Eight years of summer storm rainfall observations from 93 stations in and around the 154 sq km Walnut Gulch catchment of the Agricultural Research Service, U.S. Department of Agriculture, in Arizona are processed to yield the total station depths of 428 storms. Statistical analysis of these random fields yields the first two moments, the spatial correlation and variance functions, and the spatial distribution of total rainfall for each storm. The absolute and relative worth of three Poisson models are evaluated by comparing their prediction of the spatial distribution of storm rainfall with observations from the second half of the sample. The effect of interstorm parameter variation is examined.

TRMM Applications for Rainfall-Induced Landslide Early Warning

NASA Astrophysics Data System (ADS)

Dok, A.; Fukuoka, H.; Hong, Y.

2012-04-01

Early warning system (EWS) is the most effective method in saving lives and reducing property damages resulted from the catastrophic landslides if properly implemented in populated areas of landslide-prone nations. For predicting the occurrence of landslides, it requires examination of empirical relationship between rainfall characteristics and past landslide occurrence. In developed countries like Japan and the US, precipitation is monitored by rain radars and ground-based rain gauge matrix. However, in developing regions like Southeast Asian countries, very limited number of rain gauges is available, and there is no implemented methodology for issuing effective warming of landslides yet. Correspondingly, satellite precipitation monitoring could be therefore a possible and promising solution for launching landslide quasi-real-time early warning system in those countries. It is due to the fact that TMPA (TRMM Multi-satellite Precipitation Analysis) can provides a globally calibration-based sequential scheme for combining precipitation estimates from multiple satellites, and gauge analyses where feasible, at fine scales (3-hourly with 0.25°x0.25° spatial resolution). It is available both after and in quasi-real time, calibrated by TRMM Combined Instrument and TRMM Microwave Imager precipitation product. However, validation of ground based rain gauge and TRMM satellite data in the vulnerable regions is still not yet operative. Snake-line/Critical-line and Soil Water Index (SWI) are used for issuing warning of landslide occurrence in Japan; whereas, Caine criterion is preferable in Europe and western nations. Herewith, it presents rainfall behavior which took place in Beichuan city (located on the 2008 Chinese Wenchuan earthquake fault), Hofu and Shobara cities in Japan where localized heavy rainfall attacked in 2009 and 2010, respectively, from TRMM 3B42RT correlated with ground based rain gauge data. The 1-day rainfall intensity and 15-day cumulative rainfall (snake line) were independently plotted to investigate the impact of short-term rainfall intensity and accumulated effective rainfall volume respectively for obtaining some probabilistic threshold. Japanese SWI was also tested to distribute threshold regarding to highly nonlinear rainfall patterns in predicting the landslide occurrence through the plot of total water of 3 serial tank models and daily precipitation. As a result, the snake line plots using TMPA work well for landslide warning in the selected cities; while SWI plots shows unusual peak value on the day of the debris flow occurrence. Graph of daily precipitation vs SWI implies possible zone of critical line, and second peak appearance 1 day before, indicating possibility of early warning.

Accounting for sensor calibration, data validation, measurement and sampling uncertainties in monitoring urban drainage systems.

PubMed

Bertrand-Krajewski, J L; Bardin, J P; Mourad, M; Béranger, Y

2003-01-01

Assessing the functioning and the performance of urban drainage systems on both rainfall event and yearly time scales is usually based on online measurements of flow rates and on samples of influent effluent for some rainfall events per year. In order to draw pertinent scientific and operational conclusions from the measurement results, it is absolutely necessary to use appropriate methods and techniques in order to i) calibrate sensors and analytical methods, ii) validate raw data, iii) evaluate measurement uncertainties, iv) evaluate the number of rainfall events to sample per year in order to determine performance indicator with a given uncertainty. Based an previous work, the paper gives a synthetic review of required and techniques, and illustrates their application to storage and settling tanks. Experiments show that, controlled and careful experimental conditions, relative uncertainties are about 20% for flow rates in sewer pipes, 6-10% for volumes, 25-35% for TSS concentrations and loads, and 18-276% for TSS removal rates. In order to evaluate the annual pollutant interception efficiency of storage and settling tanks with a given uncertainty, efforts should first be devoted to decrease the sampling uncertainty by increasing the number of sampled events.

Effects of rainfall events on the occurrence and detection efficiency of viruses in river water impacted by combined sewer overflows.

PubMed

Hata, Akihiko; Katayama, Hiroyuki; Kojima, Keisuke; Sano, Shoichi; Kasuga, Ikuro; Kitajima, Masaaki; Furumai, Hiroaki

2014-01-15

Rainfall events can introduce large amount of microbial contaminants including human enteric viruses into surface water by intermittent discharges from combined sewer overflows (CSOs). The present study aimed to investigate the effect of rainfall events on viral loads in surface waters impacted by CSO and the reliability of molecular methods for detection of enteric viruses. The reliability of virus detection in the samples was assessed by using process controls for virus concentration, nucleic acid extraction and reverse transcription (RT)-quantitative PCR (qPCR) steps, which allowed accurate estimation of virus detection efficiencies. Recovery efficiencies of poliovirus in river water samples collected during rainfall events (<10%) were lower than those during dry weather conditions (>10%). The log10-transformed virus concentration efficiency was negatively correlated with suspended solid concentration (r(2)=0.86) that increased significantly during rainfall events. Efficiencies of DNA extraction and qPCR steps determined with adenovirus type 5 and a primer sharing control, respectively, were lower in dry weather. However, no clear relationship was observed between organic water quality parameters and efficiencies of these two steps. Observed concentrations of indigenous enteric adenoviruses, GII-noroviruses, enteroviruses, and Aichi viruses increased during rainfall events even though the virus concentration efficiency was presumed to be lower than in dry weather. The present study highlights the importance of using appropriate process controls to evaluate accurately the concentration of water borne enteric viruses in natural waters impacted by wastewater discharge, stormwater, and CSOs. © 2013.

Comparison between snowmelt-runoff and rainfall-runoff nonpoint source pollution in a typical urban catchment in Beijing, China.

PubMed

Chen, Lei; Zhi, Xiaosha; Shen, Zhenyao; Dai, Ying; Aini, Guzhanuer

2018-01-01

As a climate-driven event, nonpoint source (NPS) pollution is caused by rainfall- or snowmelt-runoff processes; however, few studies have compared the characteristics and mechanisms of these two kinds of NPS processes. In this study, three factors relating to urban NPS, including surface dust, snowmelt, and rainfall-runoff processes, were analyzed comprehensively by both field sampling and laboratory experiments. The seasonal variation and leaching characteristics of pollutants in surface dust were explored, and the runoff quality of snowmelt NPS and rainfall NPS were compared. The results indicated that dusts are the main sources of urban NPS and more pollutants are deposited in dust samples during winter and spring. However, pollutants in surface dust showed a low leaching ratio, which indicated most NPS pollutants would be carried as particulate forms. Compared to surface layer, underlying snow contained higher chemical oxygen demand, total suspended solids (TSS), Cu, Fe, Mn, and Pb concentrations, while the event mean concentration of most pollutants in snowmelt tended to be higher in roads. Moreover, the TSS and heavy metal content of snowmelt NPS was always higher than those of rainfall NPS, which indicated the importance of controlling snowmelt pollution for effective water quality management.

Calibrating SALT: a sampling scheme to improve estimates of suspended sediment yield

Treesearch

Robert B. Thomas

1986-01-01

Abstract - SALT (Selection At List Time) is a variable probability sampling scheme that provides unbiased estimates of suspended sediment yield and its variance. SALT performs better than standard schemes which are estimate variance. Sampling probabilities are based on a sediment rating function which promotes greater sampling intensity during periods of high...

Simulation of radar reflectivity and surface measurements of rainfall

NASA Technical Reports Server (NTRS)

Chandrasekar, V.; Bringi, V. N.

1987-01-01

Raindrop size distributions (RSDs) are often estimated using surface raindrop sampling devices (e.g., disdrometers) or optical array (2D-PMS) probes. A number of authors have used these measured distributions to compute certain higher-order RSD moments that correspond to radar reflectivity, attenuation, optical extinction, etc. Scatter plots of these RSD moments versus disdrometer-measured rainrates are then used to deduce physical relationships between radar reflectivity, attenuation, etc., which are measured by independent instruments (e.g., radar), and rainrate. In this paper RSDs of the gamma form as well as radar reflectivity (via time series simulation) are simulated to study the correlation structure of radar estimates versus rainrate as opposed to RSD moment estimates versus rainrate. The parameters N0, D0 and m of a gamma distribution are varied over the range normally found in rainfall, as well as varying the device sampling volume. The simulations are used to explain some possible features related to discrepancies which can arise when radar rainfall measurements are compared with surface or aircraft-based sampling devices.

Hydrologic conditions and water quality in an agricultural area in Kleberg and Nueces Counties, Texas, 1996-98

USGS Publications Warehouse

Ockerman, Darwin J.; Petri, Brian L.

2001-01-01

During 1996?98, rainfall and runoff were monitored on a 49,680-acre agricultural watershed in Kleberg and Nueces Counties in South Texas. Nineteen rainfall samples were analyzed for selected nutrients, and runoff samples from 29 storms were analyzed for major ions, nutrients, and pesticides. Loads of nutrients in rainfall and loads of nutrients and pesticides in runoff were computed. For a 40,540-acre part of the watershed (lower study area), constituent loads entering the watershed in rainfall, in runoff from the upper study area, and from agricultural chemical applications to the lower study area were compared with runoff loads exiting the lower study area. Total rainfall for 1996?98 averaged 25.86 inches per year, which is less than the long-term annual average rainfall of 29.80 inches for the area. Rainfall and runoff during 1996?98 were typical of historical patterns, with periods of below average rainfall and runoff interspersed with extreme events. Five individual storms accounted for about 38 percent of the total rainfall and 94 percent of the total runoff. During the 3-year study, the total nitrogen runoff yield from the lower study area was 1.3 pounds per acre per year, compared with 49 pounds per acre per year applied as fertilizer and 3.1 pounds per acre per year from rainfall. While almost all of the fertilizer and rainfall nitrogen was ammonia and nitrate, most of the nitrogen in runoff was particulate organic nitrogen, associated with crop residue. Total nitrogen exiting the lower study area in surface-water runoff was about 2.5 percent of the nitrogen inputs (fertilizer and rainfall nitrogen). Annual deposition of total nitrogen entering the lower study area in rainfall exceeded net yields of total nitrogen exiting the watershed in runoff because most of the rainfall does not contribute to runoff. During the study, the total phosphorus runoff yield from the lower study area was 0.48 pound per acre per year compared with 4.2 pounds per acre per year applied as fertilizer and 0.03 pound per acre per year from rainfall. Twenty-one pesticides were detected in runoff with varying degrees of frequency during the study. The herbicide atrazine was detected in all runoff samples. All of the most frequently detected pesticides (atrazine, trifluralin, simazine, pendimethalin, and diuron) exhibited higher concentrations during the pre-harvest period (March? May) than during the post-harvest period (August? October). During 1996?98, an average of 0.37 pound per acre per year of atrazine was applied to the lower study area. During the same period, 0.0027 pound per acre per year of atrazine and its breakdown product deethylatrazine exited the lower study area in runoff (about 0.7 percent of the total atrazine applied to the cropland). During 1997, when heavy rainfall occurred during the months of April and May, the atrazine plus deethylatrazine exiting the lower study area was 1.8 percent of the applied atrazine. The 1996?98 average sediment yield was 610 pounds per acre per year. Sediment loads from the study area are associated with large storm events. Of the 45,300 tons of sediment transported from the study area during 1996?98 about 87 percent was transported during the three largest runoff events (April 1997, October 1997, and October 1998). Runoff-weighted average concentrations were computed for selected nutrients and pesticides. The 1996?98 runoff-weighted concentrations for total nitrogen and total phosphorus were 1.3 and 0.50 milligrams per liter, respectively. The 1996?98 runoff-weighted concentration for atrazine plus deethylatrazine was 2.7 micrograms per liter.

Interaction between the effects of evaporation rate and amount of simulated rainfall on development of the free-living stages of Haemonchus contortus.

PubMed

O'Connor, Lauren J; Kahn, Lewis P; Walkden-Brown, Stephen W

2008-08-17

A factorial experiment (3 x 4 x 2 x 3) was conducted in programmable incubators to investigate interaction between the effects of rainfall amount, rainfall distribution and evaporation rate on development of Haemonchus contortus to L3. Sheep faeces containing H. contortus eggs were incubated on sterilised soil under variable temperatures typical of summer in the Northern Tablelands of NSW, Australia. Simulated rainfall was applied in 1 of 3 amounts (12, 24 or 32 mm) and 4 distributions (a single event on the day after deposition, or the same total amount split in 2, 3 or 4 equal events over 2, 3 or 4 days, respectively). Samples were incubated at either a Low or High rate of evaporation (Low: 2.1-3.4 mm/day and High: 3.8-6.1 mm/day), and faeces and soil were destructively sampled at 4, 7 and 14 days post-deposition. Recovery of L3 from the soil (extra-pellet L3) increased over time (up to 0.52% at day 14) and with each increment of rainfall (12 mm: <0.01%; 24 mm: 0.10%; 32 mm: 0.45%) but was reduced under the High evaporation rate (0.01%) compared with the Low evaporation rate (0.31%). All rainfall amounts yielded significantly different recoveries of L3 under Low evaporation rates but there was no difference between the 12 and 24 mm treatments under the High evaporation rate. The distribution of simulated rainfall did not significantly affect recovery of infective larvae. Faecal moisture content was positively associated with L3 recovery, as was the ratio of cumulative precipitation and cumulative evaporation (P/E), particularly when measured in the first 4 days post-deposition. The results show that evaporation rate plays a significant role in regulating the influence of rainfall amount on the success of L3 transmission.

A hydro-mechanical framework for early warning of rainfall-induced landslides (Invited)

NASA Astrophysics Data System (ADS)

Godt, J.; Lu, N.; Baum, R. L.

2013-12-01

Landslide early warning requires an estimate of the location, timing, and magnitude of initial movement, and the change in volume and momentum of material as it travels down a slope or channel. In many locations advance assessment of landslide location, volume, and momentum is possible, but prediction of landslide timing entails understanding the evolution of rainfall and soil-water conditions, and consequent effects on slope stability in real time. Existing schemes for landslide prediction generally rely on empirical relations between landslide occurrence and rainfall amount and duration, however, these relations do not account for temporally variable rainfall nor the variably saturated processes that control the hydro-mechanical response of hillside materials to rainfall. Although limited by the resolution and accuracy of rainfall forecasts and now-casts in complex terrain and by the inherent difficulty in adequately characterizing subsurface materials, physics-based models provide a general means to quantitatively link rainfall and landslide occurrence. To obtain quantitative estimates of landslide potential from physics-based models using observed or forecasted rainfall requires explicit consideration of the changes in effective stress that result from changes in soil moisture and pore-water pressures. The physics that control soil-water conditions are transient, nonlinear, hysteretic, and dependent on material composition and history. In order to examine the physical processes that control infiltration and effective stress in variably saturated materials, we present field and laboratory results describing intrinsic relations among soil water and mechanical properties of hillside materials. At the REV (representative elementary volume) scale, the interaction between pore fluids and solid grains can be effectively described by the relation between soil suction, soil water content, hydraulic conductivity, and suction stress. We show that these relations can be obtained independently from outflow, shear strength, and deformation tests for a wide range of earth materials. We then compare laboratory results with measurements of pore pressure and moisture content from landslide-prone settings and demonstrate that laboratory results obtained for hillside materials are representative of field conditions. These fundamental relations provide a basis to combine observed or forecasted rainfall with in-situ measurements of soil water conditions using hydro-mechanical models that simulate transient variably saturated flow and slope stability. We conclude that early warning using an approach in which in-situ observations are used to establish initial conditions for hydro-mechanical models is feasible in areas of high landslide risk where laboratory characterization of materials is practical and accurate rainfall information can be obtained. Analogous to weather and climate forecasting, such models could then be applied in an ensemble fashion to obtain quantitative estimates of landslide probability and error. Application to broader regions likely awaits breakthroughs in the development of remotely sensed proxies of soil properties and subsurface moisture conditions.

Rainfall, Streamflow, and Water-Quality Data During Stormwater Monitoring, Halawa Stream Drainage Basin, Oahu, Hawaii, July 1, 2004 to June 30, 2005

USGS Publications Warehouse

Young, Stacie T.M.; Ball, Marcael T.J.

2005-01-01

Storm runoff water-quality samples were collected as part of the State of Hawaii Department of Transportation Stormwater Monitoring Program. This program is designed to assess the effects of highway runoff and urban runoff on Halawa Stream. For this program, rainfall data were collected at two stations, continuous streamflow data at two stations, and water-quality data at five stations, which include the two continuous streamflow stations. This report summarizes rainfall, streamflow, and water-quality data collected between July 1, 2004 and June 30, 2005. A total of 15 samples was collected over three storms during July 1, 2004 to June 30, 2005. In general, an attempt was made to collect grab samples nearly simultaneously at all five stations and flow-weighted time-composite samples at the three stations equipped with automatic samplers. However, all three storms were partially sampled because either not all stations were sampled or not all composite samples were collected. Samples were analyzed for total suspended solids, total dissolved solids, nutrients, chemical oxygen demand, and selected trace metals (cadmium, chromium, copper, lead, nickel, and zinc). Chromium and nickel were added to the analysis starting October 1, 2004. Grab samples were additionally analyzed for oil and grease, total petroleum hydrocarbons, fecal coliform, and biological oxygen demand. Quality-assurance/quality-control samples were also collected during storms and during routine maintenance to verify analytical procedures and check the effectiveness of equipment-cleaning procedures.

Applications of Polarimetric Radar to the Hydrometeorology of Urban Floods in St. Louis

NASA Astrophysics Data System (ADS)

Chaney, M. M.; Smith, J. A.; Baeck, M. L.

2017-12-01

Predicting and responding to flash flooding requires accurate spatial and temporal representation of rainfall rates. The polarimetric upgrade of all US radars has led to optimism about more accurate rainfall rate estimation from the NEXRAD network of WSR-88D radars in the US. Previous work has proposed different algorithms to do so, but significant uncertainties remain, especially for extreme short-term rainfall rates that control flash floods in urban settings. We will examine the relationship between radar rainfall estimates and gage rainfall rates for a catalog of 30 storms in St. Louis during the period of polarimetric radar measurements, 2012-2016. The storms are selected to provide a large sample of extreme rainfall measurements at the 15-minute to 3-hour time scale. A network of 100 rain gages and a lack of orographic or coastal effects make St. Louis an interesting location to study these relationships. A better understanding of the relationships between polarimetric radar measurements and gage rainfall rates will aid in refining polarimetric radar rainfall algorithms, in turn helping hydrometeorologists predict flash floods and other hazards associated with severe rainfall. Given the fact that St. Louis contains some of the flashiest watersheds in the United States (Smith and Smith, 2015), it is an especially important urban area in which to have accurate, real-time rainfall data. Smith, Brianne K, and James A Smith. "The Flashiest Watersheds in the Contiguous United States." American Meteorological Society (2015): 2365-2381. Web.

Bacterial content in runoff from simulated rainfall applied to plots amended with poultry litter

USDA-ARS?s Scientific Manuscript database

To evaluate potential bacterial runoff from poultry litter, litter was applied to test plots and exposed to simulated rainfall 1, 8 or 15 d after litter application. Runoff samples were tested for Salmonella and Campylobacter, two bacterial pathogens commonly associated with poultry, as well as com...

Rainfall intensity effects on removal of fecal indicator bacteria from solid dairy manure applied over grass-covered soil.

PubMed

Blaustein, Ryan A; Hill, Robert L; Micallef, Shirley A; Shelton, Daniel R; Pachepsky, Yakov A

2016-01-01

The rainfall-induced release of pathogens and microbial indicators from land-applied manure and their subsequent removal with runoff and infiltration precedes the impairment of surface and groundwater resources. It has been assumed that rainfall intensity and changes in intensity during rainfall do not affect microbial removal when expressed as a function of rainfall depth. The objective of this work was to test this assumption by measuring the removal of Escherichia coli, enterococci, total coliforms, and chloride ion from dairy manure applied in soil boxes containing fescue, under 3, 6, and 9cmh(-1) of rainfall. Runoff and leachate were collected at increasing time intervals during rainfall, and post-rainfall soil samples were taken at 0, 2, 5, and 10cm depths. Three kinetic-based models were fitted to the data on manure-constituent removal with runoff. Rainfall intensity appeared to have positive effects on rainwater partitioning to runoff, and removal with this effluent type occurred in two stages. While rainfall intensity generally did not impact the parameters of runoff-removal models, it had significant, inverse effects on the numbers of bacteria remaining in soil after rainfall. As rainfall intensity and soil profile depth increased, the numbers of indicator bacteria tended to decrease. The cumulative removal of E. coli from manure exceeded that of enterococci, especially in the form of removal with infiltration. This work may be used to improve the parameterization of models for bacteria removal with runoff and to advance estimations of depths of bacteria removal with infiltration, both of which are critical to risk assessment of microbial fate and transport in the environment. Published by Elsevier B.V.

Multistatic Array Sampling Scheme for Fast Near-Field Image Reconstruction

DTIC Science & Technology

2016-01-01

1 Multistatic Array Sampling Scheme for Fast Near-Field Image Reconstruction William F. Moulder, James D. Krieger, Denise T. Maurais-Galejs, Huy...described and validated experimentally with the formation of high quality microwave images. It is further shown that the scheme is more than two orders of... scheme (wherein transmitters and receivers are co-located) which require NTNR transmit-receive elements to achieve the same sampling. The second

Assessment of probabilistic areal reduction factors of precipitations for the entire French territory with gridded rainfall data.

NASA Astrophysics Data System (ADS)

Fouchier, Catherine; Maire, Alexis; Arnaud, Patrick; Cantet, Philippe; Odry, Jean

2016-04-01

The starting point of our study was the availability of maps of rainfall quantiles available for the entire French mainland territory at the spatial resolution of 1 km². These maps display the rainfall amounts estimated for different rainfall durations (from 15 minutes to 72 hours) and different return periods (from 2 years up to 1 000 years). They are provided by a regionalized stochastic hourly point rainfall generator, the SHYREG method which was previously developed by Irstea (Arnaud et al., 2007; Cantet and Arnaud, 2014). Being calibrated independently on numerous raingauges data (with an average density across the country of 1 raingauge per 200 km²), this method suffers from a limitation common to point-process rainfall generators: it can only reproduce point rainfall patterns and has no capacity to generate rainfall fields. It can't hence provide areal rainfall quantiles, the estimation of the latter being however needed for the construction of design rainfall or for the diagnostic of observed events. One means of bridging this gap between our local rainfall quantiles and areal rainfall quantiles is given by the concept of probabilistic areal reduction factors of rainfall (ARF) as defined by Omolayo (1993). This concept enables to estimate areal rainfall of a particular frequency within a certain amount of time from point rainfalls of the same frequency and duration. Assessing such ARF for the whole French territory is of particular interest since it should allow us to compute areal rainfall quantiles, and eventually watershed rainfall quantiles, by using the already available grids of statistical point rainfall of the SHYREG method. Our purpose was then to assess these ARF thanks to long time-series of spatial rainfall data. We have used two sets of rainfall fields: i) hourly rainfall fields from a 10-year reference database of Quantitative Precipitation Estimation (QPE) over France (Tabary et al., 2012), ii) daily rainfall fields resulting from a 53-year high-resolution atmospheric reanalysis over France with the SAFRAN-gauge-based analysis system (Vidal et al., 2010). We have then built samples of maximal rainfalls for each cell location (the "point" rainfalls) and for different areas centered on each cell location (the areal rainfalls) of these gridded data. To compute rainfall quantiles, we have fitted a Gumbel law, with the L-moment method, on each of these samples. Our daily and hourly ARF have then shown four main trends: i) a sensitivity to the return period, with ARF values decreasing when the return period increases; ii) a sensitivity to the rainfall duration, with ARF values decreasing when the rainfall duration decreases; iii) a sensitivity to the season, with ARF values smaller for the summer period than for the winter period; iv) a sensitivity to the geographical location, with low ARF values in the French Mediterranean area and ARF values close to 1 for the climatic zones of Northern and Western France (oceanic to semi-continental climate). The results of this data-intensive study led for the first time on the whole French territory are in agreement with studies led abroad (e.g. Allen and DeGaetano 2005, Overeem et al. 2010) and confirm and widen the results of previous studies that were carried out in France on smaller areas and with fewer rainfall durations (e.g. Ramos et al., 2006, Neppel et al., 2003). References Allen R. J. and DeGaetano A. T. (2005). Areal reduction factors for two eastern United States regions with high rain-gauge density. Journal of Hydrologic Engineering 10(4): 327-335. Arnaud P., Fine J.-A. and Lavabre J. (2007). An hourly rainfall generation model applicable to all types of climate. Atmospheric Research 85(2): 230-242. Cantet, P. and Arnaud, P. (2014). Extreme rainfall analysis by a stochastic model: impact of the copula choice on the sub-daily rainfall generation, Stochastic Environmental Research and Risk Assessment, Springer Berlin Heidelberg, 28(6), 1479-1492. Neppel L., Bouvier C. and Lavabre J. (2003). Areal reduction factor probabilities for rainfall in Languedoc Roussillon. IAHS-AISH Publication (278): 276-283. Omolayo, A. S. (1993). On the transposition of areal reduction factors for rainfall frequency estimation. Journal of Hydrology 145 (1-2): 191-205. Overeem A., Buishand T. A., Holleman I. and Uijlenhoet R. (2010). Extreme value modeling of areal rainfall from weather radar. Water Resources Research 46(9): 10 p. Ramos M.-H., Leblois E., Creutin J.-D. (2006). From point to areal rainfall: Linking the different approaches for the frequency characterisation of rainfalls in urban areas. Water Science and Technology. 54(6-7): 33-40. Tabary P., Dupuy P., L'Henaff G., Gueguen C., Moulin L., Laurantin O., Merlier C., Soubeyroux J. M. (2012). A 10-year (1997-2006) reanalysis of Quantitative Precipitation Estimation over France: methodology and first results. IAHS-AISH Publication (351) : 255-260. Vidal J.-P., Martin E., Franchistéguy L., Baillon M. and Soubeyroux J.-M. (2010). A 50-year high-resolution atmospheric reanalysis over France with the Safran system. International Journal of Climatology 30(11): 1627-1644.

A TRMM-Calibrated Infrared Technique for Global Rainfall Estimation

NASA Technical Reports Server (NTRS)

Negri, Andrew J.; Adler, Robert F.

2002-01-01

The development of a satellite infrared (IR) technique for estimating convective and stratiform rainfall and its application in studying the diurnal variability of rainfall on a global scale is presented. The Convective-Stratiform Technique (CST), calibrated by coincident, physically retrieved rain rates from the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR), is applied over the global tropics during 2001. The technique is calibrated separately over land and ocean, making ingenious use of the IR data from the TRMM Visible/Infrared Scanner (VIRS) before application to global geosynchronous satellite data. The low sampling rate of TRMM PR imposes limitations on calibrating IR-based techniques; however, our research shows that PR observations can be applied to improve IR-based techniques significantly by selecting adequate calibration areas and calibration length. The diurnal cycle of rainfall, as well as the division between convective and stratiform rainfall will be presented. The technique is validated using available data sets and compared to other global rainfall products such as Global Precipitation Climatology Project (GPCP) IR product, calibrated with TRMM Microwave Imager (TMI) data. The calibrated CST technique has the advantages of high spatial resolution (4 km), filtering of non-raining cirrus clouds, and the stratification of the rainfall into its convective and stratiform components, the latter being important for the calculation of vertical profiles of latent heating.

High-frequency DOC and nitrate measurements provide new insights into their export and their relationships to rainfall-runoff processes

NASA Astrophysics Data System (ADS)

Schwab, Michael; Klaus, Julian; Pfister, Laurent; Weiler, Markus

2015-04-01

Over the past decades, stream sampling protocols for environmental tracers were often limited by logistical and technological constraints. Long-term sampling programs would typically rely on weekly sampling campaigns, while high-frequency sampling would remain restricted to a few days or hours at best. We stipulate that the currently predominant sampling protocols are too coarse to capture and understand the full amplitude of rainfall-runoff processes and its relation to water quality fluctuations. Weekly sampling protocols are not suited to get insights into the hydrological system during high flow conditions. Likewise, high frequency measurements of a few isolated events do not allow grasping inter-event variability in contributions and processes. Our working hypothesis is based on the potential of a new generation of field-deployable instruments for measuring environmental tracers at high temporal frequencies over an extended period. With this new generation of instruments we expect to gain new insights into rainfall-runoff dynamics, both at intra- and inter-event scales. Here, we present the results of one year of DOC and nitrate measurements with the field deployable UV-Vis spectrometer spectro::lyser (scan Messtechnik GmbH). The instrument measures the absorption spectrum from 220 to 720 nm in situ and at high frequencies and derives DOC and nitrate concentrations. The measurements were carried out at 15 minutes intervals in the Weierbach catchment (0.47 km2) in Luxemburg. This fully forested catchment is characterized by cambisol soils and fractured schist as underlying bedrock. The time series of DOC and nitrate give insights into the high frequency dynamics of stream water. Peaks in DOC concentrations are closely linked to discharge peaks that occur during or right after a rainfall event. Those first discharge peaks can be linked to fast near surface runoff processes and are responsible for a remarkable amount of DOC export. A special characterisation of the Weierbach catchment are the delayed second peaks a few days after the rainfall event. Nitrate concentrations are following this second peak. We assume that this delayed response is going back to subsurface or upper groundwater flows, with nitrate enriched water. On an inter-event scale during low flow / base flow conditions, we observe interesting diurnal patterns of both DOC and nitrate concentrations. Overall, the long-term high-frequency measurements of DOC and nitrate provide us the opportunity to separate different rainfall-runoff processes and link the amount of DOC and nitrate export to them to quantify the overall relevance of the different processes.

Short-range prediction of a heavy precipitation event by assimilating Chinese CINRAD-SA radar reflectivity data using complex cloud analysis

NASA Astrophysics Data System (ADS)

Sheng, C.; Gao, S.; Xue, M.

2006-11-01

With the ARPS (Advanced Regional Prediction System) Data Analysis System (ADAS) and its complex cloud analysis scheme, the reflectivity data from a Chinese CINRAD-SA Doppler radar are used to analyze 3D cloud and hydrometeor fields and in-cloud temperature and moisture. Forecast experiments starting from such initial conditions are performed for a northern China heavy rainfall event to examine the impact of the reflectivity data and other conventional observations on short-range precipitation forecast. The full 3D cloud analysis mitigates the commonly known spin-up problem with precipitation forecast, resulting a significant improvement in precipitation forecast in the first 4 to 5 hours. In such a case, the position, timing and amount of precipitation are all accurately predicted. When the cloud analysis is used without in-cloud temperature adjustment, only the forecast of light precipitation within the first hour is improved. Additional analysis of surface and upper-air observations on the native ARPS grid, using the 1 degree real-time NCEP AVN analysis as the background, helps improve the location and intensity of rainfall forecasting slightly. Hourly accumulated rainfall estimated from radar reflectivity data is found to be less accurate than the model predicted precipitation when full cloud analysis is used.

Grid-cell-based crop water accounting for the famine early warning system

NASA Astrophysics Data System (ADS)

Verdin, James; Klaver, Robert

2002-06-01

Rainfall monitoring is a regular activity of food security analysts for sub-Saharan Africa due to the potentially disastrous impact of drought. Crop water accounting schemes are used to track rainfall timing and amounts relative to phenological requirements, to infer water limitation impacts on yield. Unfortunately, many rain gauge reports are available only after significant delays, and the gauge locations leave large gaps in coverage. As an alternative, a grid-cell-based formulation for the water requirement satisfaction index (WRSI) was tested for maize in Southern Africa. Grids of input variables were obtained from remote sensing estimates of rainfall, meteorological models, and digital soil maps. The spatial WRSI was computed for the 1996-97 and 1997-98 growing seasons. Maize yields were estimated by regression and compared with a limited number of reports from the field for the 1996-97 season in Zimbabwe. Agreement at a useful level (r = 0·80) was observed. This is comparable to results from traditional analysis with station data. The findings demonstrate the complementary role that remote sensing, modelling, and geospatial analysis can play in an era when field data collection in sub-Saharan Africa is suffering an unfortunate decline. Published in 2002 by John Wiley & Sons, Ltd.

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.

Rainfall and runoff quantity and quality characteristics of four urban land-use catchments in Fresno, California, October 1981 to April 1983

USGS Publications Warehouse

Oltmann, Richard N.; Shulters, Michael V.

1989-01-01

Rainfall and runoff quantity and quality were monitored for industrial, single-dwelling residential, multiple-dwelling residential, and commercial land-use catchments during the 1981-82 and 1982-83 rain seasons. Storm-composite rainfall and discrete run6ff samples were analyzed for numerous inorganic, biological, physical, and organic constituents. Atmospheric dry-deposition and street-surface particulate samples also were collected and analyzed. With the exception of the industrial catchment, the highest runoff concentrations for most constituents occurred during the initial storm runoff and then decreased throughout the remainder of the storm, independent of hydraulic conditions. Metal concentrations were high during initial runoff, but also increased as flow increased. Constituent concentrations for the industrial catchment fluctuated greatly during storms. Statistical tests showed higher ammonia plus organic nitrogen, ammonia, pH, and phenol concentrations in rainfall at the industrial site than at the single-dwelling residential and laboratory sites. Statistical testing of runoff quality data showed higher concentrations for the industrial catchment than for the two residential and commercial catchments for most constituents. Total recoverable lead was one of the few constituents that had lower concentrations for the industrial catchment than for the other three catchments. The two residential catchments showed no significant difference in runoff concentrations for 50 of the 57 constituents used in the statistical analysis. The commercial catchment runoff concentrations for most constituents generally were similar to the residential catchments. Although constituent concentrations generally were higher for the industrial catchment than for the commercial catchment, constituent storm loads from the commercial catchment were similar to the industrial catchment because of the greater runoff volume from the highly impervious commercial catchment. Between 10 and 50 percent of the constituent runoff loads for the two residential catchments were attributed to the rainfall load, with the percentages generally considerably less for the industrial catchment. Event mean concentrations (EMC) for most constituents for all but the industrial catchment were highest for the first two or three storms of the rain season after which they became almost constant. Constituent event mean concentrations for the industrial catchment generally did not show any pattern throughout a rain season. Multiple-regression predictor equations for event mean concentrations were developed for several constituents for all sites. Average annual constituent unit loads were computed for 18 constituents for each catchment. The organophosphorus compounds, diazinon, malathion, and parathion were the most prevalent pesticides detected in rainfall. Diazinon was detected in all 54 rainfall samples. Parathion and malathion were detected in 49 and 50 samples, respectively. Other pesticides detected in rainfall included chlordane, lindane, methoxychlor, endosulfan, and 2,4-D. Of these, only methoxychlor and endosulfan were not consistently detected in runoff.

A mesoscale hybrid data assimilation system based on the JMA nonhydrostatic model

NASA Astrophysics Data System (ADS)

Ito, K.; Kunii, M.; Kawabata, T. T.; Saito, K. K.; Duc, L. L.

2015-12-01

This work evaluates the potential of a hybrid ensemble Kalman filter and four-dimensional variational (4D-Var) data assimilation system for predicting severe weather events from a deterministic point of view. This hybrid system is an adjoint-based 4D-Var system using a background error covariance matrix constructed from the mixture of a so-called NMC method and perturbations in a local ensemble transform Kalman filter data assimilation system, both of which are based on the Japan Meteorological Agency nonhydrostatic model. To construct the background error covariance matrix, we investigated two types of schemes. One is a spatial localization scheme and the other is neighboring ensemble approach, which regards the result at a horizontally spatially shifted point in each ensemble member as that obtained from a different realization of ensemble simulation. An assimilation of a pseudo single-observation located to the north of a tropical cyclone (TC) yielded an analysis increment of wind and temperature physically consistent with what is expected for a mature TC in both hybrid systems, whereas an analysis increment in a 4D-Var system using a static background error covariance distorted a structure of the mature TC. Real data assimilation experiments applied to 4 TCs and 3 local heavy rainfall events showed that hybrid systems and EnKF provided better initial conditions than the NMC-based 4D-Var, both for predicting the intensity and track forecast of TCs and for the location and amount of local heavy rainfall events.

The Impact of Aerosols on Cloud and Precipitation Processes: Cloud-Resolving Model Simulations

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Li, X.; Khain, A.; Simpson, S.; Johnson, D.; Remer, L.

2004-01-01

Cloud microphysics is inevitably affected by the smoke particle (CCN, cloud condensation nuclei) size distributions below the clouds. Therefore, size distributions parameterized as spectral bin microphysics are needed to explicitly study the effects of atmospheric aerosol concentration on cloud development, rainfall production, and rainfall rates for convective clouds. Recently, two detailed spectral-bin microphysical schemes were implemented into the Goddard Cumulus Ensembel (GCE) model. The formulation for the explicit spectral-bin microphysical processes is based on solving stochastic kinetic equations for the size distribution functions of water droplets (i.e., cloud droplets and raindrops), and several types of ice particles [i.e. pristine ice crystals (columnar and plate-like), snow (dendrites and aggregates), graupel and frozen drops/hail]. Each type is described by a special size distribution function containing many categories (i.e. 33 bins). Atmospheric aerosols are also described using number density size distribution functions. A spectral-bin microphysical model is very expensive from a computational point of view and has only been implemented into the 2D version of the GCE at the present time. The model is tested by studying the evolution of deep tropical clouds in the west Pacific warm pool region and in the mid-latitude continent with different concentrations of CCN: a low "c1ean"concentration and a high "dirty" concentration. In addition, differences and similarities between bulk microphysics and spectral-bin microphysical schemes will be examined and discussed.

Effect of different sampling schemes on the spatial placement of conservation reserves in Utah, USA

USGS Publications Warehouse

Bassett, S.D.; Edwards, T.C.

2003-01-01

We evaluated the effect of three different sampling schemes used to organize spatially explicit biological information had on the spatial placement of conservation reserves in Utah, USA. The three sampling schemes consisted of a hexagon representation developed by the EPA/EMAP program (statistical basis), watershed boundaries (ecological), and the current county boundaries of Utah (socio-political). Four decision criteria were used to estimate effects, including amount of area, length of edge, lowest number of contiguous reserves, and greatest number of terrestrial vertebrate species covered. A fifth evaluation criterion was the effect each sampling scheme had on the ability of the modeled conservation reserves to cover the six major ecoregions found in Utah. Of the three sampling schemes, county boundaries covered the greatest number of species, but also created the longest length of edge and greatest number of reserves. Watersheds maximized species coverage using the least amount of area. Hexagons and watersheds provide the least amount of edge and fewest number of reserves. Although there were differences in area, edge and number of reserves among the sampling schemes, all three schemes covered all the major ecoregions in Utah and their inclusive biodiversity. ?? 2003 Elsevier Science Ltd. All rights reserved.

The soiling of materials in the ambient atmosphere

NASA Astrophysics Data System (ADS)

Hamilton, R. S.; Mansfield, T. A.

Models describing the rate of soiling of exposed surfaces due to the deposition and accumulation of particulate matter from the atmosphere are reviewed. Samples of white painted wood were exposed for 110 days in the ambient atmosphere. Separate samples were sheltered and unsheltered from rainfall. Reflectance was measured daily. Results are compared with recently published studies in the U.S.A. (samples in the ambient atmosphere) and the U.K. (samples in a road tunnel). Experimental soiling rates were compared with predicted values. Existing models were satisfactory for predicting soiling in a tunnel but underestimated soiling in an ambient situation; a revised formulation is proposed for this situation. Rainfall generally produced a cleaning effect but redistribution of washed-off material could produce enhanced soiling.

40 CFR 761.316 - Interpreting PCB concentration measurements resulting from this sampling scheme.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 40 Protection of Environment 32 2013-07-01 2013-07-01 false Interpreting PCB concentration measurements resulting from this sampling scheme. 761.316 Section 761.316 Protection of Environment... scheme. (a) For an individual sample taken from an approximately 1 meter square portion of the entire...

The Impact of Sampling Schemes on the Site Frequency Spectrum in Nonequilibrium Subdivided Populations

PubMed Central

Städler, Thomas; Haubold, Bernhard; Merino, Carlos; Stephan, Wolfgang; Pfaffelhuber, Peter

2009-01-01

Using coalescent simulations, we study the impact of three different sampling schemes on patterns of neutral diversity in structured populations. Specifically, we are interested in two summary statistics based on the site frequency spectrum as a function of migration rate, demographic history of the entire substructured population (including timing and magnitude of specieswide expansions), and the sampling scheme. Using simulations implementing both finite-island and two-dimensional stepping-stone spatial structure, we demonstrate strong effects of the sampling scheme on Tajima's D (DT) and Fu and Li's D (DFL) statistics, particularly under specieswide (range) expansions. Pooled samples yield average DT and DFL values that are generally intermediate between those of local and scattered samples. Local samples (and to a lesser extent, pooled samples) are influenced by local, rapid coalescence events in the underlying coalescent process. These processes result in lower proportions of external branch lengths and hence lower proportions of singletons, explaining our finding that the sampling scheme affects DFL more than it does DT. Under specieswide expansion scenarios, these effects of spatial sampling may persist up to very high levels of gene flow (Nm > 25), implying that local samples cannot be regarded as being drawn from a panmictic population. Importantly, many data sets on humans, Drosophila, and plants contain signatures of specieswide expansions and effects of sampling scheme that are predicted by our simulation results. This suggests that validating the assumption of panmixia is crucial if robust demographic inferences are to be made from local or pooled samples. However, future studies should consider adopting a framework that explicitly accounts for the genealogical effects of population subdivision and empirical sampling schemes. PMID:19237689

Deterministic multidimensional nonuniform gap sampling.

PubMed

Worley, Bradley; Powers, Robert

2015-12-01

Born from empirical observations in nonuniformly sampled multidimensional NMR data relating to gaps between sampled points, the Poisson-gap sampling method has enjoyed widespread use in biomolecular NMR. While the majority of nonuniform sampling schemes are fully randomly drawn from probability densities that vary over a Nyquist grid, the Poisson-gap scheme employs constrained random deviates to minimize the gaps between sampled grid points. We describe a deterministic gap sampling method, based on the average behavior of Poisson-gap sampling, which performs comparably to its random counterpart with the additional benefit of completely deterministic behavior. We also introduce a general algorithm for multidimensional nonuniform sampling based on a gap equation, and apply it to yield a deterministic sampling scheme that combines burst-mode sampling features with those of Poisson-gap schemes. Finally, we derive a relationship between stochastic gap equations and the expectation value of their sampling probability densities. Copyright © 2015 Elsevier Inc. All rights reserved.

Estimating the timing and location of shallow rainfall-induced landslides using a model for transient, unsaturated infiltration

USGS Publications Warehouse

Baum, Rex L.; Godt, Jonathan W.; Savage, William Z.

2010-01-01

Shallow rainfall-induced landslides commonly occur under conditions of transient infiltration into initially unsaturated soils. In an effort to predict the timing and location of such landslides, we developed a model of the infiltration process using a two-layer system that consists of an unsaturated zone above a saturated zone and implemented this model in a geographic information system (GIS) framework. The model links analytical solutions for transient, unsaturated, vertical infiltration above the water table to pressure-diffusion solutions for pressure changes below the water table. The solutions are coupled through a transient water table that rises as water accumulates at the base of the unsaturated zone. This scheme, though limited to simplified soil-water characteristics and moist initial conditions, greatly improves computational efficiency over numerical models in spatially distributed modeling applications. Pore pressures computed by these coupled models are subsequently used in one-dimensional slope-stability computations to estimate the timing and locations of slope failures. Applied over a digital landscape near Seattle, Washington, for an hourly rainfall history known to trigger shallow landslides, the model computes a factor of safety for each grid cell at any time during a rainstorm. The unsaturated layer attenuates and delays the rainfall-induced pore-pressure response of the model at depth, consistent with observations at an instrumented hillside near Edmonds, Washington. This attenuation results in realistic estimates of timing for the onset of slope instability (7 h earlier than observed landslides, on average). By considering the spatial distribution of physical properties, the model predicts the primary source areas of landslides.

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.

Detecting causal drivers and empirical prediction of the Indian Summer Monsoon

NASA Astrophysics Data System (ADS)

Di Capua, G.; Vellore, R.; Raghavan, K.; Coumou, D.

2017-12-01

The Indian summer monsoon (ISM) is crucial for the economy, society and natural ecosystems on the Indian peninsula. Predict the total seasonal rainfall at several months lead time would help to plan effective water management strategies, improve flood or drought protection programs and prevent humanitarian crisis. However, the complexity and strong internal variability of the ISM circulation system make skillful seasonal forecasting challenging. Moreover, to adequately identify the low-frequency, and far-away processes which influence ISM behavior novel tools are needed. We applied a Response-Guided Causal Precursor Detection (RGCPD) scheme, which is a novel empirical prediction method which unites a response-guided community detection scheme with a causal discovery algorithm (CEN). These tool allow us to assess causal pathways between different components of the ISM circulation system and with far-away regions in the tropics, mid-latitudes or Arctic. The scheme has successfully been used to identify causal precursors of the Stratospheric polar vortex enabling skillful predictions at (sub) seasonal timescales (Kretschmer et al. 2016, J.Clim., Kretschmer et al. 2017, GRL). We analyze observed ISM monthly rainfall over the monsoon trough region. Applying causal discovery techniques, we identify several causal precursor communities in the fields of 2m-temperature, sea level pressure and snow depth over Eurasia. Specifically, our results suggest that surface temperature conditions in both tropical and Arctic regions contribute to ISM variability. A linear regression prediction model based on the identified set of communities has good hindcasting skills with 4-5 months lead times. Further we separate El Nino, La Nina and ENSO-neutral years from each other and find that the causal precursors are different dependent on ENSO state. The ENSO-state dependent causal precursors give even higher skill, especially for La Nina years when the ISM is relatively strong. These findings are promising results that might ultimately contribute to both improved understanding of the ISM circulation system and help improving seasonal ISM forecasts.

Moored rainfall measurements during COARE

NASA Technical Reports Server (NTRS)

Mcphaden, Michael J.

1994-01-01

This presentation discusses mini-ORG rainfall estimates collected from an array of six moornings in the western equatorial Pacific during the TOGA-COARE experiment. The moorings were clustered in the vicinity of the COARE intensive flux array (IFA) centered near 2 deg S, 156 deg E. The basic data set consisted of hourly means computed from 5-second samples.

Effect of uncertainties on probabilistic-based design capacity of hydrosystems

NASA Astrophysics Data System (ADS)

Tung, Yeou-Koung

2018-02-01

Hydrosystems engineering designs involve analysis of hydrometric data (e.g., rainfall, floods) and use of hydrologic/hydraulic models, all of which contribute various degrees of uncertainty to the design process. Uncertainties in hydrosystem designs can be generally categorized into aleatory and epistemic types. The former arises from the natural randomness of hydrologic processes whereas the latter are due to knowledge deficiency in model formulation and model parameter specification. This study shows that the presence of epistemic uncertainties induces uncertainty in determining the design capacity. Hence, the designer needs to quantify the uncertainty features of design capacity to determine the capacity with a stipulated performance reliability under the design condition. Using detention basin design as an example, the study illustrates a methodological framework by considering aleatory uncertainty from rainfall and epistemic uncertainties from the runoff coefficient, curve number, and sampling error in design rainfall magnitude. The effects of including different items of uncertainty and performance reliability on the design detention capacity are examined. A numerical example shows that the mean value of the design capacity of the detention basin increases with the design return period and this relation is found to be practically the same regardless of the uncertainty types considered. The standard deviation associated with the design capacity, when subject to epistemic uncertainty, increases with both design frequency and items of epistemic uncertainty involved. It is found that the epistemic uncertainty due to sampling error in rainfall quantiles should not be ignored. Even with a sample size of 80 (relatively large for a hydrologic application) the inclusion of sampling error in rainfall quantiles resulted in a standard deviation about 2.5 times higher than that considering only the uncertainty of the runoff coefficient and curve number. Furthermore, the presence of epistemic uncertainties in the design would result in under-estimation of the annual failure probability of the hydrosystem and has a discounting effect on the anticipated design return period.

Rapid evaluation of high-performance systems

NASA Astrophysics Data System (ADS)

Forbes, G. W.; Ruoff, J.

2017-11-01

System assessment for design often involves averages, such as rms wavefront error, that are estimated by ray tracing through a sample of points within the pupil. Novel general-purpose sampling and weighting schemes are presented and it is also shown that optical design can benefit from tailored versions of these schemes. It turns out that the type of Gaussian quadrature that has long been recognized for efficiency in this domain requires about 40-50% more ray tracing to attain comparable accuracy to generic versions of the new schemes. Even greater efficiency gains can be won, however, by tailoring such sampling schemes to the optical context where azimuthal variation in the wavefront is generally weaker than the radial variation. These new schemes are special cases of what is known in the mathematical world as cubature. Our initial results also led to the consideration of simpler sampling configurations that approximate the newfound cubature schemes. We report on the practical application of a selection of such schemes and make observations that aid in the discovery of novel cubature schemes relevant to optical design of systems with circular pupils.

[Hydrology and pollution characteristics of urban runoff: Beijing as a sample].

PubMed

Dong, Xin; Du, Peng-Fei; Li, Zhi-Yi; Yu, Zheng-Rong; Wang, Rui; Huang, Jin-Liang

2008-03-01

The purpose of this study is identification and characterization of hydrological process of urban runoff, as well as concentration variation of pollutants in it. Samples were collected in 4 rainfall events in Beijing from Jun. 2006 to Aug. 2006. Hydrology and pollution of the rainfall-runoff process were analyzed on roof and road. Study results show that the shapes of hydrological curves of runoff, despite for a 5 - 20 min delay and a milder tendency, are similar to rainfall curves. Runoff coefficients of roof are 0.80 - 0.98, while 0.87 - 0.97 of road. Event mean concentrations (EMC) of pollutants are influenced by build-up and wash-off features, which leads to a higher concentration in road runoff than in roof runoff. Major pollutants that excess the water quality standards are COD, TN, and TP. Evident correlations (> 0.1) are found between pollutants. Correlation with particles are higher for COD and SO4(2-) (> 0.5), while lower for nutrients (<0.5). First flush effects (FFE) are found and affected by several factors, such as pollutant variety, types of land covers, and rainfall intensity. FFE are found more intense in SS, more frequently in road runoff, and more difficult to form for COD and nutrients with low rainfall intensity. Therefore, control of first period of runoff would be an effective approach for runoff management in Beijing.

SPECIAL SESSION: (H21) on Global Precipitation Mission for Hydrology and Hydrometeorology. Sampling-Error Considerations for GPM-Era Rainfall Products

NASA Technical Reports Server (NTRS)

Bell, Thomas L.; Lau, William K. M. (Technical Monitor)

2002-01-01

The proposed Global Precipitation Mission (GPM) builds on the success of the Tropical Rainfall Measuring Mission (TRMM), offering a constellation of microwave-sensor-equipped smaller satellites in addition to a larger, multiply-instrumented "mother" satellite that will include an improved precipitation radar system to which the precipitation estimates of the smaller satellites can be tuned. Coverage by the satellites will be nearly global rather than being confined as TRMM was to lower latitudes. It is hoped that the satellite constellation can provide observations at most places on the earth at least once every three hours, though practical considerations may force some compromises. The GPM system offers the possibility of providing precipitation maps with much better time resolution than the monthly averages around which TRMM was planned, and therefore opens up new possibilities for hydrology and data assimilation into models. In this talk, methods that were developed for estimating sampling error in the rainfall averages that TRMM is providing will be used to estimate sampling error levels for GPM-era configurations. Possible impacts on GPM products of compromises in the sampling frequency will be discussed.

Effects of flow regime on metal concentrations and the attainment of water quality standards in a remediated stream reach, Butte, Montana

USGS Publications Warehouse

Runkel, Robert L.; Kimball, Briant A.; Nimick, David A.; Walton-Day, Katherine

2016-01-01

Low-flow synoptic sampling campaigns are often used as the primary tool to characterize watersheds affected by mining. Although such campaigns are an invaluable part of site characterization, investigations which focus solely on low-flow conditions may yield misleading results. The objective of this paper is to demonstrate this point and elucidate the mechanisms responsible for the release of metals during rainfall runoff. This objective is addressed using data from diel and synoptic sampling campaigns conducted over a two-day period. Low-flow synoptic sampling results indicate that concentrations of most constituents meet aquatic standards. This finding is in contrast to findings from a diel sampling campaign that captured dramatic increases in concentrations during rainfall runoff. Concentrations during the rising limb of the hydrograph were 2–23 times concentrations observed during synoptic sampling (most increases were >10-fold), remaining elevated during the receding limb of the hydrograph to produce a clockwise hysteresis loop. Hydrologic mechanisms responsible for the release of metals include increased transport due to resuspension of streambed solids, erosion of alluvial tailings, and overland flow. Rainfall also elevated the alluvial groundwater table and increased infiltration through the vadose zone, likely resulting in dissolution from alluvial tailings that were dry prior to the event.

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.

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

NASA Astrophysics Data System (ADS)

Chappell, Adrian; Agnew, Clive T.

2008-04-01

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

A Novel, Simplified Scheme for Plastics Identification: "JCE" Classroom Activity 104

ERIC Educational Resources Information Center

Harris, Mary E.; Walker, Barbara

2010-01-01

In this Activity, students identify samples of seven types of recyclable plastic by using a flowchart scheme. The flowchart procedure includes making density comparisons of the plastic samples in water and alcohol and observing physical changes of plastic samples subjected to boiling water temperatures and exposure to acetone. This scheme is…

Coupling of Community Land Model with RegCM4 for Indian Summer Monsoon Simulation

NASA Astrophysics Data System (ADS)

Maurya, R. K. S.; Sinha, P.; Mohanty, M. R.; Mohanty, U. C.

2017-11-01

Three land surface schemes available in the regional climate model RegCM4 have been examined to understand the coupling between land and atmosphere for simulation of the Indian summer monsoon rainfall. The RegCM4 is coupled with biosphere-atmosphere transfer scheme (BATS) and the National Center for Atmospheric Research (NCAR) Community Land Model versions 3.5, and 4.5 (CLM3.5 and CLM4.5, respectively) and model performance is evaluated for recent drought (2009) and normal (2011) monsoon years. The CLM4.5 has a more distinct category of surface and it is capable of representing better the land surface characteristics. National Centers for Environmental Prediction (NCEP) and Department of Energy (DOE) reanalysis version 2 (NNRP2) datasets are considered as driving force to conduct the experiments for the Indian monsoon region (30°E-120°E; 30°S-50°N). The NNRP2 and India Meteorological Department (IMD) gridded precipitation data are used for verification analysis. The results indicate that RegCM4 simulations with CLM4.5 (RegCM4-CLM4.5) and CLM3.5 (RegCM4-CLM3.5) surface temperature (at 2 ms) have very low warm biases ( 1 °C), while with BATS (RegCM4-BATS) has a cold bias of about 1-3 °C in peninsular India and some parts of central India. Warm bias in the RegCM4-BATS is observed over the Indo-Gangetic plain and northwest India and the bias is more for the deficit year as compared to the normal year. However, the warm (cold) bias is less in RegCM4-CLM4.5 than other schemes for both the deficit and normal years. The model-simulated maximum (minimum) surface temperature and sensible heat flux at the surface are positively (negatively) biased in all the schemes; however, the bias is higher in RegCM4-BATS and lower in RegCM4-CLM4.5 over India. All the land surface schemes overestimated the precipitation in peninsular India and underestimated in central parts of India for both the years; however, the biases are less in RegCM4-CLM4.5 and more in RegCM4-CLM3.5 and RegCM4-BATS. During both the years, BATS scheme in RegCM4 failed to represent low precipitation over the leeward than windward side of the Western Ghats, while CLM schemes (both versions) in the RegCM4 are able to depict this feature. In the topographic regions, such as the Western Ghats, northeast India and state of Jammu and Kashmir, RegCM4-BATS overestimates the rainfall amount with higher bias. Statistical analysis using anomaly correlation coefficient, root mean square error, equitable threat score, and critical success index confirms that RegCM4-CLM performs better than RegCM4-BATS in the simulation of the Indian summer monsoon.

Early Results from the Global Precipitation Measurement (GPM) Mission in Japan

NASA Astrophysics Data System (ADS)

Kachi, Misako; Kubota, Takuji; Masaki, Takeshi; Kaneko, Yuki; Kanemaru, Kaya; Oki, Riko; Iguchi, Toshio; Nakamura, Kenji; Takayabu, Yukari N.

2015-04-01

The Global Precipitation Measurement (GPM) mission is an international collaboration to achieve highly accurate and highly frequent global precipitation observations. The GPM mission consists of the GPM Core Observatory jointly developed by U.S. and Japan and Constellation Satellites that carry microwave radiometers and provided by the GPM partner agencies. The Dual-frequency Precipitation Radar (DPR) was developed by the Japan Aerospace Exploration Agency (JAXA) and the National Institute of Information and Communications Technology (NICT), and installed on the GPM Core Observatory. The GPM Core Observatory chooses a non-sun-synchronous orbit to carry on diurnal cycle observations of rainfall from the Tropical Rainfall Measuring Mission (TRMM) satellite and was successfully launched at 3:37 a.m. on February 28, 2014 (JST), while the Constellation Satellites, including JAXA's Global Change Observation Mission (GCOM) - Water (GCOM-W1) or "SHIZUKU," are launched by each partner agency sometime around 2014 and contribute to expand observation coverage and increase observation frequency JAXA develops the DPR Level 1 algorithm, and the NASA-JAXA Joint Algorithm Team develops the DPR Level 2 and DPR-GMI combined Level2 algorithms. JAXA also develops the Global Rainfall Map (GPM-GSMaP) algorithm, which is a latest version of the Global Satellite Mapping of Precipitation (GSMaP), as national product to distribute hourly and 0.1-degree horizontal resolution rainfall map. Major improvements in the GPM-GSMaP algorithm is; 1) improvements in microwave imager algorithm based on AMSR2 precipitation standard algorithm, including new land algorithm, new coast detection scheme; 2) Development of orographic rainfall correction method for warm rainfall in coastal area (Taniguchi et al., 2012); 3) Update of database, including rainfall detection over land and land surface emission database; 4) Development of microwave sounder algorithm over land (Kida et al., 2012); and 5) Development of gauge-calibrated GSMaP algorithm (Ushio et al., 2013). In addition to those improvements in the algorithms number of passive microwave imagers and/or sounders used in the GPM-GSMaP was increased compared to the previous version. After the early calibration and validation of the products and evaluation that all products achieved the release criteria, all GPM standard products and the GPM-GSMaP product has been released to the public since September 2014. The GPM products can be downloaded via the internet through the JAXA G-Portal (https://www.gportal.jaxa.jp).

Predictive performance of rainfall thresholds for shallow landslides in Switzerland from gridded daily data

NASA Astrophysics Data System (ADS)

Leonarduzzi, Elena; Molnar, Peter; McArdell, Brian W.

2017-08-01

A high-resolution gridded daily precipitation data set was combined with a landslide inventory containing over 2000 events in the period 1972-2012 to analyze rainfall thresholds which lead to landsliding in Switzerland. We colocated triggering rainfall to landslides, developed distributions of triggering and nontriggering rainfall event properties, and determined rainfall thresholds and intensity-duration ID curves and validated their performance. The best predictive performance was obtained by the intensity-duration ID threshold curve, followed by peak daily intensity Imax and mean event intensity Imean. Event duration by itself had very low predictive power. A single country-wide threshold of Imax = 28 mm/d was extended into space by regionalization based on surface erodibility and local climate (mean daily precipitation). It was found that wetter local climate and lower erodibility led to significantly higher rainfall thresholds required to trigger landslides. However, we showed that the improvement in model performance due to regionalization was marginal and much lower than what can be achieved by having a high-quality landslide database. Reference cases in which the landslide locations and timing were randomized and the landslide sample size was reduced showed the sensitivity of the Imax rainfall threshold model. Jack-knife and cross-validation experiments demonstrated that the model was robust. The results reported here highlight the potential of using rainfall ID threshold curves and rainfall threshold values for predicting the occurrence of landslides on a country or regional scale with possible applications in landslide warning systems, even with daily data.

Ancient numerical daemons of conceptual hydrological modeling: 1. Fidelity and efficiency of time stepping schemes

NASA Astrophysics Data System (ADS)

Clark, Martyn P.; Kavetski, Dmitri

2010-10-01

A major neglected weakness of many current hydrological models is the numerical method used to solve the governing model equations. This paper thoroughly evaluates several classes of time stepping schemes in terms of numerical reliability and computational efficiency in the context of conceptual hydrological modeling. Numerical experiments are carried out using 8 distinct time stepping algorithms and 6 different conceptual rainfall-runoff models, applied in a densely gauged experimental catchment, as well as in 12 basins with diverse physical and hydroclimatic characteristics. Results show that, over vast regions of the parameter space, the numerical errors of fixed-step explicit schemes commonly used in hydrology routinely dwarf the structural errors of the model conceptualization. This substantially degrades model predictions, but also, disturbingly, generates fortuitously adequate performance for parameter sets where numerical errors compensate for model structural errors. Simply running fixed-step explicit schemes with shorter time steps provides a poor balance between accuracy and efficiency: in some cases daily-step adaptive explicit schemes with moderate error tolerances achieved comparable or higher accuracy than 15 min fixed-step explicit approximations but were nearly 10 times more efficient. From the range of simple time stepping schemes investigated in this work, the fixed-step implicit Euler method and the adaptive explicit Heun method emerge as good practical choices for the majority of simulation scenarios. In combination with the companion paper, where impacts on model analysis, interpretation, and prediction are assessed, this two-part study vividly highlights the impact of numerical errors on critical performance aspects of conceptual hydrological models and provides practical guidelines for robust numerical implementation.

Rainfall, Streamflow, and Water-Quality Data During Stormwater Monitoring, Halawa Stream Drainage Basin, Oahu, Hawaii, July 1, 2005 to June 30, 2006

USGS Publications Warehouse

Presley, Todd K.; Jamison, Marcael T.J.; Young-Smith, Stacie T. M.

2006-01-01

Storm runoff water-quality samples were collected as part of the State of Hawaii Department of Transportation Stormwater Monitoring Program. This program is designed to assess the effects of highway runoff and urban runoff on Halawa Stream. For this program, rainfall data were collected at two stations, continuous discharge data at one station, continuous streamflow data at two stations, and water-quality data at five stations, which include the continuous discharge and streamflow stations. This report summarizes rainfall, discharge, streamflow, and water-quality data collected between July 1, 2005 and June 30, 2006. A total of 23 samples was collected over five storms during July 1, 2005 to June 30, 2006. The goal was to collect grab samples nearly simultaneously at all five stations, and flow-weighted time-composite samples at the three stations equipped with automatic samplers; however, all five storms were partially sampled owing to lack of flow at the time of sampling at some sites, or because some samples collected by the automatic sampler did not represent water from the storm. Samples were analyzed for total suspended solids, total dissolved solids, nutrients, chemical oxygen demand, and selected trace metals (cadmium, chromium, copper, lead, nickel, and zinc). Additionally, grab samples were analyzed for oil and grease, total petroleum hydrocarbons, fecal coliform, and biological oxygen demand. Quality-assurance/quality-control samples were also collected during storms and during routine maintenance to verify analytical procedures and check the effectiveness of equipment-cleaning procedures.

How predictable is the anomaly pattern of the Indian summer rainfall?

NASA Astrophysics Data System (ADS)

Li, Juan; Wang, Bin

2016-05-01

Century-long efforts have been devoted to seasonal forecast of Indian summer monsoon rainfall (ISMR). Most studies of seasonal forecast so far have focused on predicting the total amount of summer rainfall averaged over the entire India (i.e., all Indian rainfall index-AIRI). However, it is practically more useful to forecast anomalous seasonal rainfall distribution (anomaly pattern) across India. The unknown science question is to what extent the anomalous rainfall pattern is predictable. This study attempted to address this question. Assessment of the 46-year (1960-2005) hindcast made by the five state-of-the-art ENSEMBLE coupled dynamic models' multi-model ensemble (MME) prediction reveals that the temporal correlation coefficient (TCC) skill for prediction of AIRI is 0.43, while the area averaged TCC skill for prediction of anomalous rainfall pattern is only 0.16. The present study aims to estimate the predictability of ISMR on regional scales by using Predictable Mode Analysis method and to develop a set of physics-based empirical (P-E) models for prediction of ISMR anomaly pattern. We show that the first three observed empirical orthogonal function (EOF) patterns of the ISMR have their distinct dynamical origins rooted in an eastern Pacific-type La Nina, a central Pacific-type La Nina, and a cooling center near dateline, respectively. These equatorial Pacific sea surface temperature anomalies, while located in different longitudes, can all set up a specific teleconnection pattern that affects Indian monsoon and results in different rainfall EOF patterns. Furthermore, the dynamical models' skill for predicting ISMR distribution primarily comes primarily from these three modes. Therefore, these modes can be regarded as potentially predictable modes. If these modes are perfectly predicted, about 51 % of the total observed variability is potentially predictable. Based on understanding the lead-lag relationships between the lower boundary anomalies and the predictable modes, a set of P-E models is established to predict the principal component of each predictable mode, so that the ISMR anomaly pattern can be predicted by using the sum of the predictable modes. Three validation schemes are used to assess the performance of the P-E models' hindcast and independent forecast. The validated TCC skills of the P-E model here are more than doubled that of dynamical models' MME hindcast, suggesting a large room for improvement of the current dynamical prediction. The methodology proposed here can be applied to a wide range of climate prediction and predictability studies. The limitation and future improvement are also discussed.

A TRMM-Calibrated Infrared Technique for Global Rainfall Estimation

NASA Technical Reports Server (NTRS)

Negri, Andrew J.; Adler, Robert F.; Xu, Li-Ming

2003-01-01

This paper presents the development of a satellite infrared (IR) technique for estimating convective and stratiform rainfall and its application in studying the diurnal variability of rainfall on a global scale. The Convective-Stratiform Technique (CST), calibrated by coincident, physically retrieved rain rates from the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR), is applied over the global tropics during summer 2001. The technique is calibrated separately over land and ocean, making ingenious use of the IR data from the TRMM Visible/Infrared Scanner (VIRS) before application to global geosynchronous satellite data. The low sampling rate of TRMM PR imposes limitations on calibrating IR- based techniques; however, our research shows that PR observations can be applied to improve IR-based techniques significantly by selecting adequate calibration areas and calibration length. The diurnal cycle of rainfall, as well as the division between convective and t i f m rainfall will be presented. The technique is validated using available data sets and compared to other global rainfall products such as Global Precipitation Climatology Project (GPCP) IR product, calibrated with TRMM Microwave Imager (TMI) data. The calibrated CST technique has the advantages of high spatial resolution (4 km), filtering of non-raining cirrus clouds, and the stratification of the rainfall into its convective and stratiform components, the latter being important for the calculation of vertical profiles of latent heating.

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

Technical Report Series on Global Modeling and Data Assimilation. Volume 12; Comparison of Satellite Global Rainfall Algorithms

NASA Technical Reports Server (NTRS)

Suarez, Max J. (Editor); Chang, Alfred T. C.; Chiu, Long S.

1997-01-01

Seventeen months of rainfall data (August 1987-December 1988) from nine satellite rainfall algorithms (Adler, Chang, Kummerow, Prabhakara, Huffman, Spencer, Susskind, and Wu) were analyzed to examine the uncertainty of satellite-derived rainfall estimates. The variability among algorithms, measured as the standard deviation computed from the ensemble of algorithms, shows regions of high algorithm variability tend to coincide with regions of high rain rates. Histograms of pattern correlation (PC) between algorithms suggest a bimodal distribution, with separation at a PC-value of about 0.85. Applying this threshold as a criteria for similarity, our analyses show that algorithms using the same sensor or satellite input tend to be similar, suggesting the dominance of sampling errors in these satellite estimates.

Investigating the role of the land surface in explaining the interannual variation of the net radiation balance over the Western Sahara and sub-Sahara

NASA Technical Reports Server (NTRS)

Smith, Eric A.; Nicholson, Sharon

1987-01-01

The status of the data sets is discussed. Progress was made in both data analysis and modeling areas. The atmospheric and land surface contributions to the net radiation budget over the Sahara-Sahel region is being decoupled. The interannual variability of these two processes was investigated and this variability related to seasonal rainfall fluctuations. A modified Barnes objective analysis scheme was developed which uses an eliptic scan pattern and a 3-pass iteration of the difference fields.

Rainwater runoff retention on an aged intensive green roof.

PubMed

Speak, A F; Rothwell, J J; Lindley, S J; Smith, C L

2013-09-01

Urban areas are characterised by large proportions of impervious surfaces which increases rainwater runoff and the potential for surface water flooding. Increased precipitation is predicted under current climate change projections, which will put further pressure on urban populations and infrastructure. Roof greening can be used within flood mitigation schemes to restore the urban hydrological balance of cities. Intensive green roofs, with their deeper substrates and higher plant biomass, are able to retain greater quantities of runoff, and there is a need for more studies on this less common type of green roof which also investigate the effect of factors such as age and vegetation composition. Runoff quantities from an aged intensive green roof in Manchester, UK, were analysed for 69 rainfall events, and compared to those on an adjacent paved roof. Average retention was 65.7% on the green roof and 33.6% on the bare roof. A comprehensive soil classification revealed the substrate, a mineral soil, to be in good general condition and also high in organic matter content which can increase the water holding capacity of soils. Large variation in the retention data made the use of predictive regression models unfeasible. This variation arose from complex interactions between Antecedant Dry Weather Period (ADWP), season, monthly weather trends, and rainfall duration, quantity and peak intensity. However, significantly lower retention was seen for high rainfall events, and in autumn, which had above average rainfall. The study period only covers one unusually wet year, so a longer study may uncover relationships to factors which can be applied to intensive roofs elsewhere. Annual rainfall retention for Manchester city centre could be increased by 2.3% by a 10% increase in intensive green roof construction. The results of this study will be of particular interest to practitioners implementing greenspace adaptation in temperate and cool maritime climates. Copyright © 2013 Elsevier B.V. All rights reserved.

Investigation of the influence of sampling schemes on quantitative dynamic fluorescence imaging

PubMed Central

Dai, Yunpeng; Chen, Xueli; Yin, Jipeng; Wang, Guodong; Wang, Bo; Zhan, Yonghua; Nie, Yongzhan; Wu, Kaichun; Liang, Jimin

2018-01-01

Dynamic optical data from a series of sampling intervals can be used for quantitative analysis to obtain meaningful kinetic parameters of probe in vivo. The sampling schemes may affect the quantification results of dynamic fluorescence imaging. Here, we investigate the influence of different sampling schemes on the quantification of binding potential (BP) with theoretically simulated and experimentally measured data. Three groups of sampling schemes are investigated including the sampling starting point, sampling sparsity, and sampling uniformity. In the investigation of the influence of the sampling starting point, we further summarize two cases by considering the missing timing sequence between the probe injection and sampling starting time. Results show that the mean value of BP exhibits an obvious growth trend with an increase in the delay of the sampling starting point, and has a strong correlation with the sampling sparsity. The growth trend is much more obvious if throwing the missing timing sequence. The standard deviation of BP is inversely related to the sampling sparsity, and independent of the sampling uniformity and the delay of sampling starting time. Moreover, the mean value of BP obtained by uniform sampling is significantly higher than that by using the non-uniform sampling. Our results collectively suggest that a suitable sampling scheme can help compartmental modeling of dynamic fluorescence imaging provide more accurate results and simpler operations. PMID:29675325

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

PubMed

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

2006-04-01

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

A comparison of temporal and location-based sampling strategies for global positioning system-triggered electronic diaries.

PubMed

Törnros, Tobias; Dorn, Helen; Reichert, Markus; Ebner-Priemer, Ulrich; Salize, Hans-Joachim; Tost, Heike; Meyer-Lindenberg, Andreas; Zipf, Alexander

2016-11-21

Self-reporting is a well-established approach within the medical and psychological sciences. In order to avoid recall bias, i.e. past events being remembered inaccurately, the reports can be filled out on a smartphone in real-time and in the natural environment. This is often referred to as ambulatory assessment and the reports are usually triggered at regular time intervals. With this sampling scheme, however, rare events (e.g. a visit to a park or recreation area) are likely to be missed. When addressing the correlation between mood and the environment, it may therefore be beneficial to include participant locations within the ambulatory assessment sampling scheme. Based on the geographical coordinates, the database query system then decides if a self-report should be triggered or not. We simulated four different ambulatory assessment sampling schemes based on movement data (coordinates by minute) from 143 voluntary participants tracked for seven consecutive days. Two location-based sampling schemes incorporating the environmental characteristics (land use and population density) at each participant's location were introduced and compared to a time-based sampling scheme triggering a report on the hour as well as to a sampling scheme incorporating physical activity. We show that location-based sampling schemes trigger a report less often, but we obtain more unique trigger positions and a greater spatial spread in comparison to sampling strategies based on time and distance. Additionally, the location-based methods trigger significantly more often at rarely visited types of land use and less often outside the study region where no underlying environmental data are available.

A Bivariate Mixed Distribution with a Heavy-tailed Component and its Application to Single-site Daily Rainfall Simulation

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

Li, Chao ..; Singh, Vijay P.; Mishra, Ashok K.

2013-02-06

This paper presents an improved brivariate mixed distribution, which is capable of modeling the dependence of daily rainfall from two distinct sources (e.g., rainfall from two stations, two consecutive days, or two instruments such as satellite and rain gauge). The distribution couples an existing framework for building a bivariate mixed distribution, the theory of copulae and a hybrid marginal distribution. Contributions of the improved distribution are twofold. One is the appropriate selection of the bivariate dependence structure from a wider admissible choice (10 candidate copula families). The other is the introduction of a marginal distribution capable of better representing lowmore » to moderate values as well as extremes of daily rainfall. Among several applications of the improved distribution, particularly presented here is its utility for single-site daily rainfall simulation. Rather than simulating rainfall occurrences and amounts separately, the developed generator unifies the two processes by generalizing daily rainfall as a Markov process with autocorrelation described by the improved bivariate mixed distribution. The generator is first tested on a sample station in Texas. Results reveal that the simulated and observed sequences are in good agreement with respect to essential characteristics. Then, extensive simulation experiments are carried out to compare the developed generator with three other alternative models: the conventional two-state Markov chain generator, the transition probability matrix model and the semi-parametric Markov chain model with kernel density estimation for rainfall amounts. Analyses establish that overall the developed generator is capable of reproducing characteristics of historical extreme rainfall events and is apt at extrapolating rare values beyond the upper range of available observed data. Moreover, it automatically captures the persistence of rainfall amounts on consecutive wet days in a relatively natural and easy way. Another interesting observation is that the recognized ‘overdispersion’ problem in daily rainfall simulation ascribes more to the loss of rainfall extremes than the under-representation of first-order persistence. The developed generator appears to be a sound option for daily rainfall simulation, especially in particular hydrologic planning situations when rare rainfall events are of great importance.« less

Mimic expert judgement through automated procedure for selecting rainfall events responsible for shallow landslide: A statistical approach to validation

NASA Astrophysics Data System (ADS)

Giovanna, Vessia; Luca, Pisano; Carmela, Vennari; Mauro, Rossi; Mario, Parise

2016-01-01

This paper proposes an automated method for the selection of rainfall data (duration, D, and cumulated, E), responsible for shallow landslide initiation. The method mimics an expert person identifying D and E from rainfall records through a manual procedure whose rules are applied according to her/his judgement. The comparison between the two methods is based on 300 D-E pairs drawn from temporal rainfall data series recorded in a 30 days time-lag before the landslide occurrence. Statistical tests, employed on D and E samples considered both paired and independent values to verify whether they belong to the same population, show that the automated procedure is able to replicate the expert pairs drawn by the expert judgment. Furthermore, a criterion based on cumulated distribution functions (CDFs) is proposed to select the most related D-E pairs to the expert one among the 6 drawn from the coded procedure for tracing the empirical rainfall threshold line.

Estimating Vegetation Structure in African Savannas using High Spatial Resolution Imagery

NASA Astrophysics Data System (ADS)

Axelsson, C.; Hanan, N. P.

2016-12-01

High spatial resolution satellite imagery allows for detailed mapping of trees in savanna landscapes, including estimates of woody cover, tree densities, crown sizes, and the spatial pattern of trees. By linking these vegetation parameters to rainfall and soil properties we gain knowledge of how the local environment influences vegetation. A thorough understanding of the underlying ecosystem processes is key to assessing the future productivity and stability of these ecosystems. In this study, we have processed and analyzed hundreds of sites sampled from African savannas across a wide range of rainfall and soil conditions. The vegetation at each site is classified using unsupervised classification with manual assignment into woody, herbaceous and bare cover classes. A crown delineation method further divides the woody areas into individual tree crowns. The results show that rainfall, soil, and topography interactively influence vegetation structure. We see that both total rainfall and rainfall seasonality play important roles and that soil type influences woody cover and the sizes of tree crowns.

Automatic Feature Selection and Weighting for the Formation of Homogeneous Groups for Regional Intensity-Duration-Frequency (IDF) Curve Estimation

NASA Astrophysics Data System (ADS)

Yang, Z.; Burn, D. H.

2017-12-01

Extreme rainfall events can have devastating impacts on society. To quantify the associated risk, the IDF curve has been used to provide the essential rainfall-related information for urban planning. However, the recent changes in the rainfall climatology caused by climate change and urbanization have made the estimates provided by the traditional regional IDF approach increasingly inaccurate. This inaccuracy is mainly caused by two problems: 1) The ineffective choice of similarity indicators for the formation of a homogeneous group at different regions; and 2) An inadequate number of stations in the pooling group that does not adequately reflect the optimal balance between group size and group homogeneity or achieve the lowest uncertainty in the rainfall quantiles estimates. For the first issue, to consider the temporal difference among different meteorological and topographic indicators, a three-layer design is proposed based on three stages in the extreme rainfall formation: cloud formation, rainfall generation and change of rainfall intensity above urban surface. During the process, the impacts from climate change and urbanization are considered through the inclusion of potential relevant features at each layer. Then to consider spatial difference of similarity indicators for the homogeneous group formation at various regions, an automatic feature selection and weighting algorithm, specifically the hybrid searching algorithm of Tabu search, Lagrange Multiplier and Fuzzy C-means Clustering, is used to select the optimal combination of features for the potential optimal homogenous groups formation at a specific region. For the second issue, to compare the uncertainty of rainfall quantile estimates among potential groups, the two sample Kolmogorov-Smirnov test-based sample ranking process is used. During the process, linear programming is used to rank these groups based on the confidence intervals of the quantile estimates. The proposed methodology fills the gap of including the urbanization impacts during the pooling group formation, and challenges the traditional assumption that the same set of similarity indicators can be equally effective in generating the optimal homogeneous group for regions with different geographic and meteorological characteristics.

Rainfall Observed Over Bangladesh 2000-2008: A Comparison of Spatial Interpolation Methods

NASA Astrophysics Data System (ADS)

Pervez, M.; Henebry, G. M.

2010-12-01

In preparation for a hydrometeorological study of freshwater resources in the greater Ganges-Brahmaputra region, we compared the results of four methods of spatial interpolation applied to point measurements of daily rainfall over Bangladesh during a seven year period (2000-2008). Two univariate (inverse distance weighted and spline-regularized and tension) and two multivariate geostatistical (ordinary kriging and kriging with external drift) methods were used to interpolate daily observations from a network of 221 rain gauges across Bangladesh spanning an area of 143,000 sq km. Elevation and topographic index were used as the covariates in the geostatistical methods. The validity of the interpolated maps was analyzed through cross-validation. The quality of the methods was assessed through the Pearson and Spearman correlations and root mean square error measurements of accuracy in cross-validation. Preliminary results indicated that the univariate methods performed better than the geostatistical methods at daily scales, likely due to the relatively dense sampled point measurements and a weak correlation between the rainfall and covariates at daily scales in this region. Inverse distance weighted produced the better results than the spline. For the days with extreme or high rainfall—spatially and quantitatively—the correlation between observed and interpolated estimates appeared to be high (r2 ~ 0.6 RMSE ~ 10mm), although for low rainfall days the correlations were poor (r2 ~ 0.1 RMSE ~ 3mm). The performance quality of these methods was influenced by the density of the sample point measurements, the quantity of the observed rainfall along with spatial extent, and an appropriate search radius defining the neighboring points. Results indicated that interpolated rainfall estimates at daily scales may introduce uncertainties in the successive hydrometeorological analysis. Interpolations at 5-day, 10-day, 15-day, and monthly time scales are currently under investigation.

Destabilization of a Clay-Rich Slope by Rainfall : Monitoring of Precursons on an Hectometric Sliding Surface

NASA Astrophysics Data System (ADS)

Doan, M. L.; Bièvre, G.; Jongmans, D.; Helmstetter, A.; Radiguet, M.

2016-12-01

The Avignonet landslide is an active clay landslide near Grenoble, France, and therefore one of the monitored site of OMIV observatory. Previous geophysical investigation, including borehole drilling and surface geophysics proved that the landslide deformation is accommodated by several localized shear zones. The shallowest shear zone is about 5 m deep and extends over 100 m. Several sensors monitor the landslide. They record several precursors prior to a major disturbance of the landslide in autumn 2012, that affects all sensors in the landslide for several months. After major rainfalls, the two piezometers located near the 5 m deep interface got larger impulsional response to rainfall. The moderate rainfalls of Oct 26th caused the hydraulic head both reached a plateau before experiencing a sudden change, triggered by the small rainfall of Oct 31st. It's not the bigger rainfall that induced the disturbance. It was not the first rainfall neither.Other sensors suggest that the destabilization of the landslide was progressive. Spontaneous potential sensors regularly spaced within the 100 m wide sensors begin to separate after Oct 28th, suggesting a landslide wide precursor. Repeated microseismic events, of high frequency, suggesting a local origin, are more frequent. Their occurrence peaks after the small rainfall of Oct 29th and again on Oct 31st, before the rainfall that triggered the disturbance. They stop at the same time as sudden change in piezometric data. Despite the lack of displacement sensor, it is assumed that the 5 m deep shear zone slipped on Oct 31st, since it affects the piezometer sampling this interface. The data shows a progressive path towards destabilization. Especially, triggering of the landslide disturbances is associated to the cumulative effect of seismic activity and rainfall, even minor. This suggests a hydromechanical process.

Rainfall estimation from soil moisture data: crash test for SM2RAIN algorithm

NASA Astrophysics Data System (ADS)

Brocca, Luca; Albergel, Clement; Massari, Christian; Ciabatta, Luca; Moramarco, Tommaso; de Rosnay, Patricia

2015-04-01

Soil moisture governs the partitioning of mass and energy fluxes between the land surface and the atmosphere and, hence, it represents a key variable for many applications in hydrology and earth science. In recent years, it was demonstrated that soil moisture observations from ground and satellite sensors contain important information useful for improving rainfall estimation. Indeed, soil moisture data have been used for correcting rainfall estimates from state-of-the-art satellite sensors (e.g. Crow et al., 2011), and also for improving flood prediction through a dual data assimilation approach (e.g. Massari et al., 2014; Chen et al., 2014). Brocca et al. (2013; 2014) developed a simple algorithm, called SM2RAIN, which allows estimating rainfall directly from soil moisture data. SM2RAIN has been applied successfully to in situ and satellite observations. Specifically, by using three satellite soil moisture products from ASCAT (Advanced SCATterometer), AMSR-E (Advanced Microwave Scanning Radiometer for Earth Observation) and SMOS (Soil Moisture and Ocean Salinity); it was found that the SM2RAIN-derived rainfall products are as accurate as state-of-the-art products, e.g., the real-time version of the TRMM (Tropical Rainfall Measuring Mission) product. Notwithstanding these promising results, a detailed study investigating the physical basis of the SM2RAIN algorithm, its range of applicability and its limitations on a global scale has still to be carried out. In this study, we carried out a crash test for SM2RAIN algorithm on a global scale by performing a synthetic experiment. Specifically, modelled soil moisture data are obtained from HTESSEL model (Hydrology Tiled ECMWF Scheme for Surface Exchanges over Land) forced by ERA-Interim near-surface meteorology. Afterwards, the modelled soil moisture data are used as input into SM2RAIN algorithm for testing weather or not the resulting rainfall estimates are able to reproduce ERA-Interim rainfall data. Correlation, root mean square differences and categorical scores were used to evaluate the goodness of the results. This analysis wants to draw global picture of the performance of SM2RAIN algorithm in absence of errors in soil moisture and rainfall data. First preliminary results over Europe have shown that SM2RAIN performs particularly well over southern Europe (e.g., Spain, Italy and Greece) while its performances diminish by moving towards Northern latitudes (Scandinavia) and over Alps. The results on a global scale will be shown and discussed at the conference session. REFERENCES Brocca, L., Melone, F., Moramarco, T., Wagner, W. (2013). A new method for rainfall estimation through soil moisture observations. Geophysical Research Letters, 40(5), 853-858. Brocca, L., Ciabatta, L., Massari, C., Moramarco, T., Hahn, S., Hasenauer, S., Kidd, R., Dorigo, W., Wagner, W., Levizzani, V. (2014). Soil as a natural rain gauge: estimating global rainfall from satellite soil moisture data. Journal of Geophysical Research, 119(9), 5128-5141. Chen F, Crow WT, Ryu D. (2014) Dual forcing and state correction via soil moisture assimilation for improved rainfall-runoff modeling. J Hydrometeor, 15, 1832-1848. Crow, W.T., van den Berg, M.J., Huffman, G.J., Pellarin, T. (2011). Correcting rainfall using satellite-based surface soil moisture retrievals: the soil moisture analysis rainfall tool (SMART). Water Resour Res, 47, W08521. Dee, D. P.,et al. (2011). The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Q. J. Roy. Meteorol. Soc., 137, 553-597 Massari, C., Brocca, L., Moramarco, T., Tramblay, Y., Didon Lescot, J.-F. (2014). Potential of soil moisture observations in flood modelling: estimating initial conditions and correcting rainfall. Advances in Water Resources, 74, 44-53.

NREPS Applications for Water Supply and Management in California and Tennessee

NASA Technical Reports Server (NTRS)

Gatlin, P.; Scott, M.; Carery, L. D.; Petersen, W. A.

2011-01-01

Management of water resources is a balancing act between temporally and spatially limited sources and competitive needs which can often exceed the supply. In order to manage water resources over a region such as the San Joaquin Valley or the Tennessee River Valley, it is pertinent to know the amount of water that has fallen in the watershed and where the water is going within it. Since rain gauge networks are typically sparsely spaced, it is typical that the majority of rainfall on the region may not be measured. To mitigate this under-sampling of rainfall, weather radar has long been employed to provide areal rainfall estimates. The Next-Generation Weather Radars (NEXRAD) make it possible to estimate rainfall over the majority of the conterminous United States. The NEXRAD Rainfall Estimation Processing System (NREPS) was developed specifically for the purpose of using weather radar to estimate rainfall for water resources management. The NREPS is tailored to meet customer needs on spatial and temporal scales relevant to the hydrologic or land-surface models of the end-user. It utilizes several techniques to mitigate artifacts in the NEXRAD data from contaminating the rainfall field. These techniques include clutter filtering, correction for occultation by topography as well as accounting for the vertical profile of reflectivity. This presentation will focus on improvements made to the NREPS system to map rainfall in the San Joaquin Valley for NASA s Water Supply and Management Project in California, but also ongoing rainfall mapping work in the Tennessee River watershed for the Tennessee Valley Authority and possible future applications in other areas of the continent.

A dimensionless approach for the runoff peak assessment: effects of the rainfall event structure

NASA Astrophysics Data System (ADS)

Gnecco, Ilaria; Palla, Anna; La Barbera, Paolo

2018-02-01

The present paper proposes a dimensionless analytical framework to investigate the impact of the rainfall event structure on the hydrograph peak. To this end a methodology to describe the rainfall event structure is proposed based on the similarity with the depth-duration-frequency (DDF) curves. The rainfall input consists of a constant hyetograph where all the possible outcomes in the sample space of the rainfall structures can be condensed. Soil abstractions are modelled using the Soil Conservation Service method and the instantaneous unit hydrograph theory is undertaken to determine the dimensionless form of the hydrograph; the two-parameter gamma distribution is selected to test the proposed methodology. The dimensionless approach is introduced in order to implement the analytical framework to any study case (i.e. natural catchment) for which the model assumptions are valid (i.e. linear causative and time-invariant system). A set of analytical expressions are derived in the case of a constant-intensity hyetograph to assess the maximum runoff peak with respect to a given rainfall event structure irrespective of the specific catchment (such as the return period associated with the reference rainfall event). Looking at the results, the curve of the maximum values of the runoff peak reveals a local minimum point corresponding to the design hyetograph derived according to the statistical DDF curve. A specific catchment application is discussed in order to point out the dimensionless procedure implications and to provide some numerical examples of the rainfall structures with respect to observed rainfall events; finally their effects on the hydrograph peak are examined.

Experimentally altered rainfall regimes and host root traits affect grassland arbuscular mycorrhizal fungal communities.

PubMed

Deveautour, Coline; Donn, Suzanne; Power, Sally A; Bennett, Alison E; Powell, Jeff R

2018-04-01

Future climate scenarios predict changes in rainfall regimes. These changes are expected to affect plants via effects on the expression of root traits associated with water and nutrient uptake. Associated microorganisms may also respond to these new precipitation regimes, either directly in response to changes in the soil environment or indirectly in response to altered root trait expression. We characterized arbuscular mycorrhizal (AM) fungal communities in an Australian grassland exposed to experimentally altered rainfall regimes. We used Illumina sequencing to assess the responses of AM fungal communities associated with four plant species sampled in different watering treatments and evaluated the extent to which shifts were associated with changes in root traits. We observed that altered rainfall regimes affected the composition but not the richness of the AM fungal communities, and we found distinctive communities in the increased rainfall treatment. We found no evidence of altered rainfall regime effects via changes in host physiology because none of the studied traits were affected by changes in rainfall. However, specific root length was observed to correlate with AM fungal richness, while concentrations of phosphorus and calcium in root tissue and the proportion of root length allocated to fine roots were correlated to community composition. Our study provides evidence that climate change and its effects on rainfall may influence AM fungal community assembly, as do plant traits related to plant nutrition and water uptake. We did not find evidence that host responses to altered rainfall drive AM fungal community assembly in this grassland ecosystem. © 2018 John Wiley & Sons Ltd.

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.

a Cumulus Parameterization Study with Special Attention to the Arakawa-Schubert Scheme

NASA Astrophysics Data System (ADS)

Kao, Chih-Yue Jim

Arakawa and Schubert (1974) developed a cumulus parameterization scheme in a framework that conceptually divides the mutual interaction of the cumulus convection and large-scale disturbance into the categories of large -scale budget requirements and the quasi-equilibrium assumption of cloud work function. We have applied the A-S scheme through a semi-prognostic approach to two different data sets: one is for an intense tropical cloud band event; the other is for tropical composite easterly wave disturbances. Both were observed in GATE. The cloud heating and drying effects predicted by the Arakawa-Schubert scheme are found to agree rather well with the observations. However, it is also found that the Arakawa-Schubert scheme underestimates both condensation and evaporation rates substantially when compared with the cumulus ensemble model results (Soong and Tao, 1980; Tao, 1983). An inclusion of the downdraft effects, as formulated by Johnson (1976), appears to alleviate this deficiency. In order to examine how the Arakawa-Schubert scheme works in a fully prognostic problem, a simulation of the evolution and structure of the tropical cloud band, mentioned above, under the influence of an imposed large-scale low -level forcing has been made, using a two-dimensional hydrostatic model with the inclusion of the Arakawa-Schubert scheme. Basically, the model result indicates that the meso-scale convective system is driven by the excess of the convective heating derived from the Arakawa-Schubert scheme over the adiabatic cooling due to the imposed large-scale lifting and induced meso-scale upward motion. However, as the convective system develops, the adiabatic warming due to the subsidence outside the cloud cluster gradually accumulates into a secondary temperature anomaly which subsequently reduces the original temperature contrast and inhibits the further development of the convective system. A 24 hour integration shows that the model is capable of simulating many important features such as the life cycle, intensity of circulation, and rainfall rates.

Monitoring stream sediment loads in response to agriculture in Prince Edward Island, Canada.

PubMed

Alberto, Ashley; St-Hilaire, Andre; Courtenay, Simon C; van den Heuvel, Michael R

2016-07-01

Increased agricultural land use leads to accelerated erosion and deposition of fine sediment in surface water. Monitoring of suspended sediment yields has proven challenging due to the spatial and temporal variability of sediment loading. Reliable sediment yield calculations depend on accurate monitoring of these highly episodic sediment loading events. This study aims to quantify precipitation-induced loading of suspended sediments on Prince Edward Island, Canada. Turbidity is considered to be a reasonably accurate proxy for suspended sediment data. In this study, turbidity was used to monitor suspended sediment concentration (SSC) and was measured for 2 years (December 2012-2014) in three subwatersheds with varying degrees of agricultural land use ranging from 10 to 69 %. Comparison of three turbidity meter calibration methods, two using suspended streambed sediment and one using automated sampling during rainfall events, revealed that the use of SSC samples constructed from streambed sediment was not an accurate replacement for water column sampling during rainfall events for calibration. Different particle size distributions in the three rivers produced significant impacts on the calibration methods demonstrating the need for river-specific calibration. Rainfall-induced sediment loading was significantly greater in the most agriculturally impacted site only when the load per rainfall event was corrected for runoff volume (total flow minus baseflow), flow increase intensity (the slope between the start of a runoff event and the peak of the hydrograph), and season. Monitoring turbidity, in combination with sediment modeling, may offer the best option for management purposes.

Operational Processing of Ground Validation Data for the Tropical Rainfall Measuring Mission

NASA Technical Reports Server (NTRS)

Kulie, Mark S.; Robinson, Mike; Marks, David A.; Ferrier, Brad S.; Rosenfeld, Danny; Wolff, David B.

1999-01-01

The Tropical Rainfall Measuring Mission (TRMM) satellite was successfully launched in November 1997. A primary goal of TRMM is to sample tropical rainfall using the first active spaceborne precipitation radar. To validate TRMM satellite observations, a comprehensive Ground Validation (GV) Program has been implemented for this mission. A key component of GV is the analysis and quality control of meteorological ground-based radar data from four primary sites: Melbourne, FL; Houston, TX; Darwin, Australia; and Kwajalein Atoll, RMI. As part of the TRMM GV effort, the Joint Center for Earth Systems Technology (JCET) at the University of Maryland, Baltimore County, has been tasked with developing and implementing an operational system to quality control (QC), archive, and provide data for subsequent rainfall product generation from the four primary GV sites. This paper provides an overview of the JCET operational environment. A description of the QC algorithm and performance, in addition to the data flow procedure between JCET and the TRNM science and Data Information System (TSDIS), are presented. The impact of quality-controlled data on higher level rainfall and reflectivity products will also be addressed, Finally, a brief description of JCET's expanded role into producing reference rainfall products will be discussed.

The linkage between household water consumption and rainfall in the semi-arid region of East Nusa Tenggara, Indonesia

NASA Astrophysics Data System (ADS)

Messakh, J. J.; Moy, D. L.; Mojo, D.; Maliti, Y.

2018-01-01

Several studies have shown that the amount of water consumption by communities will depend on the factors of water consumption patterns that are influenced by social, cultural, economic and local climate conditions. Research on the linkage between rainfall and household water consumption in semi-arid areas of Indonesia has never been done. This study has been conducted on 17 regions in NTT, and case study has taken samples in one town and one village. The research used survey and documentation method. The results show that the average amount of household water consumption in semi-arid region of East Nusa Tenggara is 107 liters / person / day. Statistical test results using Pearson correlation found r = -0.194 and sig = 0.448. This means that there is a negative correlation between rainfall and household water consumption. The greater the rainfall the smaller the consumption of water, or the smaller the rainfall the greater the consumption of water, but the linkage is not significant. Research shows that the amount of household water consumption will be influenced by many interrelated factors and none of the most dominant factors, including the size of the rainfall that occurs in a region.

A statistical forecast model using the time-scale decomposition technique to predict rainfall during flood period over the middle and lower reaches of the Yangtze River Valley

NASA Astrophysics Data System (ADS)

Hu, Yijia; Zhong, Zhong; Zhu, Yimin; Ha, Yao

2018-04-01

In this paper, a statistical forecast model using the time-scale decomposition method is established to do the seasonal prediction of the rainfall during flood period (FPR) over the middle and lower reaches of the Yangtze River Valley (MLYRV). This method decomposites the rainfall over the MLYRV into three time-scale components, namely, the interannual component with the period less than 8 years, the interdecadal component with the period from 8 to 30 years, and the interdecadal component with the period larger than 30 years. Then, the predictors are selected for the three time-scale components of FPR through the correlation analysis. At last, a statistical forecast model is established using the multiple linear regression technique to predict the three time-scale components of the FPR, respectively. The results show that this forecast model can capture the interannual and interdecadal variation of FPR. The hindcast of FPR during 14 years from 2001 to 2014 shows that the FPR can be predicted successfully in 11 out of the 14 years. This forecast model performs better than the model using traditional scheme without time-scale decomposition. Therefore, the statistical forecast model using the time-scale decomposition technique has good skills and application value in the operational prediction of FPR over the MLYRV.

Influence of seasonal variation on the hydro-biogeochemical characteristics of two upland lakes in the Southeastern Amazon, Brazil.

PubMed

Sahoo, Prafulla K; Guimarães, José T F; Souza-Filho, Pedro W M; Silva, Marcio S DA; Silva, Renato O; Pessim, Gustavo; Moraes, Bergson C DE; Pessoa, Paulo F P; Rodrigues, Tarcísio M; Costa, Marlene F DA; Dall'agnol, Roberto

2016-01-01

Limnological characteristics of the Violão and Amendoim lakes, in the Serra dos Carajás, Amazon, were studied interannually (2013-2014). Climate data indicate anomalous conditions during the 2013 rainy period with higher rainfall and lower temperature in the beginning (November). Lake levels were influenced after the first and second hour of each rainfall, which showed a strong synchronization between seasonal fluctuation of lake levels and local weather patterns. Based on the water quality, both lakes are classified as classes "1" and "2" in the CONAMA (Conselho Nacional do Meio Ambiente) scheme and as "excellent" to "good" in the WQI (Water Quality Index) categories. However, the limnology is distinctly different between the lakes and seasons. Higher trophic state and phytoplankton productivity were observed mainly during the rainy period in Violão Lake compared to Amendoim Lake. This may be due to deposition of leached nutrients in the former, mainly total phosphorus (TP), which was probably derived from mafic soils and guano. This is consistent with the significant positive correlation between Chlorophyll-a and TP at the end of the rainy period (March-April), whereas this was not observed in the beginning (November). This could possibly be a consequence of the more intense cloud cover, and unusual high rainfall that limits nutrient availability.

Spatial and temporal heterogeneity of microbial life in artificial landscapes

NASA Astrophysics Data System (ADS)

Sengupta, A.; Kaur, R.; Meredith, L. K.; Troch, P. A. A.

2017-12-01

The Landscape Evolution Observatory (LEO) project at Biosphere 2 consists of three replicated artificial landscapes which are sealed within a climate-controlled glass house. LEO is composed of basaltic soil material with low organic matter, nutrients, and microbes. The landscapes are built to resemble zero-order basins and enable researchers to observe hydrological, biological, and geochemical evolution of landscapes in a controlled environment. This study is focused on capturing microbial community dynamics in LEO soil, pre- and post-controlled rainfall episodes. Soil samples were collected from six different locations and at five depths in each of the three slopes followed by DNA extraction from 180 samples and sent for amplicon and minimal draft metagenome sequencing. The average concentration of DNA recovered from each sample was higher in the post-rainfall samples than the pre-rainfall samples, a trend consistent in all three slopes. The sequence data will be evaluated to reveal heterogeneity of the soil microbes, providing a more exact narrative of the microbes present in each slope and the spatiotemporal trends of microbial life in the landscapes. Next, functional traits will be predicted from the community data and metagenomes to determine whether consistent changes occur with respect to wetting and drying episodes. Together, these results will highlight the relevance of a unique terrestrial ecosystem research infrastructure in supporting interdisciplinary hydrobiogeochemical research.

Evaluating the improvements of the BOLAM meteorological model operational at ISPRA: A case study approach - preliminary results

NASA Astrophysics Data System (ADS)

Mariani, S.; Casaioli, M.; Lastoria, B.; Accadia, C.; Flavoni, S.

2009-04-01

The Institute for Environmental Protection and Research - ISPRA (former Agency for Environmental Protection and Technical Services - APAT) runs operationally since 2000 an integrated meteo-marine forecasting chain, named the Hydro-Meteo-Marine Forecasting System (Sistema Idro-Meteo-Mare - SIMM), formed by a cascade of four numerical models, telescoping from the Mediterranean basin to the Venice Lagoon, and initialized by means of analyses and forecasts from the European Centre for Medium-Range Weather Forecasts (ECMWF). The operational integrated system consists of a meteorological model, the parallel verision of BOlogna Limited Area Model (BOLAM), coupled over the Mediterranean sea with a WAve Model (WAM), a high-resolution shallow-water model of the Adriatic and Ionian Sea, namely the Princeton Ocean Model (POM), and a finite-element version of the same model (VL-FEM) on the Venice Lagoon, aimed to forecast the acqua alta events. Recently, the physically based, fully distributed, rainfall-runoff TOPographic Kinematic APproximation and Integration (TOPKAPI) model has been integrated into the system, coupled to BOLAM, over two river basins, located in the central and northeastern part of Italy, respectively. However, at the present time, this latter part of the forecasting chain is not operational and it is used in a research configuration. BOLAM was originally implemented in 2000 onto the Quadrics parallel supercomputer (and for this reason referred to as QBOLAM, as well) and only at the end of 2006 it was ported (together with the other operational marine models of the forecasting chain) onto the Silicon Graphics Inc. (SGI) Altix 8-processor machine. In particular, due to the Quadrics implementation, the Kuo scheme was formerly implemented into QBOLAM for the cumulus convection parameterization. On the contrary, when porting SIMM onto the Altix Linux cluster, it was achievable to implement into QBOLAM the more advanced convection parameterization by Kain and Fritsch. A fully updated serial version of the BOLAM code has been recently acquired. Code improvements include a more precise advection scheme (Weighted Average Flux); explicit advection of five hydrometeors, and state-of-the-art parameterization schemes for radiation, convection, boundary layer turbulence and soil processes (also with possible choice among different available schemes). The operational implementation of the new code into the SIMM model chain, which requires the development of a parallel version, will be achieved during 2009. In view of this goal, the comparative verification of the different model versions' skill represents a fundamental task. On this purpose, it has been decided to evaluate the performance improvement of the new BOLAM code (in the available serial version, hereinafter BOLAM 2007) with respect to the version with the Kain-Fritsch scheme (hereinafter KF version) and to the older one employing the Kuo scheme (hereinafter Kuo version). In the present work, verification of precipitation forecasts from the three BOLAM versions is carried on in a case study approach. The intense rainfall episode occurred on 10th - 17th December 2008 over Italy has been considered. This event produced indeed severe damages in Rome and its surrounding areas. Objective and subjective verification methods have been employed in order to evaluate model performance against an observational dataset including rain gauge observations and satellite imagery. Subjective comparison of observed and forecast precipitation fields is suitable to give an overall description of the forecast quality. Spatial errors (e.g., shifting and pattern errors) and rainfall volume error can be assessed quantitatively by means of object-oriented methods. By comparing satellite images with model forecast fields, it is possible to investigate the differences between the evolution of the observed weather system and the predicted ones, and its sensitivity to the improvements in the model code. Finally, the error in forecasting the cyclone evolution can be tentatively related with the precipitation forecast error.

A meteo-hydrological modelling system for the reconstruction of river runoff: the case of the Ofanto river catchment

NASA Astrophysics Data System (ADS)

Verri, Giorgia; Pinardi, Nadia; Gochis, David; Tribbia, Joseph; Navarra, Antonio; Coppini, Giovanni; Vukicevic, Tomislava

2017-10-01

A meteo-hydrological modelling system has been designed for the reconstruction of long time series of rainfall and river runoff events. The modelling chain consists of the mesoscale meteorological model of the Weather Research and Forecasting (WRF), the land surface model NOAH-MP and the hydrology-hydraulics model WRF-Hydro. Two 3-month periods are reconstructed for winter 2011 and autumn 2013, containing heavy rainfall and river flooding events. Several sensitivity tests were performed along with an assessment of which tunable parameters, numerical choices and forcing data most impacted on the modelling performance.The calibration of the experiments highlighted that the infiltration and aquifer coefficients should be considered as seasonally dependent.The WRF precipitation was validated by a comparison with rain gauges in the Ofanto basin. The WRF model was demonstrated to be sensitive to the initialization time and a spin-up of about 1.5 days was needed before the start of the major rainfall events in order to improve the accuracy of the reconstruction. However, this was not sufficient and an optimal interpolation method was developed to correct the precipitation simulation. It is based on an objective analysis (OA) and a least square (LS) melding scheme, collectively named OA+LS. We demonstrated that the OA+LS method is a powerful tool to reduce the precipitation uncertainties and produce a lower error precipitation reconstruction that itself generates a better river discharge time series. The validation of the river streamflow showed promising statistical indices.The final set-up of our meteo-hydrological modelling system was able to realistically reconstruct the local rainfall and the Ofanto hydrograph.

Looking at flood trends with different eyes: the value of a fuzzy flood classification scheme

NASA Astrophysics Data System (ADS)

Sikorska, A. E.; Viviroli, D.; Brunner, M. I.; Seibert, J.

2016-12-01

Natural floods can be governed by several processes such as heavy rainfall or intense snow- or glacier-melt. These processes result in different flood characteristics in terms of flood shape and magnitude. Pooling floods of different types might therefore impair the analyses of flood frequencies and trends. Thus, the categorization of flood events into different flood type classes and the determination of their respective frequencies is essential for a better understanding and for the prediction of floods. In reality however most flood events are caused by a mix of processes and a unique determination of a flood type per event often becomes difficult. This study proposes an innovative method for a more reliable categorization of floods according to similarities in flood drivers. The categorization of floods into subgroups relies on a fuzzy decision tree. While the classical (crisp) decision tree allows for the identification of only one flood type per event, the fuzzy approach enables the detection of mixed types. Hence, events are represented as a spectrum of six possible flood types, while a degree of acceptance attributed to each of them specifies the importance of each type during the event formation. Considered types are flash, short rainfall, long rainfall, snow-melt, rainfall-on-snow, and, in high altitude watersheds, also glacier-melt floods. The fuzzy concept also enables uncertainty present in the identification of flood processes and in the method to be incorporated into the flood categorization process. We demonstrate, for a set of nine Swiss watersheds and 30 years of observations, that this new concept provides more reliable flood estimates than the classical approach as it allows for a more dedicated flood prevention technique adapted to a specific flood type.

Influence of the Biosphere on Precipitation: July 1995 Studies with the ARM-CART Data

NASA Technical Reports Server (NTRS)

Sud, Y. C.; Mocko, D. M.; Walker, G. K.; Koster, Randal D.

2000-01-01

Ensemble sets of simulation experiments were conducted with a single column model (SCM) using the Goddard GEOS II GCM physics containing a recent version of the Cumulus Scheme (McRAS) and a biosphere based land-fluxes scheme (SSiB). The study used the 18 July to 5 August 1995 ARM-CART (Atmospheric Radiation Measurement-Cloud Atmospheric Radiation Test-bed) data, which was collected at the ARM-CART site in the mid-western United States and analyzed for single column modeling (SCM) studies. The new findings affirm the earlier findings that the vegetation, which increases the solar energy absorption at the surface together with soil and soil-moisture dependent processes, which modulate the surface, fluxes (particularly evapotranspiration) together help to increase the local rainfall. In addition, the results also show that for the particular study period roughly 50% of the increased evaporation over the ARM-CART site would be converted into rainfall with the Column, while the remainder would be advected out to the large-scale. Notwithstanding the limitations of only one-way interaction (i.e., the large-scale influencing the regional physics and not vice versa), the current SCM simulations show a very robust relationship. The evaporation-precipitation relationship turns out to be independent of the soil types, and soil moisture; however, it is weakly dependent on the vegetation cover because of its surface-albedo effect. Clearly, these inferences are prone to weaknesses of the SCM physics, the assumptions of the large-scale being unaffected by gridscale (SCM-scale) changes in moist processes, and other limitations of the evaluation procedures.

Decomposition of Sources of Errors in Seasonal Streamflow Forecasts in a Rainfall-Runoff Dominated Basin

NASA Astrophysics Data System (ADS)

Sinha, T.; Arumugam, S.

2012-12-01

Seasonal streamflow forecasts contingent on climate forecasts can be effectively utilized in updating water management plans and optimize generation of hydroelectric power. Streamflow in the rainfall-runoff dominated basins critically depend on forecasted precipitation in contrast to snow dominated basins, where initial hydrological conditions (IHCs) are more important. Since precipitation forecasts from Atmosphere-Ocean-General Circulation Models are available at coarse scale (~2.8° by 2.8°), spatial and temporal downscaling of such forecasts are required to implement land surface models, which typically runs on finer spatial and temporal scales. Consequently, multiple sources are introduced at various stages in predicting seasonal streamflow. Therefore, in this study, we addresses the following science questions: 1) How do we attribute the errors in monthly streamflow forecasts to various sources - (i) model errors, (ii) spatio-temporal downscaling, (iii) imprecise initial conditions, iv) no forecasts, and (iv) imprecise forecasts? and 2) How does monthly streamflow forecast errors propagate with different lead time over various seasons? In this study, the Variable Infiltration Capacity (VIC) model is calibrated over Apalachicola River at Chattahoochee, FL in the southeastern US and implemented with observed 1/8° daily forcings to estimate reference streamflow during 1981 to 2010. The VIC model is then forced with different schemes under updated IHCs prior to forecasting period to estimate relative mean square errors due to: a) temporally disaggregation, b) spatial downscaling, c) Reverse Ensemble Streamflow Prediction (imprecise IHCs), d) ESP (no forecasts), and e) ECHAM4.5 precipitation forecasts. Finally, error propagation under different schemes are analyzed with different lead time over different seasons.

Real-time projections of cholera outbreaks through data assimilation and rainfall forecasting

NASA Astrophysics Data System (ADS)

Pasetto, Damiano; Finger, Flavio; Rinaldo, Andrea; Bertuzzo, Enrico

2017-10-01

Although treatment for cholera is well-known and cheap, outbreaks in epidemic regions still exact high death tolls mostly due to the unpreparedness of health care infrastructures to face unforeseen emergencies. In this context, mathematical models for the prediction of the evolution of an ongoing outbreak are of paramount importance. Here, we test a real-time forecasting framework that readily integrates new information as soon as available and periodically issues an updated forecast. The spread of cholera is modeled by a spatially-explicit scheme that accounts for the dynamics of susceptible, infected and recovered individuals hosted in different local communities connected through hydrologic and human mobility networks. The framework presents two major innovations for cholera modeling: the use of a data assimilation technique, specifically an ensemble Kalman filter, to update both state variables and parameters based on the observations, and the use of rainfall forecasts to force the model. The exercise of simulating the state of the system and the predictive capabilities of the novel tools, set at the initial phase of the 2010 Haitian cholera outbreak using only information that was available at that time, serves as a benchmark. Our results suggest that the assimilation procedure with the sequential update of the parameters outperforms calibration schemes based on Markov chain Monte Carlo. Moreover, in a forecasting mode the model usefully predicts the spatial incidence of cholera at least one month ahead. The performance decreases for longer time horizons yet allowing sufficient time to plan for deployment of medical supplies and staff, and to evaluate alternative strategies of emergency management.

Evaluation of Cloud-Resolving Model Intercomparison Simulations Using TWP-ICE Observations: Precipitation and Cloud Structure

NASA Technical Reports Server (NTRS)

Varble, Adam; Fridlind, Ann M.; Zipser, Edward J.; Ackerman, Andrew S.; Chaboureau, Jean-Pierre; Fan, Jiwen; Hill, Adrian; McFarlane, Sally A.; Pinty, Jean-Pierre; Shipway, Ben

2011-01-01

The Tropical Warm Pool.International Cloud Experiment (TWP ]ICE) provided extensive observational data sets designed to initialize, force, and constrain atmospheric model simulations. In this first of a two ]part study, precipitation and cloud structures within nine cloud ]resolving model simulations are compared with scanning radar reflectivity and satellite infrared brightness temperature observations during an active monsoon period from 19 to 25 January 2006. Seven of nine simulations overestimate convective area by 20% or more leading to general overestimation of convective rainfall. This is balanced by underestimation of stratiform rainfall by 5% to 50% despite overestimation of stratiform area by up to 65% because of a preponderance of very low stratiform rain rates in all simulations. All simulations fail to reproduce observed radar reflectivity distributions above the melting level in convective regions and throughout the troposphere in stratiform regions. Observed precipitation ]sized ice reaches higher altitudes than simulated precipitation ]sized ice despite some simulations that predict lower than observed top ]of ]atmosphere infrared brightness temperatures. For the simulations that overestimate radar reflectivity aloft, graupel is the cause with one ]moment microphysics schemes whereas snow is the cause with two ]moment microphysics schemes. Differences in simulated radar reflectivity are more highly correlated with differences in mass mean melted diameter (Dm) than differences in ice water content. Dm is largely dependent on the mass ]dimension relationship and gamma size distribution parameters such as size intercept (N0) and shape parameter (m). Having variable density, variable N0, or m greater than zero produces radar reflectivities closest to those observed.

Assessment of microclimate conditions under artificial shades in a ginseng field.

PubMed

Lee, Kyu Jong; Lee, Byun-Woo; Kang, Je Yong; Lee, Dong Yun; Jang, Soo Won; Kim, Kwang Soo

2016-01-01

Knowledge on microclimate conditions under artificial shades in a ginseng field would facilitate climate-aware management of ginseng production. Weather data were measured under the shade and outside the shade at two fields located in Gochang-gun and Jeongeup-si, Korea, in 2011 and 2012 seasons to assess temperature and humidity conditions under the shade. An empirical approach was developed and validated for the estimation of leaf wetness duration (LWD) using weather measurements outside the shade as inputs to the model. Air temperature and relative humidity were similar between under the shade and outside the shade. For example, temperature conditions favorable for ginseng growth, e.g., between 8°C and 27°C, occurred slightly less frequently in hours during night times under the shade (91%) than outside (92%). Humidity conditions favorable for development of a foliar disease, e.g., relative humidity > 70%, occurred slightly more frequently under the shade (84%) than outside (82%). Effectiveness of correction schemes to an empirical LWD model differed by rainfall conditions for the estimation of LWD under the shade using weather measurements outside the shade as inputs to the model. During dew eligible days, a correction scheme to an empirical LWD model was slightly effective (10%) in reducing estimation errors under the shade. However, another correction approach during rainfall eligible days reduced errors of LWD estimation by 17%. Weather measurements outside the shade and LWD estimates derived from these measurements would be useful as inputs for decision support systems to predict ginseng growth and disease development.

Assessment of microclimate conditions under artificial shades in a ginseng field

PubMed Central

Lee, Kyu Jong; Lee, Byun-Woo; Kang, Je Yong; Lee, Dong Yun; Jang, Soo Won; Kim, Kwang Soo

2015-01-01

Background Knowledge on microclimate conditions under artificial shades in a ginseng field would facilitate climate-aware management of ginseng production. Methods Weather data were measured under the shade and outside the shade at two fields located in Gochang-gun and Jeongeup-si, Korea, in 2011 and 2012 seasons to assess temperature and humidity conditions under the shade. An empirical approach was developed and validated for the estimation of leaf wetness duration (LWD) using weather measurements outside the shade as inputs to the model. Results Air temperature and relative humidity were similar between under the shade and outside the shade. For example, temperature conditions favorable for ginseng growth, e.g., between 8°C and 27°C, occurred slightly less frequently in hours during night times under the shade (91%) than outside (92%). Humidity conditions favorable for development of a foliar disease, e.g., relative humidity > 70%, occurred slightly more frequently under the shade (84%) than outside (82%). Effectiveness of correction schemes to an empirical LWD model differed by rainfall conditions for the estimation of LWD under the shade using weather measurements outside the shade as inputs to the model. During dew eligible days, a correction scheme to an empirical LWD model was slightly effective (10%) in reducing estimation errors under the shade. However, another correction approach during rainfall eligible days reduced errors of LWD estimation by 17%. Conclusion Weather measurements outside the shade and LWD estimates derived from these measurements would be useful as inputs for decision support systems to predict ginseng growth and disease development. PMID:26843827

Soil erosion under multiple time-varying rainfall events

NASA Astrophysics Data System (ADS)

Heng, B. C. Peter; Barry, D. Andrew; Jomaa, Seifeddine; Sander, Graham C.

2010-05-01

Soil erosion is a function of many factors and process interactions. An erosion event produces changes in surface soil properties such as texture and hydraulic conductivity. These changes in turn alter the erosion response to subsequent events. Laboratory-scale soil erosion studies have typically focused on single independent rainfall events with constant rainfall intensities. This study investigates the effect of multiple time-varying rainfall events on soil erosion using the EPFL erosion flume. The rainfall simulator comprises ten Veejet nozzles mounted on oscillating bars 3 m above a 6 m × 2 m flume. Spray from the nozzles is applied onto the soil surface in sweeps; rainfall intensity is thus controlled by varying the sweeping frequency. Freshly-prepared soil with a uniform slope was subjected to five rainfall events at daily intervals. In each 3-h event, rainfall intensity was ramped up linearly to a maximum of 60 mm/h and then stepped down to zero. Runoff samples were collected and analysed for particle size distribution (PSD) as well as total sediment concentration. We investigate whether there is a hysteretic relationship between sediment concentration and discharge within each event and how this relationship changes from event to event. Trends in the PSD of the eroded sediment are discussed and correlated with changes in sediment concentration. Close-up imagery of the soil surface following each event highlight changes in surface soil structure with time. This study enhances our understanding of erosion processes in the field, with corresponding implications for soil erosion modelling.

A TRMM-Calibrated Infrared Technique for Convective and Stratiform Rainfall: Analysis and Validation

NASA Technical Reports Server (NTRS)

Negri, Andrew; Starr, David OC. (Technical Monitor)

2001-01-01

A satellite infrared technique with passive microwave calibration has been developed for estimating convective and stratiform rainfall. The Convective-Stratiform Technique, calibrated by coincident, physically retrieved rain rates from the TRMM Microwave Imager (TMI), has been applied to 30 min interval GOES infrared data and aggregated over seasonal and yearly periods over northern South America. The diurnal cycle of rainfall, as well as the division between convective and stratiform rainfall is presented. For the period Jan-April 1999, analysis revealed significant effects of local circulations (river breeze, land/sea breeze, mountain/valley) on both the total rainfall and it's diurnal cycle. Results compared well (a one-hour lag) with the diurnal cycle derived from TOGA radar-estimated rainfall in Rondonia. The satellite estimates revealed that the convective rain constituted 24% of the rain area while accounting for 67% of the rain volume. Estimates of the diurnal cycle (both total rainfall and convective/stratiform) for an area encompassing the Amazon Basin (3 x 10(exp 6) sq km) were in phase with those from the TRMM Precipitation Radar, despite the latter's limited sampling. Results will be presented comparing the yearly (2000) diurnal cycle for large regions (including the Amazon Basin), and an intercomparison of January-March estimates for three years, (1999-2001). We hope to demonstrate the utility of using the TRMM PR observations as verification for infrared estimates of the diurnal cycle, and as verification of the apportionment of rainfall into convective and stratiform components.

A TRMM-Calibrated Infrared Technique for Convective and Stratiform Rainfall: Analysis and Validation

NASA Technical Reports Server (NTRS)

Negri, Andrew; Starr, David OC. (Technical Monitor)

2001-01-01

A satellite infrared technique with passive microwave calibration has been developed for estimating convective and stratiform. rainfall. The Convective-Stratiform Technique, calibrated by coincident, physically retrieved rain rates from the TRMM Microwave Imager (TMI), has been applied to 30 min interval GOES infrared data and aggregated over seasonal and yearly periods over northern South America. The diurnal cycle of rainfall, as well as the division between convective and stratiform rainfall is presented. For the period Jan-April 1999, analysis revealed significant effects of local circulations (river breeze, land/sea breeze, mountain/valley) on both the total rainfall and it's diurnal cycle. Results compared well (a one-hour lag) with the diurnal cycle derived from TOGA radar-estimated rainfall in Rondonia. The satellite estimates revealed that the convective rain constituted 24% of the rain area while accounting for 67% of the rain volume. Estimates of the diurnal cycle (both total rainfall and convective/stratiform) for an area encompassing the Amazon Basin (3 x 10(exp 6) square km) were in phase with those from the TRMM Precipitation Radar, despite the latter's limited sampling. Results will be presented comparing the yearly (2000) diurnal cycle for large regions (including the Amazon Basin), and an intercomparison of January-March estimates for three years, 1999-2001. We hope to demonstrate the utility of using the TRMM PR observations as verification for infrared estimates of the diurnal cycle, and as verification of the apportionment of rainfall into convective and stratiform components.

Ground-foraging ants (Hymenoptera: Formicidae) and rainfall effect on pitfall trapping in a deciduous thorn woodland (caatinga), Northeastern Brazil.

PubMed

Nunes, Francyregis A; Segundo, Glauco B Martins; Vasconcelos, Yuri B; Azevedo, Raul; Quinet, Yves

2011-12-01

The semi-arid Caatinga is the fourth largest biome of Brazil, which biota still remains one of the most poorly known, especially with regard to invertebrate groups. In this study, a ground-foraging ant assemblage was surveyed during one year and the effect of rainfall on pitfall trapping was assessed. The study was performed in an area located in the municipality of Pentecoste (3 degrees 48' S - 39 degrees 20' W), in the State of Ceará. A 200m transect with 20 equidistant sampling points was established. Transect sampling was performed once a month during 12 months, over the period August 2008-August 2009. At each sampling point, a pitfall trap partially filled with a mixture of ethanol and monoethylene glycol was placed at the beginning of each month and remained in the field for seven days. 39 species belonging to six subfamilies and 19 genera, plus two unidentified species, were collected, with Pheidole (10 spp.) and Camponotus (8 spp.) being the taxa with the most species. 23 species were frequent, being found in more than 50% of the 12 transect samplings. Five species had an intermediate frequency (25 to 50%), while 13 were relatively infrequent (less than 25%). Most of the species (22) showed low occurrence, being found in less than 10% of the 240 samples (20 samples each month, during 12 months). Only five species were collected in more than 50% of the samples, those species being also responsible for most of the total abundance (number of captured individuals of all species) observed each month. The species-accumulation curves (observed and estimated) indicated that sampling sufficiency was attained, and that about 92% of the estimated ground-foraging ant fauna had been collected. 40 and 29 species were collected in the dry and rainy season, respectively, with monthly species richness ranging from 13 to 28. The total ant abundance showed a drastic decrease during the rainy season, and a negative linear correlation was found between rainfall and total ant abundance (R2 = 0.68). A similar negative linear correlation was found for species occurrences against rainfall (R2 = 0.71), and for mean number of species per pitfall trap against rainfall (R2 = 0.71). However, some species showed equal abundance, occurrence and mean number of individuals per pitfall trap in both seasons, while others showed a much higher abundance and occurrence during the rainy season. Pitfall trapping as a method to sample ground-foraging ant assemblage of the Caatinga biome and potential factors responsible for lower pitfall trap performance during rainy season are discussed.

Real-time adjusting of rainfall estimates from commercial microwave links

NASA Astrophysics Data System (ADS)

Fencl, Martin; Dohnal, Michal; Bareš, Vojtěch

2017-04-01

Urban stormwater predictions require reliable rainfall information with space-time resolution higher than commonly provided by standard rainfall monitoring networks of national weather services. Rainfall data from commercial microwave links (CMLs) could fill this gap. CMLs are line-of-sight radio connections widely used by cellular operators which operate at millimeter bands, where radio waves are attenuated by raindrops. Attenuation data of each single CML in the cellular network can be remotely accessed in (near) real-time with virtually arbitrary sampling frequency and convert to rainfall intensity. Unfortunately, rainfall estimates from CMLs can be substantially biased. Fencl et al., (2017), therefore, proposed adjusting method which enables to correct for this bias. They used rain gauge (RG) data from existing rainfall monitoring networks, which would have otherwise insufficient spatial and temporal resolution for urban rainfall monitoring when used alone without CMLs. In this investigation, we further develop the method to improve its performance in a real-time setting. First, a shortcoming of the original algorithm which delivers unreliable results at the beginning of a rainfall event is overcome by introducing model parameter prior distributions estimated from previous parameter realizations. Second, weights reflecting variance between RGs are introduced into cost function, which is minimized when optimizing model parameters. Finally, RG data used for adjusting are preprocessed by moving average filter. The performance of improved adjusting method is evaluated on four short CMLs (path length < 2 km) located in the small urban catchment (2.3 km2) in Prague-Letnany (CZ). The adjusted CMLs are compared to reference rainfall calculated from six RGs in the catchment. The suggested improvements of the method lead on average to 10% higher Nash-Sutcliffe efficiency coefficient (median value 0.85) for CML adjustment to hourly RG data. Reliability of CML rainfall estimates is especially improved at the beginning of rainfall events and during strong convective rainfalls, whereas performance during longer frontal rainfalls is almost unchanged. Our results clearly demonstrate that adjusting of CMLs to existing RGs represents a viable approach with great potential for real-time applications in stormwater management. This work was supported by the project of Czech Science Foundation (GACR) No.17-16389S. References: Fencl, M., Dohnal, M., Rieckermann, J. and Bareš, V.: Gauge-Adjusted Rainfall Estimates from Commercial Microwave Links, Hydrol Earth Syst. Sci., 2017 (accepted).

Transport mechanisms of Silver Nanoparticles by runoff - A Flume Experiment

NASA Astrophysics Data System (ADS)

Mahdi Mahdi, Karrar NM; Commelin, Meindert; Peters, Ruud J. B.; Baartman, Jantiene E. M.; Ritsema, Coen; Geissen, Violette

2017-04-01

Silver Nanoparticles (AgNPs) are being used in many products as it has unique antimicrobial-biocidal properties. Through leaching, these particles will reach the soil environment which may affect soil organisms and disrupt plants. This work aims to study the potential transport of AgNPs with water and sediment over the soil surface due to soil erosion by water. This was done in a laboratory setting, using a rainfall simulator and flume. Low AgNPs concentration (50 μg.kg-1) was applied to two soil-flumes with slopes of 20% and 10%. The rainfall was applied in four events of 15 min each with the total amount of rainfall was 15mm in each event. After applying the rainfall, different samples were collected; soil clusters, background (BS) and surface sediments (Sf), from the flume surface, and, Runoff sediments (RS) and water (RW) was collected from the outlet. The results showed that AgNPs were detected in all samples collected, however, AgNPs concentration varied according samples type (soil or water), time of collection (for runoff water and sediment) and the slope of the soil flume. Further, the higher AgNPs concentrations were detected in the background soil (BS); as the BS samples have more finer parts (silt and clay). The AgNPs concentration in the runoff sediments increased with subsequent applied rain events. In addition to that, increasing the slope of the flume from 10% to 20% increased the total AgNPs transported with the runoff sediments by a factor 1.5. The study confirms that AgNPs can be transported over the soil surface by both runoff water and sediments due to erosion.

Critical rainfall conditions for the initiation of torrential flows. Results from the Rebaixader catchment (Central Pyrenees)

NASA Astrophysics Data System (ADS)

Abancó, Clàudia; Hürlimann, Marcel; Moya, José; Berenguer, Marc

2016-10-01

Torrential flows like debris flows or debris floods are fast movements formed by a mix of water and different amounts of unsorted solid material. They generally occur in steep torrents and pose high risk in mountainous areas. Rainfall is their most common triggering factor and the analysis of the critical rainfall conditions is a fundamental research task. Due to their wide use in warning systems, rainfall thresholds for the triggering of torrential flows are an important outcome of such analysis and are empirically derived using data from past events. In 2009, a monitoring system was installed in the Rebaixader catchment, Central Pyrenees (Spain). Since then, rainfall data of 25 torrential flows (;TRIG rainfalls;) were recorded, with a 5-min sampling frequency. Other 142 rainfalls that did not trigger torrential flows (;NonTRIG rainfalls;) were also collected and analyzed. The goal of this work was threefold: (i) characterize rainfall episodes in the Rebaixader catchment and compare rainfall data that triggered torrential flows and others that did not; (ii) define and test Intensity-Duration (ID) thresholds using rainfall data measured inside the catchment by with different techniques; (iii) analyze how the criterion used for defining the rainfall duration and the spatial variability of rainfall influences the value obtained for the thresholds. The statistical analysis of the rainfall characteristics showed that the parameters that discriminate better the TRIG and NonTRIG rainfalls are the rainfall intensities, the mean rainfall and the total rainfall amount. The antecedent rainfall was not significantly different between TRIG and NonTRIG rainfalls, as it can be expected when the source material is very pervious (a sandy glacial soil in the study site). Thresholds were derived from data collected at one rain gauge located inside the catchment. Two different methods were applied to calculate the duration and intensity of rainfall: (i) using total duration, Dtot, and mean intensity, Imean, of the rainfall event, and (ii) using floating durations, D, and intensities, Ifl, based on the maximum values over floating periods of different duration. The resulting thresholds are considerably different (Imean = 6.20 Dtot-0.36 and Ifl_90% = 5.49 D-0.75, respectively) showing a strong dependence on the applied methodology. On the other hand, the definition of the thresholds is affected by several types of uncertainties. Data from both rain gauges and weather radar were used to analyze the uncertainty associated with the spatial variability of the triggering rainfalls. The analysis indicates that the precipitation recorded by the nearby rain gauges can introduce major uncertainties, especially for convective summer storms. Thus, incorporating radar rainfall can significantly improve the accuracy of the measured triggering rainfall. Finally, thresholds were also derived according to three different criteria for the definition of the duration of the triggering rainfall: (i) the duration until the peak intensity, (ii) the duration until the end of the rainfall; and, (iii) the duration until the trigger of the torrential flow. An important contribution of this work is the assessment of the threshold relationships obtained using the third definition of duration. Moreover, important differences are observed in the obtained thresholds, showing that ID relationships are significantly dependent on the applied methodology.

Escherichia coli Concentrations in the Mill Creek Watershed, Cleveland, Ohio, 2001-2004

USGS Publications Warehouse

Brady, Amie M.G.

2007-01-01

Mill Creek in Cleveland, Ohio, receives discharges from combined-sewer overflows (CSOs) and other sanitary-sewage inputs. These discharges affect the water quality of the creek and that of its receiving stream, the Cuyahoga River. In an effort to mitigate this problem, the Northeast Ohio Regional Sewer District implemented a project to eliminate or control (by reducing the number of overflows) all of the CSOs in the Mill Creek watershed. This study focused on monitoring the microbiological water quality of the creek before and during sewage-collection system modifications. Routine samples were collected semimonthly from August 2001 through September 2004 at a site near a U.S. Geological Survey stream gage near the mouth of Mill Creek. In addition, event samples were collected September 19 and 22, 2003, when rainfall accumulations were 0.5 inches (in.) or greater. Concentrations of Escherichia coli (E. coli) were determined and instantaneous discharges were calculated. Streamflow and water-quality characteristics were measured at the time of sampling, and precipitation data measured at a nearby precipitation gage were obtained from the National Oceanic and Atmospheric Administration. Concentrations of E. coli were greater than Ohio's single-sample maximum for primary-contact recreation (298 colony-forming units per 100 milliliters (CFU/100 mL)) in 84 percent of the routine samples collected. In all but one routine sample E. coli concentrations in samples collected when instantaneous streamflows were greater than 20 cubic feet per second (ft3/s) were greater than Ohio's single-sample maximum. When precipitation occurred in the 24-hour period before routine sample collection, concentrations were greater than the maximum in 89 percent of the samples as compared to 73 percent when rainfall was absent during the 24 hours prior to routine sample collection. Before modifications to the sewage-collection system in the watershed began, E. coli concentrations in Mill Creek ranged from 220 to 29,000 CFU/100 mL. After major modifications, E. coli concentrations ranged from 110 to 80,000 CFU/100 mL. The percentage of sample E. coli concentrations in the former group greater than Ohio's single-sample maximum was 88 percent, whereas 85 percent of sample concentrations was greater than the maximum after major modifications occurred. Instantaneous discharges of E. coli were calculated for each of the modification periods. No statistically significant difference was observed between the median instantaneous discharges of E. coli for the premodification and minor-modification periods (5.1 ? 106 and 3.6 ? 106 CFU per second, respectively). During rainfall events in September 2003, samples were collected every 15 to 30 minutes. E. coli concentrations in all of these samples (n = 34) were greater than Ohio's single-sample maximum for primary-contact recreation. On September 19, total accumulated rainfall was 1.7 in., and streamflow reached a peak of 1,040 ft3/s. Sample collection started after 0.8 in. of precipitation had fallen and continued throughout the remainder of the storm. For these samples, E. coli concentrations ranged from 32,000 to 140,000 CFU/100 mL. On September 22, total accumulated rainfall was 0.5 in., and streamflow reached a peak of 497 ft3/s. Sample collection began before the start of the rain and continued throughout the storm. E. coli concentrations ranged from 450 to 260,000 CFU/100 mL.

Regional model simulation of summer rainfall over the Philippines: Effect of choice of driving fields and ocean flux schemes

NASA Astrophysics Data System (ADS)

Francisco, R. V.; Argete, J.; Giorgi, F.; Pal, J.; Bi, X.; Gutowski, W. J.

2006-09-01

The latest version of the Abdus Salam International Centre for Theoretical Physics (ICTP) regional model RegCM is used to investigate summer monsoon precipitation over the Philippine archipelago and surrounding ocean waters, a region where regional climate models have not been applied before. The sensitivity of simulated precipitation to driving lateral boundary conditions (NCEP and ERA40 reanalyses) and ocean surface flux scheme (BATS and Zeng) is assessed for 5 monsoon seasons. The ability of the RegCM to simulate the spatial patterns and magnitude of monsoon precipitation is demonstrated, both in response to the prominent large scale circulations over the region and to the local forcing by the physiographical features of the Philippine islands. This provides encouraging indications concerning the development of a regional climate modeling system for the Philippine region. On the other hand, the model shows a substantial sensitivity to the analysis fields used for lateral boundary conditions as well as the ocean surface flux schemes. The use of ERA40 lateral boundary fields consistently yields greater precipitation amounts compared to the use of NCEP fields. Similarly, the BATS scheme consistently produces more precipitation compared to the Zeng scheme. As a result, different combinations of lateral boundary fields and surface ocean flux schemes provide a good simulation of precipitation amounts and spatial structure over the region. The response of simulated precipitation to using different forcing analysis fields is of the same order of magnitude as the response to using different surface flux parameterizations in the model. As a result it is difficult to unambiguously establish which of the model configurations is best performing.

A new approach to the convective parameterization of the regional atmospheric model BRAMS

NASA Astrophysics Data System (ADS)

Dos Santos, A. F.; Freitas, S. R.; de Campos Velho, H. F.; Luz, E. F.; Gan, M. A.; de Mattos, J. Z.; Grell, G. A.

2013-05-01

The summer characteristics of January 2010 was performed using the atmospheric model Brazilian developments on the Regional Atmospheric Modeling System (BRAMS). The convective parameterization scheme of Grell and Dévényi was used to represent clouds and their interaction with the large scale environment. As a result, the precipitation forecasts can be combined in several ways, generating a numerical representation of precipitation and atmospheric heating and moistening rates. The purpose of this study was to generate a set of weights to compute a best combination of the hypothesis of the convective scheme. It is an inverse problem of parameter estimation and the problem is solved as an optimization problem. To minimize the difference between observed data and forecasted precipitation, the objective function was computed with the quadratic difference between five simulated precipitation fields and observation. The precipitation field estimated by the Tropical Rainfall Measuring Mission satellite was used as observed data. Weights were obtained using the firefly algorithm and the mass fluxes of each closure of the convective scheme were weighted generating a new set of mass fluxes. The results indicated the better skill of the model with the new methodology compared with the old ensemble mean calculation.

An efficient and stable hydrodynamic model with novel source term discretization schemes for overland flow and flood simulations

NASA Astrophysics Data System (ADS)

Xia, Xilin; Liang, Qiuhua; Ming, Xiaodong; Hou, Jingming

2017-05-01

Numerical models solving the full 2-D shallow water equations (SWEs) have been increasingly used to simulate overland flows and better understand the transient flow dynamics of flash floods in a catchment. However, there still exist key challenges that have not yet been resolved for the development of fully dynamic overland flow models, related to (1) the difficulty of maintaining numerical stability and accuracy in the limit of disappearing water depth and (2) inaccurate estimation of velocities and discharges on slopes as a result of strong nonlinearity of friction terms. This paper aims to tackle these key research challenges and present a new numerical scheme for accurately and efficiently modeling large-scale transient overland flows over complex terrains. The proposed scheme features a novel surface reconstruction method (SRM) to correctly compute slope source terms and maintain numerical stability at small water depth, and a new implicit discretization method to handle the highly nonlinear friction terms. The resulting shallow water overland flow model is first validated against analytical and experimental test cases and then applied to simulate a hypothetic rainfall event in the 42 km2 Haltwhistle Burn, UK.

Precipitation phase separation schemes in the Naqu River basin, eastern Tibetan plateau

NASA Astrophysics Data System (ADS)

Liu, Shaohua; Yan, Denghua; Qin, Tianling; Weng, Baisha; Lu, Yajing; Dong, Guoqiang; Gong, Boya

2018-01-01

Precipitation phase has a profound influence on the hydrological processes in the Naqu River basin, eastern Tibetan plateau. However, there are only six meteorological stations with precipitation phase (rainfall/snowfall/sleet) before 1979 within and around the basin. In order to separate snowfall from precipitation, a new separation scheme with S-shaped curve of snowfall proportion as an exponential function of daily mean temperature was developed. The determinations of critical temperatures in the single/two temperature threshold (STT/TTT2) methods were explored accordingly, and the temperature corresponding to the 50 % snowfall proportion (SP50 temperature) is an efficiently critical temperature for the STT, and two critical temperatures in TTT2 can be determined based on the exponential function and SP50 temperature. Then, different separation schemes were evaluated in separating snowfall from precipitation in the Naqu River basin. The results show that the S-shaped curve methods outperform other separation schemes. Although the STT and TTT2 slightly underestimate and overestimate the snowfall when the temperature is higher and colder than SP50 temperature respectively, the monthly and annual separation snowfalls are generally consistent with the observed snowfalls. On the whole, S-shaped curve methods, STT, and TTT2 perform well in separating snowfall from precipitation with the Pearson correlation coefficient of annual separation snowfall above 0.8 and provide possible approaches to separate the snowfall from precipitation for hydrological modelling.

Detecting Climate Variability in Tropical Rainfall

NASA Astrophysics Data System (ADS)

Berg, W.

2004-05-01

A number of satellite and merged satellite/in-situ rainfall products have been developed extending as far back as 1979. While the availability of global rainfall data covering over two decades and encompassing two major El Niño events is a valuable resource for a variety of climate studies, significant differences exist between many of these products. Unfortunately, issues such as availability often determine the use of a product for a given application instead of an understanding of the strengths and weaknesses of the various products. Significant efforts have been made to address the impact of sparse sampling by satellite sensors of variable rainfall processes by merging various satellite and in-situ rainfall products. These combine high spatial and temporal frequency satellite infrared data with higher quality passive microwave observations and rain gauge observations. Combining such an approach with spatial and temporal averaging of the data can reduce the large random errors inherent in satellite rainfall estimates to very small levels. Unfortunately, systematic biases can and do result in artificial climate signals due to the underconstrained nature of the rainfall retrieval problem. Because all satellite retrieval algorithms make assumptions regarding the cloud structure and microphysical properties, systematic changes in these assumed parameters between regions and/or times results in regional and/or temporal biases in the rainfall estimates. These biases tend to be relatively small compared to random errors in the retrieval, however, when random errors are reduced through spatial and temporal averaging for climate applications, they become the dominant source of error. Whether or not such biases impact the results for climate studies is very much dependent on the application. For example, all of the existing satellite rainfall products capture the increased rainfall in the east Pacific associated with El Niño, however, the resulting tropical response to El Niño is substantially smaller due to decreased rainfall in the west Pacific partially canceling increases in the central and east Pacific. These differences are not limited to the long-term merged rainfall products using infrared data, but are also exist in state-of-the-art rainfall retrievals from the active and passive microwave sensors on board the Tropical Rainfall Measuring Mission (TRMM). For example, large differences exist in the response of tropical mean rainfall retrieved from the TRMM microwave imager (TMI) 2A12 algorithm and the precipitation radar (PR) 2A25 algorithm to the 1997/98 El Niño. To assist scientists attempting to wade through the vast array of climate rainfall products currently available, and to help them determine whether systematic biases in these rainfall products impact the conclusions of a given study, we have developed a Climate Rainfall Data Center (CRDC). The CRDC web site (rain.atmos.colostate.edu/CRDC) provides climate researchers information on the various rainfall datasets available as well as access to experts in the field of satellite rainfall retrievals to assist them in the appropriate selection and use of climate rainfall products.

Genome-wide association analysis of secondary imaging phenotypes from the Alzheimer's disease neuroimaging initiative study.

PubMed

Zhu, Wensheng; Yuan, Ying; Zhang, Jingwen; Zhou, Fan; Knickmeyer, Rebecca C; Zhu, Hongtu

2017-02-01

The aim of this paper is to systematically evaluate a biased sampling issue associated with genome-wide association analysis (GWAS) of imaging phenotypes for most imaging genetic studies, including the Alzheimer's Disease Neuroimaging Initiative (ADNI). Specifically, the original sampling scheme of these imaging genetic studies is primarily the retrospective case-control design, whereas most existing statistical analyses of these studies ignore such sampling scheme by directly correlating imaging phenotypes (called the secondary traits) with genotype. Although it has been well documented in genetic epidemiology that ignoring the case-control sampling scheme can produce highly biased estimates, and subsequently lead to misleading results and suspicious associations, such findings are not well documented in imaging genetics. We use extensive simulations and a large-scale imaging genetic data analysis of the Alzheimer's Disease Neuroimaging Initiative (ADNI) data to evaluate the effects of the case-control sampling scheme on GWAS results based on some standard statistical methods, such as linear regression methods, while comparing it with several advanced statistical methods that appropriately adjust for the case-control sampling scheme. Copyright © 2016 Elsevier Inc. All rights reserved.

The issues of current rainfall estimation techniques in mountain natural multi-hazard investigation

NASA Astrophysics Data System (ADS)

Zhuo, Lu; Han, Dawei; Chen, Ningsheng; Wang, Tao

2017-04-01

Mountain hazards (e.g., landslides, debris flows, and floods) induced by rainfall are complex phenomena that require good knowledge of rainfall representation at different spatiotemporal scales. This study reveals rainfall estimation from gauges is rather unrepresentative over a large spatial area in mountain regions. As a result, the conventional practice of adopting the triggering threshold for hazard early warning purposes is insufficient. The main reason is because of the huge orographic influence on rainfall distribution. Modern rainfall estimation methods such as numerical weather prediction modelling and remote sensing utilising radar from the space or on land are able to provide spatially more representative rainfall information in mountain areas. But unlike rain gauges, they only indirectly provide rainfall measurements. Remote sensing suffers from many sources of errors such as weather conditions, attenuation and sampling methods, while numerical weather prediction models suffer from spatiotemporal and amplitude errors depending on the model physics, dynamics, and model configuration. A case study based on Sichuan, China is used to illustrate the significant difference among the three aforementioned rainfall estimation methods. We argue none of those methods can be relied on individually, and the challenge is on how to make the full utilisation of the three methods conjunctively because each of them only provides partial information. We propose that a data fusion approach should be adopted based on the Bayesian inference method. However such an approach requires the uncertainty information from all those estimation techniques which still need extensive research. We hope this study will raise the awareness of this important issue and highlight the knowledge gap that should be filled in so that such a challenging problem could be tackled collectively by the community.

Water-quality characteristics indicative of wastewater in selected streams in the upper Neuse River Basin, Durham and Orange Counties, North Carolina, from 2004 to 2013

USGS Publications Warehouse

Ferrell, Gloria M.; Yearout, Matthew S.; Grimes, Barbara H.; Graves, Alexandria K.; Fitzgerald, Sharon A.; Meyer, Michael T.

2014-01-01

During the third phase of data collection, May 2012 to January 2013, data were collected to address the suitability of optical brighteners as tracers of wastewater in small streams during streamflow recession. Samples were collected at five small streams following periods of rainfall and analyzed for optical brighteners, specific conductance nutrients, and selected hormones. Optical brighteners were absent in the undeveloped catchment but were present in the recession period after rainfall events in catchments with centralized though possibly leaky sewage treatment and areas with onsite treatment. Sand filter systems in areas with onsite treatment appear to change the effluent flow and retention characteristics such that optical brighteners were present both before and after rainfall events. Nitrate plus nitrite, as nitrogen concentrations in samples from this last study phase generally were larger than those collected during baseflow conditions in the previous phases of this study.

The role of global cloud climatologies in validating numerical models

NASA Technical Reports Server (NTRS)

HARSHVARDHAN

1993-01-01

The purpose of this work is to estimate sampling errors of area-time averaged rain rate due to temporal samplings by satellites. In particular, the sampling errors of the proposed low inclination orbit satellite of the Tropical Rainfall Measuring Mission (TRMM) (35 deg inclination and 350 km altitude), one of the sun synchronous polar orbiting satellites of NOAA series (98.89 deg inclination and 833 km altitude), and two simultaneous sun synchronous polar orbiting satellites--assumed to carry a perfect passive microwave sensor for direct rainfall measurements--will be estimated. This estimate is done by performing a study of the satellite orbits and the autocovariance function of the area-averaged rain rate time series. A model based on an exponential fit of the autocovariance function is used for actual calculations. Varying visiting intervals and total coverage of averaging area on each visit by the satellites are taken into account in the model. The data are generated by a General Circulation Model (GCM). The model has a diurnal cycle and parameterized convective processes. A special run of the GCM was made at NASA/GSFC in which the rainfall and precipitable water fields were retained globally for every hour of the run for the whole year.

Overview: Precipitation characteristics and sensitivities to environmental conditions during GoAmazon2014/5 and ACRIDICON-CHUVA

NASA Astrophysics Data System (ADS)

Machado, Luiz A. T.; Calheiros, Alan J. P.; Biscaro, Thiago; Giangrande, Scott; Silva Dias, Maria A. F.; Cecchini, Micael A.; Albrecht, Rachel; Andreae, Meinrat O.; Araujo, Wagner F.; Artaxo, Paulo; Borrmann, Stephan; Braga, Ramon; Burleyson, Casey; Eichholz, Cristiano W.; Fan, Jiwen; Feng, Zhe; Fisch, Gilberto F.; Jensen, Michael P.; Martin, Scot T.; Pöschl, Ulrich; Pöhlker, Christopher; Pöhlker, Mira L.; Ribaud, Jean-François; Rosenfeld, Daniel; Saraiva, Jaci M. B.; Schumacher, Courtney; Thalman, Ryan; Walter, David; Wendisch, Manfred

2018-05-01

This study provides an overview of precipitation processes and their sensitivities to environmental conditions in the Central Amazon Basin near Manaus during the GoAmazon2014/5 and ACRIDICON-CHUVA experiments. This study takes advantage of the numerous measurement platforms and instrument systems operating during both campaigns to sample cloud structure and environmental conditions during 2014 and 2015; the rainfall variability among seasons, aerosol loading, land surface type, and topography has been carefully characterized using these data. Differences between the wet and dry seasons were examined from a variety of perspectives. The rainfall rates distribution, total amount of rainfall, and raindrop size distribution (the mass-weighted mean diameter) were quantified over both seasons. The dry season generally exhibited higher rainfall rates than the wet season and included more intense rainfall periods. However, the cumulative rainfall during the wet season was 4 times greater than that during the total dry season rainfall, as shown in the total rainfall accumulation data. The typical size and life cycle of Amazon cloud clusters (observed by satellite) and rain cells (observed by radar) were examined, as were differences in these systems between the seasons. Moreover, monthly mean thermodynamic and dynamic variables were analysed using radiosondes to elucidate the differences in rainfall characteristics during the wet and dry seasons. The sensitivity of rainfall to atmospheric aerosol loading was discussed with regard to mass-weighted mean diameter and rain rate. This topic was evaluated only during the wet season due to the insignificant statistics of rainfall events for different aerosol loading ranges and the low frequency of precipitation events during the dry season. The impacts of aerosols on cloud droplet diameter varied based on droplet size. For the wet season, we observed no dependence between land surface type and rain rate. However, during the dry season, urban areas exhibited the largest rainfall rate tail distribution, and deforested regions exhibited the lowest mean rainfall rate. Airplane measurements were taken to characterize and contrast cloud microphysical properties and processes over forested and deforested regions. Vertical motion was not correlated with cloud droplet sizes, but cloud droplet concentration correlated linearly with vertical motion. Clouds over forested areas contained larger droplets than clouds over pastures at all altitudes. Finally, the connections between topography and rain rate were evaluated, with higher rainfall rates identified at higher elevations during the dry season.

Application of satellite precipitation data to analyse and model arbovirus activity in the tropics

PubMed Central

2011-01-01

Background Murray Valley encephalitis virus (MVEV) is a mosquito-borne Flavivirus (Flaviviridae: Flavivirus) which is closely related to Japanese encephalitis virus, West Nile virus and St. Louis encephalitis virus. MVEV is enzootic in northern Australia and Papua New Guinea and epizootic in other parts of Australia. Activity of MVEV in Western Australia (WA) is monitored by detection of seroconversions in flocks of sentinel chickens at selected sample sites throughout WA. Rainfall is a major environmental factor influencing MVEV activity. Utilising data on rainfall and seroconversions, statistical relationships between MVEV occurrence and rainfall can be determined. These relationships can be used to predict MVEV activity which, in turn, provides the general public with important information about disease transmission risk. Since ground measurements of rainfall are sparse and irregularly distributed, especially in north WA where rainfall is spatially and temporally highly variable, alternative data sources such as remote sensing (RS) data represent an attractive alternative to ground measurements. However, a number of competing alternatives are available and careful evaluation is essential to determine the most appropriate product for a given problem. Results The Tropical Rainfall Measurement Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) 3B42 product was chosen from a range of RS rainfall products to develop rainfall-based predictor variables and build logistic regression models for the prediction of MVEV activity in the Kimberley and Pilbara regions of WA. Two models employing monthly time-lagged rainfall variables showed the strongest discriminatory ability of 0.74 and 0.80 as measured by the Receiver Operating Characteristics area under the curve (ROC AUC). Conclusions TMPA data provide a state-of-the-art data source for the development of rainfall-based predictive models for Flavivirus activity in tropical WA. Compared to ground measurements these data have the advantage of being collected spatially regularly, irrespective of remoteness. We found that increases in monthly rainfall and monthly number of days above average rainfall increased the risk of MVEV activity in the Pilbara at a time-lag of two months. Increases in monthly rainfall and monthly number of days above average rainfall increased the risk of MVEV activity in the Kimberley at a lag of three months. PMID:21255449

Thirty-one years of debris-flow observation and monitoring near La Honda, California, USA

USGS Publications Warehouse

Wieczorek, G.F.; Wilson, R.C.; Ellen, S.D.; Reid, M.E.; Jayko, A.S.

2007-01-01

From 1975 until 2006,18 intense storms triggered at least 248 debris flows within 10 km2 northwest of the town of La Honda within the Santa Cruz Mountains, California. In addition to mapping debris flows and other types of landslides, studies included soil sampling and geologic mapping, piezometric and tensiometer monitoring, and rainfall measurement and recording. From 1985 until 1995, a system with radio telemetered rain gages and piezometers within the La Honda region was used for issuing six debris-flow warnings within the San Francisco Bay region through the NOAA ALERT system. Depending upon the relative intensity of rainfall during storms, debris flows were generated from deep slumps, shallow slumps, shallow slides in colluvium and shallow slides over bedrock. Analysis shows the storms with abundant antecedent rainfall followed by several days of steady heavy intense rainfall triggered the most abundant debris flows. ?? 2007 millpress.

Multivariate space - time analysis of PRE-STORM precipitation

NASA Technical Reports Server (NTRS)

Polyak, Ilya; North, Gerald R.; Valdes, Juan B.

1994-01-01

This paper presents the methodologies and results of the multivariate modeling and two-dimensional spectral and correlation analysis of PRE-STORM rainfall gauge data. Estimated parameters of the models for the specific spatial averages clearly indicate the eastward and southeastward wave propagation of rainfall fluctuations. A relationship between the coefficients of the diffusion equation and the parameters of the stochastic model of rainfall fluctuations is derived that leads directly to the exclusive use of rainfall data to estimate advection speed (about 12 m/s) as well as other coefficients of the diffusion equation of the corresponding fields. The statistical methodology developed here can be used for confirmation of physical models by comparison of the corresponding second-moment statistics of the observed and simulated data, for generating multiple samples of any size, for solving the inverse problem of the hydrodynamic equations, and for application in some other areas of meteorological and climatological data analysis and modeling.

Improvement of Systematic Bias of mean state and the intraseasonal variability of CFSv2 through superparameterization and revised cloud-convection-radiation parameterization

NASA Astrophysics Data System (ADS)

Mukhopadhyay, P.; Phani Murali Krishna, R.; Goswami, Bidyut B.; Abhik, S.; Ganai, Malay; Mahakur, M.; Khairoutdinov, Marat; Dudhia, Jimmy

2016-05-01

Inspite of significant improvement in numerical model physics, resolution and numerics, the general circulation models (GCMs) find it difficult to simulate realistic seasonal and intraseasonal variabilities over global tropics and particularly over Indian summer monsoon (ISM) region. The bias is mainly attributed to the improper representation of physical processes. Among all the processes, the cloud and convective processes appear to play a major role in modulating model bias. In recent times, NCEP CFSv2 model is being adopted under Monsoon Mission for dynamical monsoon forecast over Indian region. The analyses of climate free run of CFSv2 in two resolutions namely at T126 and T382, show largely similar bias in simulating seasonal rainfall, in capturing the intraseasonal variability at different scales over the global tropics and also in capturing tropical waves. Thus, the biases of CFSv2 indicate a deficiency in model's parameterization of cloud and convective processes. Keeping this in background and also for the need to improve the model fidelity, two approaches have been adopted. Firstly, in the superparameterization, 32 cloud resolving models each with a horizontal resolution of 4 km are embedded in each GCM (CFSv2) grid and the conventional sub-grid scale convective parameterization is deactivated. This is done to demonstrate the role of resolving cloud processes which otherwise remain unresolved. The superparameterized CFSv2 (SP-CFS) is developed on a coarser version T62. The model is integrated for six and half years in climate free run mode being initialised from 16 May 2008. The analyses reveal that SP-CFS simulates a significantly improved mean state as compared to default CFS. The systematic bias of lesser rainfall over Indian land mass, colder troposphere has substantially been improved. Most importantly the convectively coupled equatorial waves and the eastward propagating MJO has been found to be simulated with more fidelity in SP-CFS. The reason of such betterment in model mean state has been found to be due to the systematic improvement in moisture field, temperature profile and moist instability. The model also has better simulated the cloud and rainfall relation. This initiative demonstrates the role of cloud processes on the mean state of coupled GCM. As the superparameterization approach is computationally expensive, so in another approach, the conventional Simplified Arakawa Schubert (SAS) scheme is replaced by a revised SAS scheme (RSAS) and also the old and simplified cloud scheme of Zhao-Karr (1997) has been replaced by WSM6 in CFSV2 (hereafter CFS-CR). The primary objective of such modifications is to improve the distribution of convective rain in the model by using RSAS and the grid-scale or the large scale nonconvective rain by WSM6. The WSM6 computes the tendency of six class (water vapour, cloud water, ice, snow, graupel, rain water) hydrometeors at each of the model grid and contributes in the low, middle and high cloud fraction. By incorporating WSM6, for the first time in a global climate model, we are able to show a reasonable simulation of cloud ice and cloud liquid water distribution vertically and spatially as compared to Cloudsat observations. The CFS-CR has also showed improvement in simulating annual rainfall cycle and intraseasonal variability over the ISM region. These improvements in CFS-CR are likely to be associated with improvement of the convective and stratiform rainfall distribution in the model. These initiatives clearly address a long standing issue of resolving the cloud processes in climate model and demonstrate that the improved cloud and convective process paramterizations can eventually reduce the systematic bias and improve the model fidelity.

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.

Designing single- and multiple-shell sampling schemes for diffusion MRI using spherical code.

PubMed

Cheng, Jian; Shen, Dinggang; Yap, Pew-Thian

2014-01-01

In diffusion MRI (dMRI), determining an appropriate sampling scheme is crucial for acquiring the maximal amount of information for data reconstruction and analysis using the minimal amount of time. For single-shell acquisition, uniform sampling without directional preference is usually favored. To achieve this, a commonly used approach is the Electrostatic Energy Minimization (EEM) method introduced in dMRI by Jones et al. However, the electrostatic energy formulation in EEM is not directly related to the goal of optimal sampling-scheme design, i.e., achieving large angular separation between sampling points. A mathematically more natural approach is to consider the Spherical Code (SC) formulation, which aims to achieve uniform sampling by maximizing the minimal angular difference between sampling points on the unit sphere. Although SC is well studied in the mathematical literature, its current formulation is limited to a single shell and is not applicable to multiple shells. Moreover, SC, or more precisely continuous SC (CSC), currently can only be applied on the continuous unit sphere and hence cannot be used in situations where one or several subsets of sampling points need to be determined from an existing sampling scheme. In this case, discrete SC (DSC) is required. In this paper, we propose novel DSC and CSC methods for designing uniform single-/multi-shell sampling schemes. The DSC and CSC formulations are solved respectively by Mixed Integer Linear Programming (MILP) and a gradient descent approach. A fast greedy incremental solution is also provided for both DSC and CSC. To our knowledge, this is the first work to use SC formulation for designing sampling schemes in dMRI. Experimental results indicate that our methods obtain larger angular separation and better rotational invariance than the generalized EEM (gEEM) method currently used in the Human Connectome Project (HCP).

Probing the microscopic environment of 23 Na ions in brain tissue by MRI: On the accuracy of different sampling schemes for the determination of rapid, biexponential T2* decay at low signal-to-noise ratio.

PubMed

Lommen, Jonathan M; Flassbeck, Sebastian; Behl, Nicolas G R; Niesporek, Sebastian; Bachert, Peter; Ladd, Mark E; Nagel, Armin M

2018-08-01

To investigate and to reduce influences on the determination of the short and long apparent transverse relaxation times ( T2,s*, T2,l*) of 23 Na in vivo with respect to signal sampling. The accuracy of T2* determination was analyzed in simulations for five different sampling schemes. The influence of noise in the parameter fit was investigated for three different models. A dedicated sampling scheme was developed for brain parenchyma by numerically optimizing the parameter estimation. This scheme was compared in vivo to linear sampling at 7T. For the considered sampling schemes, T2,s* / T2,l* exhibit an average bias of 3% / 4% with a variation of 25% / 15% based on simulations with previously published T2* values. The accuracy could be improved with the optimized sampling scheme by strongly averaging the earliest sample. A fitting model with constant noise floor can increase accuracy while additional fitting of a noise term is only beneficial in case of sampling until late echo time > 80 ms. T2* values in white matter were determined to be T2,s* = 5.1 ± 0.8 / 4.2 ± 0.4 ms and T2,l* = 35.7 ± 2.4 / 34.4 ± 1.5 ms using linear/optimized sampling. Voxel-wise T2* determination of 23 Na is feasible in vivo. However, sampling and fitting methods have to be chosen carefully to retrieve accurate results. Magn Reson Med 80:571-584, 2018. © 2018 International Society for Magnetic Resonance in Medicine. © 2018 International Society for Magnetic Resonance in Medicine.

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.

Measurement of surface water runoff from plots of two different sizes

NASA Astrophysics Data System (ADS)

Joel, Abraham; Messing, Ingmar; Seguel, Oscar; Casanova, Manuel

2002-05-01

Intensities and amounts of water infiltration and runoff on sloping land are governed by the rainfall pattern and soil hydraulic conductivity, as well as by the microtopography and soil surface conditions. These components are closely interrelated and occur simultaneously, and their particular contribution may change during a rainfall event, or their effects may vary at different field scales. The scale effect on the process of infiltration/runoff was studied under natural field and rainfall conditions for two plot sizes: small plots of 0·25 m2 and large plots of 50 m2. The measurements were carried out in the central region of Chile in a piedmont most recently used as natural pastureland. Three blocks, each having one large plot and five small plots, were established. Cumulative rainfall and runoff quantities were sampled every 5 min. Significant variations in runoff responses to rainfall rates were found for the two plot sizes. On average, large plots yielded only 40% of runoff quantities produced on small plots per unit area. This difference between plot sizes was observed even during periods of continuous runoff.

Simulation of infiltration and redistribution of intense rainfall using Land Surface Models

NASA Astrophysics Data System (ADS)

Mueller, Anna; Verhoef, Anne; Cloke, Hannah

2016-04-01

Flooding from intense rainfall (FFIR) can cause widespread damage and disruption. Numerical Weather Prediction (NWP) models provide distributed information about atmospheric conditions, such as precipitation, that can lead to a flooding event. Short duration, high intensity rainfall events are generally poorly predicted by NWP models, because of the high spatiotemporal resolution required and because of the way the convective rainfall is described in the model. The resolution of NWP models is ever increasing. Better understanding of complex hydrological processes and the effect of scale is important in order to improve the prediction of magnitude and duration of such events, in the context of disaster management. Working as part of the NERC SINATRA project, we evaluated how the Land Surface Model (LSM) components of NWP models cope with high intensity rainfall input and subsequent infiltration problems. Both in terms of the amount of water infiltrated in the soil store, as well as the timing and the amount of surface and subsurface runoff generated. The models investigated are SWAP (Soil Water Air Plant, Alterra, the Netherlands, van Dam 1997), JULES (Joint UK Land Environment Simulator a component of Unified Model in UK Met Office, Best et al. 2011) and CHTESSEL (Carbon and Hydrology- Tiled ECMWF Scheme for Surface Exchanges over Land, Balsamo et al. 2009) We analysed the numerical aspects arising from discontinuities (or sharp gradients) in forcing and/or the model solution. These types of infiltration configurations were tested in the laboratory (Vachaud 1971), for some there are semi-analytical solutions (Philip 1957, Parlange 1972, Vanderborght 2005) or reference numerical solutions (Haverkamp 1977, van Dam 2000, Vanderborght 2005). The maximum infiltration by the surface, Imax, is in general dependent on atmospheric conditions, surface type, soil type, soil moisture content θ, and surface orographic factor σ. The models used differ in their approach to describe and deal with this top boundary condition definition. All three LSMs discretise the spatial derivative in the Richards equation (∂/∂z) using central finite differences, which is a 2nd order method, that according to Godunov's theorem is non-monotone. It is prone to producing non-physical oscillations in the solution. We performed a mesh and timestep dependence study for hypothetical soil columns and showed the presence of the oscillations in Jules and SWAP solutions. We also investigated the rainfall/runoff partition and redistribution in case of intense rainfall using these three models.

Signal enhancement for the sensitivity-limited solid state NMR experiments using a continuous, non-uniform acquisition scheme

NASA Astrophysics Data System (ADS)

Qiang, Wei

2011-12-01

We describe a sampling scheme for the two-dimensional (2D) solid state NMR experiments, which can be readily applied to the sensitivity-limited samples. The sampling scheme utilizes continuous, non-uniform sampling profile for the indirect dimension, i.e. the acquisition number decreases as a function of the evolution time ( t1) in the indirect dimension. For a beta amyloid (Aβ) fibril sample, we observed overall 40-50% signal enhancement by measuring the cross peak volume, while the cross peak linewidths remained comparable to the linewidths obtained by regular sampling and processing strategies. Both the linear and Gaussian decay functions for the acquisition numbers result in similar percentage of increment in signal. In addition, we demonstrated that this sampling approach can be applied with different dipolar recoupling approaches such as radiofrequency assisted diffusion (RAD) and finite-pulse radio-frequency-driven recoupling (fpRFDR). This sampling scheme is especially suitable for the sensitivity-limited samples which require long signal averaging for each t1 point, for instance the biological membrane proteins where only a small fraction of the sample is isotopically labeled.

Effect of climate change on the irrigation and discharge scheme for winter wheat in Huaibei Plain, China

NASA Astrophysics Data System (ADS)

Zhu, Y.; Ren, L.; Lü, H.

2017-12-01

On the Huaibei Plain of Anhui Province, China, winter wheat (WW) is the most prominent crop. The study area belongs to transitional climate, with shallow water table. The original climate change is complex, in addition, global warming make the climate change more complex. The winter wheat growth period is from October to June, just during the rainless season, the WW growth always depends on part of irrigation water. Under such complex climate change, the rainfall varies during the growing seasons, and water table elevations also vary. Thus, water tables supply variable moisture change between soil water and groundwater, which impact the irrigation and discharge scheme for plant growth and yield. In Huaibei plain, the environmental pollution is very serious because of agricultural use of chemical fertilizer, pesticide, herbicide and etc. In order to protect river water and groundwater from pollution, the irrigation and discharge scheme should be estimated accurately. Therefore, determining the irrigation and discharge scheme for winter wheat under climate change is important for the plant growth management decision-making. Based on field observations and local weather data of 2004-2005 and 2005-2006, the numerical model HYDRUS-1D was validated and calibrated by comparing simulated and measured root-zone soil water contents. The validated model was used to estimate the irrigation and discharge scheme in 2010-2090 under the scenarios described by HadCM3 (1970 to 2000 climate states are taken as baselines) with winter wheat growth in an optimum state indicated by growth height and LAI.

Integrating interannual climate variability forecasts into weather-indexed crop insurance. The case of Malawi, Kenya and Tanzania

NASA Astrophysics Data System (ADS)

Vicarelli, M.; Giannini, A.; Osgood, D.

2009-12-01

In this study we explore the potential for re-insurance schemes built on regional climatic forecasts. We focus on micro-insurance contracts indexed on precipitation in 9 villages in Kenya, Tanzania (Eastern Africa) and Malawi (Southern Africa), and analyze the precipitation patterns and payouts resulting from El Niño Southern Oscillation (ENSO). The inability to manage future climate risk represents a “poverty trap” for several African regions. Weather shocks can potentially destabilize not only household, but also entire countries. Governments in drought-prone countries, donors and relief agencies are becoming aware of the importance to develop an ex-ante risk management framework for weather risk. Joint efforts to develop innovative mechanisms to spread and pool risk such as microinsurance and microcredit are currently being designed in several developing countries. While ENSO is an important component in modulating the rainfall regime in tropical Africa, the micro-insurance experiments currently under development to address drought risk among smallholder farmers in this region do not take into account ENSO monitoring or forecasting yet. ENSO forecasts could be integrated in the contracts and reinsurance schemes could be designed at the continental scale taking advantage of the different impact of ENSO on different regions. ENSO is associated to a bipolar precipitation pattern in Southern and Eastern Africa. La Niña years (i.e. Cold ENSO Episodes) are characterized by dry climate in Eastern Africa and wet climate in Southern Africa. During El Niño (or Warm Episode) the precipitation dipole is inverted, and Eastern Africa experiences increased probability for above normal rainfall (Halpert and Ropelewski, 1992, Journal of Climate). Our study represents the first exercise in trying to include ENSO forecasts in micro weather index insurance contract design. We analyzed the contracts payouts with respect to climate variability. In particular (i) we simulated possible payouts using historical precipitation data and analyzed the differences between years with different ENSO states from 1961 to 2005; (ii) we applied Monte Carlo methods to simulate precipitation distributions in each location and calculated the mean and variance of payouts associated to different ENSO states. The results obtained from historical precipitation data indicate that more abundant rainfall reduces payouts and the risk of loan default during La Niña in southern Kenya and Malawi, during El Niño in Tanzania. The results of the Monte Carlo simulations confirm our findings. Our results suggest that re-insurance schemes could be successfully designed to exploit the anti-correlation patterns related to interannual climate variability for different regions in Africa. Moreover, the exploratory framework presented can potentially be refined applied to other regions (e.g. Central and Latin America).

Measurements of effective non-rainfall in soil with the use of time-domain reflectometry technique

NASA Astrophysics Data System (ADS)

Nakonieczna, Anna; Kafarski, Marcin; Wilczek, Andrzej; Szypłowska, Agnieszka; Skierucha, Wojciech

2014-05-01

The non-rainfall vectors are fog, dew, hoarfrost and vapour adsorption directly from the atmosphere. The measurements of the amount of water supplied to the soil due to their temporary existence are essential, because in dry areas such water uptake can exceed that of rainfall. Although several devices and methods were proposed for estimating the effective non-rainfall input into the soil, the measurement standard has not yet been established. This is mainly due to obstacles in measuring small water additions to the medium, problems with taking readings in actual soil samples and atmospheric disturbances during their course in natural environment. There still exists the need for automated devices capable of measuring water deposition on real-world soil surfaces, whose resolution is high enough to measure the non-rainfall intensity and increase rate, which are usually very low. In order to achieve the desirable resolution and accuracy of the effective non-rainfall measurements the time-domain reflectometry (TDR) technique was employed. The TDR sensor designed and made especially for the purpose was an untypical waveguide. It consisted of a base made of laminate covered with copper, which served as a bottom of a cuboidal open container in which the examined materials were placed, and a copper signal wire placed on the top of the container. The wire adhered along its entire length to the tested material in order to eliminate the formation of air gaps between the two, what enhanced the accuracy of the measurements. The tested porous materials were glass beads, rinsed sand and three soil samples, which were collected in south-eastern Poland. The diameter ranges of their constituent particles were measured with the use of the laser diffraction technique. The sensor filled with the wetted material was placed on a scale and connected to the TDR meter. The automated readings of mass and TDR time were collected simultaneously every minute. The TDR time was correlated with the mass loss, which was a measure of the amount of water that evaporated from the porous medium. Preliminary measurements demonstrated that the temperature control is dispensable for the conducted laboratory studies, because small temperature variations do not influence the results noticeably. However, field measurements would definitely require advanced temperature calibration. The aim of the research was to test the designed sensor for the effective non-rainfall intensity measurements in actual soil samples. It turned out that the device is highly sensitive to the amount of water present in the investigated medium. The geometry of the sensor allowed obtaining satisfactory resolution, which in the case of soil samples did not exceed 0.015 mm of water. Moreover, the direct translation of the TDR time into the water amount present in the examined media is straightforward and workable among the tested materials, which is the main advantage of the presented measurement method. Hence, both the applied TDR technique and the construction of the sensor proved to be adequate for the planned measurements of the effective non-rainfall intensity.

Toward a Framework for Systematic Error Modeling of NASA Spaceborne Radar with NOAA/NSSL Ground Radar-Based National Mosaic QPE

NASA Technical Reports Server (NTRS)

Kirstettier, Pierre-Emmanual; Honh, Y.; Gourley, J. J.; Chen, S.; Flamig, Z.; Zhang, J.; Howard, K.; Schwaller, M.; Petersen, W.; Amitai, E.

2011-01-01

Characterization of the error associated to satellite rainfall estimates is a necessary component of deterministic and probabilistic frameworks involving space-born passive and active microwave measurement") for applications ranging from water budget studies to forecasting natural hazards related to extreme rainfall events. We focus here on the error structure of NASA's Tropical Rainfall Measurement Mission (TRMM) Precipitation Radar (PR) quantitative precipitation estimation (QPE) at ground. The problem is addressed by comparison of PR QPEs with reference values derived from ground-based measurements using NOAA/NSSL ground radar-based National Mosaic and QPE system (NMQ/Q2). A preliminary investigation of this subject has been carried out at the PR estimation scale (instantaneous and 5 km) using a three-month data sample in the southern part of US. The primary contribution of this study is the presentation of the detailed steps required to derive trustworthy reference rainfall dataset from Q2 at the PR pixel resolution. It relics on a bias correction and a radar quality index, both of which provide a basis to filter out the less trustworthy Q2 values. Several aspects of PR errors arc revealed and quantified including sensitivity to the processing steps with the reference rainfall, comparisons of rainfall detectability and rainfall rate distributions, spatial representativeness of error, and separation of systematic biases and random errors. The methodology and framework developed herein applies more generally to rainfall rate estimates from other sensors onboard low-earth orbiting satellites such as microwave imagers and dual-wavelength radars such as with the Global Precipitation Measurement (GPM) mission.

Calibration and field application of passive sampling for episodic exposure to polar organic pesticides in streams.

PubMed

Fernández, Diego; Vermeirssen, Etiënne L M; Bandow, Nicole; Muñoz, Katherine; Schäfer, Ralf B

2014-11-01

Rainfall-triggered runoff is a major driver of pesticide input in streams. Only few studies have examined the suitability of passive sampling to quantify such episodic exposures. In this study, we used Empore™ styrene-divinylbenzene reverse phase sulfonated disks (SDB disks) and event-driven water samples (EDS) to assess exposure to 15 fungicides and 4 insecticides in 17 streams in a German vineyard area during 4 rainfall events. We also conducted a microcosm experiment to determine the SDB-disk sampling rates and provide a free-software solution to derive sampling rates under time-variable exposure. Sampling rates ranged from 0.26 to 0.77 L d(-1) and time-weighted average (TWA) concentrations from 0.05 to 2.11 μg/L. The 2 sampling systems were in good agreement and EDS exceeded TWA concentrations on average by a factor of 3. Our study demonstrates that passive sampling is suitable to quantify episodic exposures from polar organic pesticides. Copyright © 2014 Elsevier Ltd. All rights reserved.

Coalescent: an open-science framework for importance sampling in coalescent theory.

PubMed

Tewari, Susanta; Spouge, John L

2015-01-01

Background. In coalescent theory, computer programs often use importance sampling to calculate likelihoods and other statistical quantities. An importance sampling scheme can exploit human intuition to improve statistical efficiency of computations, but unfortunately, in the absence of general computer frameworks on importance sampling, researchers often struggle to translate new sampling schemes computationally or benchmark against different schemes, in a manner that is reliable and maintainable. Moreover, most studies use computer programs lacking a convenient user interface or the flexibility to meet the current demands of open science. In particular, current computer frameworks can only evaluate the efficiency of a single importance sampling scheme or compare the efficiencies of different schemes in an ad hoc manner. Results. We have designed a general framework (http://coalescent.sourceforge.net; language: Java; License: GPLv3) for importance sampling that computes likelihoods under the standard neutral coalescent model of a single, well-mixed population of constant size over time following infinite sites model of mutation. The framework models the necessary core concepts, comes integrated with several data sets of varying size, implements the standard competing proposals, and integrates tightly with our previous framework for calculating exact probabilities. For a given dataset, it computes the likelihood and provides the maximum likelihood estimate of the mutation parameter. Well-known benchmarks in the coalescent literature validate the accuracy of the framework. The framework provides an intuitive user interface with minimal clutter. For performance, the framework switches automatically to modern multicore hardware, if available. It runs on three major platforms (Windows, Mac and Linux). Extensive tests and coverage make the framework reliable and maintainable. Conclusions. In coalescent theory, many studies of computational efficiency consider only effective sample size. Here, we evaluate proposals in the coalescent literature, to discover that the order of efficiency among the three importance sampling schemes changes when one considers running time as well as effective sample size. We also describe a computational technique called "just-in-time delegation" available to improve the trade-off between running time and precision by constructing improved importance sampling schemes from existing ones. Thus, our systems approach is a potential solution to the "2(8) programs problem" highlighted by Felsenstein, because it provides the flexibility to include or exclude various features of similar coalescent models or importance sampling schemes.

Evaluation of microtiter-plate enzyme-linked immunosorbent assay for the analysis of triazine and chloroacetanilide herbicides in rainfall

USGS Publications Warehouse

Pomes, M.L.; Thurman, E.M.; Aga, D.S.; Goolsby, D.A.

1998-01-01

Triazine and chloroacetanilide concentrations in rainfall samples collected from a 23-state region of the United States were analyzed with microtiter-plate enzyme-linked immunosorbent assay (ELISA). Thirty-six percent of rainfall samples (2072 out of 5691) were confirmed using gas chromatography/mass spectrometry (GC/MS) to evaluate the operating performance of ELISA as a screening test. Comparison of ELISA to GC/MS results showed that the two ELISA methods accurately reported GC/MS results (m = 1), but with more variability evident with the triazine than with the chloroacetanilide ELISA. Bayes's rule, a standardized method to report the results of screening tests, indicated that the two ELISA methods yielded comparable predictive values (80%), but the triazine ELISA yielded a false- positive rate of 11.8% and the chloroacetanilide ELISA yielded a false- negative rate of 23.1%. The false-positive rate for the triazine ELISA may arise from cross reactivity with an unknown triazine or metabolite. The false-negative rate of the chloroacetanilide ELISA probably resulted from a combination of low sensitivity at the reporting limit of 0.15 ??g/L and a distribution characterized by 75% of the samples at or below the reporting limit of 0.15 ??g/L.Triazine and chloroacetanilide concentrations in rainfall samples collected from a 23-state region of the United States were analyzed with microtiter-plate enzyme-linked immunosorbent assay (ELISA). Thirty-six percent of rainfall samples (2072 out of 5691) were confirmed using gas chromatography/mass spectrometry (GC/MS) to evaluate the operating performance of ELISA as a screening test. Comparison of ELISA to GC/MS results showed that the two ELISA methods accurately reported GC/MS results (m = 1), but with more variability evident with the triazine than with the chloroacetanilide ELISA. Bayes's rule, a standardized method to report the results of screening tests, indicated that the two ELISA methods yielded comparable predictive values (80%), but the triazine ELISA yielded a false-positive rate of 11.8% and the chloroacetanilide ELISA yielded a false-negative rate of 23.1%. The false-positive rate for the triazine ELISA may arise from cross reactivity with an unknown triazine or metabolite. The false-negative rate of the chloroacetanilide ELISA probably resulted from a combination of low sensitivity at the reporting limit of 0.15 ??g/L and a distribution characterized by 75% of the samples at or below the reporting limit of 0.15 ??g/L.

Mean Excess Function as a method of identifying sub-exponential tails: Application to extreme daily rainfall

NASA Astrophysics Data System (ADS)

Nerantzaki, Sofia; Papalexiou, Simon Michael

2017-04-01

Identifying precisely the distribution tail of a geophysical variable is tough, or, even impossible. First, the tail is the part of the distribution for which we have the less empirical information available; second, a universally accepted definition of tail does not and cannot exist; and third, a tail may change over time due to long-term changes. Unfortunately, the tail is the most important part of the distribution as it dictates the estimates of exceedance probabilities or return periods. Fortunately, based on their tail behavior, probability distributions can be generally categorized into two major families, i.e., sub-exponentials (heavy-tailed) and hyper-exponentials (light-tailed). This study aims to update the Mean Excess Function (MEF), providing a useful tool in order to asses which type of tail better describes empirical data. The MEF is based on the mean value of a variable over a threshold and results in a zero slope regression line when applied for the Exponential distribution. Here, we construct slope confidence intervals for the Exponential distribution as functions of sample size. The validation of the method using Monte Carlo techniques on four theoretical distributions covering major tail cases (Pareto type II, Log-normal, Weibull and Gamma) revealed that it performs well especially for large samples. Finally, the method is used to investigate the behavior of daily rainfall extremes; thousands of rainfall records were examined, from all over the world and with sample size over 100 years, revealing that heavy-tailed distributions can describe more accurately rainfall extremes.

Improving a spatial rainfall product using multiple-point geostatistical simulations and its effect on a national hydrological model.

NASA Astrophysics Data System (ADS)

Oriani, F.; Stisen, S.

2016-12-01

Rainfall amount is one of the most sensitive inputs to distributed hydrological models. Its spatial representation is of primary importance to correctly study the uncertainty of basin recharge and its propagation to the surface and underground circulation. We consider here the 10-km-grid rainfall product provided by the Danish Meteorological Institute as input to the National Water Resources Model of Denmark. Due to a drastic reduction in the rain gauge network in recent years (from approximately 500 stations in the period 1996-2006, to 250 in the period 2007-2014), the grid rainfall product, based on the interpolation of these data, is much less reliable. Consequently, the related hydrological model shows a significantly lower prediction power. To give a better estimation of spatial rainfall at the grid points far from ground measurements, we use the direct sampling technique (DS) [1], belonging to the family of multiple-point geostatistics. DS, already applied to rainfall and spatial variable estimation [2, 3], simulates a grid value by sampling a training data set where a similar data neighborhood occurs. In this way, complex statistical relations are preserved by generating similar spatial patterns to the ones found in the training data set. Using the reliable grid product from the period 1996-2006 as training data set, we first test the technique by simulating part of this data set, then we apply the technique to the grid product of the period 2007-2014, and subsequently analyzing the uncertainty propagation to the hydrological model. We show that DS can improve the reliability of the rainfall product by generating more realistic rainfall patterns, with a significant repercussion on the hydrological model. The reduction of rain gauge networks is a global phenomenon which has huge implications for hydrological model performance and the uncertainty assessment of water resources. Therefore, the presented methodology can potentially be used in many regions where historical records can act as training data. [1] G.Mariethoz et al. (2010), Water Resour. Res., 10.1029/2008WR007621.[2] F. Oriani et al. (2014), Hydrol. Earth Syst. Sc., 10.5194/hessd-11-3213-2014. [3] G. Mariethoz et al. (2012), Water Resour. Res., 10.1029/2012WR012115.

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.

Extreme precipitation forecasting in the Chilean Andean region with complex topography using the Weather Research and Forecasting (WRF) model

NASA Astrophysics Data System (ADS)

Gironás, J.; Yáñez Morroni, G.; Caneo, M.; Delgado, R.

2017-12-01

The Weather Research and Forecasting (WRF) model is broadly used for weather forecasting, hindcasting and researching due to its good performance. However, the atmospheric conditions for simulating are not always optimal when it includes complex topographies: affecting WRF mathematical stability and convergence, therefore, its performance. As Chile is a country strongly characterized by a complex topography and high gradients of elevation, WRF is ineffective resolving Chilean mountainous terrain and foothills. The need to own an effective weather forecasting tool relies on that Chile's main cities are located in these regions. Furthermore, the most intense rainfall events take place here, commonly caused by the presence of cutoff lows. This work analyzes a microphysics scheme ensemble to enhance initial forecasts made by the Chilean Weather Agency (DMC). These forecasts were made over the Santiago piedmont, in Quebrada de Ramón watershed, located upstream an urban area highly populated. In this region a non-existing planning increases the potential damage of a flash flood. An initial testing was made over different vertical levels resolution (39 and 50 levels), and subsequently testing with land use and surface models, and finally with the initial and boundary condition data (GFS/FNL). Our task made emphasis in analyzing microphysics and lead time (3 to 5 days before the storm peak) in the computational simulations over three extreme rainfall events between 2015 and 2017. WRF shortcoming are also related to the complex configuration of the synoptic events, even when the steep topography difficult the rainfall event peak amount, and to a lesser degree, the exact rainfall event beginning prediction. No evident trend was found in the lead time, but as expected, better results in rainfall and zero isotherm height are obtained with smaller anticipation. We found that WRF do predict properly the N-hours with the biggest amount of rainfall (5 hours corresponding to Quebrada de Ramón's time of concentration) and the temperatures during the event. This is a fundamental input to a hydrological model that could forecast flash floods. Finally, WSM-6Class microphysics was chosen as the one with best performance, but a geostatistical approach to countervail WRF forecasts' shortcomings over Andean piedmont is required.

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

Utilizing the Vertical Variability of Precipitation to Improve Radar QPE

NASA Technical Reports Server (NTRS)

Gatlin, Patrick N.; Petersen, Walter A.

2016-01-01

Characteristics of the melting layer and raindrop size distribution can be exploited to further improve radar quantitative precipitation estimation (QPE). Using dual-polarimetric radar and disdrometers, we found that the characteristic size of raindrops reaching the ground in stratiform precipitation often varies linearly with the depth of the melting layer. As a result, a radar rainfall estimator was formulated using D(sub m) that can be employed by polarimetric as well as dual-frequency radars (e.g., space-based radars such as the GPM DPR), to lower the bias and uncertainty of conventional single radar parameter rainfall estimates by as much as 20%. Polarimetric radar also suffers from issues associated with sampling the vertical distribution of precipitation. Hence, we characterized the vertical profile of polarimetric parameters (VP3)-a radar manifestation of the evolving size and shape of hydrometeors as they fall to the ground-on dual-polarimetric rainfall estimation. The VP3 revealed that the profile of ZDR in stratiform rainfall can bias dual-polarimetric rainfall estimators by as much as 50%, even after correction for the vertical profile of reflectivity (VPR). The VP3 correction technique that we developed can improve operational dual-polarimetric rainfall estimates by 13% beyond that offered by a VPR correction alone.

Detecting spatial structures in throughfall data: the effect of extent, sample size, sampling design, and variogram estimation method

NASA Astrophysics Data System (ADS)

Voss, Sebastian; Zimmermann, Beate; Zimmermann, Alexander

2016-04-01

In the last three decades, an increasing number of studies analyzed spatial patterns in throughfall to investigate the consequences of rainfall redistribution for biogeochemical and hydrological processes in forests. In the majority of cases, variograms were used to characterize the spatial properties of the throughfall data. The estimation of the variogram from sample data requires an appropriate sampling scheme: most importantly, a large sample and an appropriate layout of sampling locations that often has to serve both variogram estimation and geostatistical prediction. While some recommendations on these aspects exist, they focus on Gaussian data and high ratios of the variogram range to the extent of the study area. However, many hydrological data, and throughfall data in particular, do not follow a Gaussian distribution. In this study, we examined the effect of extent, sample size, sampling design, and calculation methods on variogram estimation of throughfall data. For our investigation, we first generated non-Gaussian random fields based on throughfall data with heavy outliers. Subsequently, we sampled the fields with three extents (plots with edge lengths of 25 m, 50 m, and 100 m), four common sampling designs (two grid-based layouts, transect and random sampling), and five sample sizes (50, 100, 150, 200, 400). We then estimated the variogram parameters by method-of-moments and residual maximum likelihood. Our key findings are threefold. First, the choice of the extent has a substantial influence on the estimation of the variogram. A comparatively small ratio of the extent to the correlation length is beneficial for variogram estimation. Second, a combination of a minimum sample size of 150, a design that ensures the sampling of small distances and variogram estimation by residual maximum likelihood offers a good compromise between accuracy and efficiency. Third, studies relying on method-of-moments based variogram estimation may have to employ at least 200 sampling points for reliable variogram estimates. These suggested sample sizes exceed the numbers recommended by studies dealing with Gaussian data by up to 100 %. Given that most previous throughfall studies relied on method-of-moments variogram estimation and sample sizes << 200, our current knowledge about throughfall spatial variability stands on shaky ground.

A new sampling scheme for tropical forest monitoring using satellite imagery

Treesearch

Frederic Achard; Tim Richards; Javier Gallego

2000-01-01

At the global level, a sampling scheme for tropical forest change assessment, using high resolution satellite images, has been defined using sampling units independent of any particular satellite sensor. For this purpose, a sampling frame has been chosen a hexagonal tessellation of 3,600 km².

The added value of stochastic spatial disaggregation for short-term rainfall forecasts currently available in Canada

NASA Astrophysics Data System (ADS)

Gagnon, Patrick; Rousseau, Alain N.; Charron, Dominique; Fortin, Vincent; Audet, René

2017-11-01

Several businesses and industries rely on rainfall forecasts to support their day-to-day operations. To deal with the uncertainty associated with rainfall forecast, some meteorological organisations have developed products, such as ensemble forecasts. However, due to the intensive computational requirements of ensemble forecasts, the spatial resolution remains coarse. For example, Environment and Climate Change Canada's (ECCC) Global Ensemble Prediction System (GEPS) data is freely available on a 1-degree grid (about 100 km), while those of the so-called High Resolution Deterministic Prediction System (HRDPS) are available on a 2.5-km grid (about 40 times finer). Potential users are then left with the option of using either a high-resolution rainfall forecast without uncertainty estimation and/or an ensemble with a spectrum of plausible rainfall values, but at a coarser spatial scale. The objective of this study was to evaluate the added value of coupling the Gibbs Sampling Disaggregation Model (GSDM) with ECCC products to provide accurate, precise and consistent rainfall estimates at a fine spatial resolution (10-km) within a forecast framework (6-h). For 30, 6-h, rainfall events occurring within a 40,000-km2 area (Québec, Canada), results show that, using 100-km aggregated reference rainfall depths as input, statistics of the rainfall fields generated by GSDM were close to those of the 10-km reference field. However, in forecast mode, GSDM outcomes inherit of the ECCC forecast biases, resulting in a poor performance when GEPS data were used as input, mainly due to the inherent rainfall depth distribution of the latter product. Better performance was achieved when the Regional Deterministic Prediction System (RDPS), available on a 10-km grid and aggregated at 100-km, was used as input to GSDM. Nevertheless, most of the analyzed ensemble forecasts were weakly consistent. Some areas of improvement are identified herein.

Identification of homogeneous regions for rainfall regional frequency analysis considering typhoon event in South Korea

NASA Astrophysics Data System (ADS)

Heo, J. H.; Ahn, H.; Kjeldsen, T. R.

2017-12-01

South Korea is prone to large, and often disastrous, rainfall events caused by a mixture of monsoon and typhoon rainfall phenomena. However, traditionally, regional frequency analysis models did not consider this mixture of phenomena when fitting probability distributions, potentially underestimating the risk posed by the more extreme typhoon events. Using long-term observed records of extreme rainfall from 56 sites combined with detailed information on the timing and spatial impact of past typhoons from the Korea Meteorological Administration (KMA), this study developed and tested a new mixture model for frequency analysis of two different phenomena; events occurring regularly every year (monsoon) and events only occurring in some years (typhoon). The available annual maximum 24 hour rainfall data were divided into two sub-samples corresponding to years where the annual maximum is from either (1) a typhoon event, or (2) a non-typhoon event. Then, three-parameter GEV distribution was fitted to each sub-sample along with a weighting parameter characterizing the proportion of historical events associated with typhoon events. Spatial patterns of model parameters were analyzed and showed that typhoon events are less commonly associated with annual maximum rainfall in the North-West part of the country (Seoul area), and more prevalent in the southern and eastern parts of the country, leading to the formation of two distinct typhoon regions: (1) North-West; and (2) Southern and Eastern. Using a leave-one-out procedure, a new regional frequency model was tested and compared to a more traditional index flood method. The results showed that the impact of typhoon on design events might previously have been underestimated in the Seoul area. This suggests that the use of the mixture model should be preferred where the typhoon phenomena is less frequent, and thus can have a significant effect on the rainfall-frequency curve. This research was supported by a grant(2017-MPSS31-001) from Supporting Technology Development Program for Disaster Management funded by Ministry of Public Safety and Security(MPSS) of the Korean government.

Verification of Satellite Rainfall Estimates from the Tropical Rainfall Measuring Mission over Ground Validation Sites

NASA Astrophysics Data System (ADS)

Fisher, B. L.; Wolff, D. B.; Silberstein, D. S.; Marks, D. M.; Pippitt, J. L.

2007-12-01

The Tropical Rainfall Measuring Mission's (TRMM) Ground Validation (GV) Program was originally established with the principal long-term goal of determining the random errors and systematic biases stemming from the application of the TRMM rainfall algorithms. The GV Program has been structured around two validation strategies: 1) determining the quantitative accuracy of the integrated monthly rainfall products at GV regional sites over large areas of about 500 km2 using integrated ground measurements and 2) evaluating the instantaneous satellite and GV rain rate statistics at spatio-temporal scales compatible with the satellite sensor resolution (Simpson et al. 1988, Thiele 1988). The GV Program has continued to evolve since the launch of the TRMM satellite on November 27, 1997. This presentation will discuss current GV methods of validating TRMM operational rain products in conjunction with ongoing research. The challenge facing TRMM GV has been how to best utilize rain information from the GV system to infer the random and systematic error characteristics of the satellite rain estimates. A fundamental problem of validating space-borne rain estimates is that the true mean areal rainfall is an ideal, scale-dependent parameter that cannot be directly measured. Empirical validation uses ground-based rain estimates to determine the error characteristics of the satellite-inferred rain estimates, but ground estimates also incur measurement errors and contribute to the error covariance. Furthermore, sampling errors, associated with the discrete, discontinuous temporal sampling by the rain sensors aboard the TRMM satellite, become statistically entangled in the monthly estimates. Sampling errors complicate the task of linking biases in the rain retrievals to the physics of the satellite algorithms. The TRMM Satellite Validation Office (TSVO) has made key progress towards effective satellite validation. For disentangling the sampling and retrieval errors, TSVO has developed and applied a methodology that statistically separates the two error sources. Using TRMM monthly estimates and high-resolution radar and gauge data, this method has been used to estimate sampling and retrieval error budgets over GV sites. More recently, a multi- year data set of instantaneous rain rates from the TRMM microwave imager (TMI), the precipitation radar (PR), and the combined algorithm was spatio-temporally matched and inter-compared to GV radar rain rates collected during satellite overpasses of select GV sites at the scale of the TMI footprint. The analysis provided a more direct probe of the satellite rain algorithms using ground data as an empirical reference. TSVO has also made significant advances in radar quality control through the development of the Relative Calibration Adjustment (RCA) technique. The RCA is currently being used to provide a long-term record of radar calibration for the radar at Kwajalein, a strategically important GV site in the tropical Pacific. The RCA technique has revealed previously undetected alterations in the radar sensitivity due to engineering changes (e.g., system modifications, antenna offsets, alterations of the receiver, or the data processor), making possible the correction of the radar rainfall measurements and ensuring the integrity of nearly a decade of TRMM GV observations and resources.

Evaluation of Cloud-Resolving and Limited Area Model Intercomparison Simulations Using TWP-ICE Observations. Part 2 ; Precipitation Microphysics

NASA Technical Reports Server (NTRS)

Varble, Adam; Zipser, Edward J.; Fridland, Ann M.; Zhu, Ping; Ackerman, Andrew S.; Chaboureau, Jean-Pierre; Fan, Jiwen; Hill, Adrian; Shipway, Ben; Williams, Christopher

2014-01-01

Ten 3-D cloud-resolving model (CRM) simulations and four 3-D limited area model (LAM) simulations of an intense mesoscale convective system observed on 23-24 January 2006 during the Tropical Warm Pool-International Cloud Experiment (TWP-ICE) are compared with each other and with observations and retrievals from a scanning polarimetric radar, colocated UHF and VHF vertical profilers, and a Joss-Waldvogel disdrometer in an attempt to explain a low bias in simulated stratiform rainfall. Despite different forcing methodologies, similar precipitation microphysics errors appear in CRMs and LAMs with differences that depend on the details of the bulk microphysics scheme used. One-moment schemes produce too many small raindrops, which biases Doppler velocities low, but produces rainwater contents (RWCs) that are similar to observed. Two-moment rain schemes with a gamma shape parameter (mu) of 0 produce excessive size sorting, which leads to larger Doppler velocities than those produced in one-moment schemes but lower RWCs. Two-moment schemes also produce a convective median volume diameter distribution that is too broad relative to observations and, thus, may have issues balancing raindrop formation, collision-coalescence, and raindrop breakup. Assuming a mu of 2.5 rather than 0 for the raindrop size distribution improves one-moment scheme biases, and allowing mu to have values greater than 0 may improve excessive size sorting in two-moment schemes. Underpredicted stratiform rain rates are associated with underpredicted ice water contents at the melting level rather than excessive rain evaporation, in turn likely associated with convective detrainment that is too high in the troposphere and mesoscale circulations that are too weak. A limited domain size also prevents a large, well-developed stratiform region like the one observed from developing in CRMs, although LAMs also fail to produce such a region.

Extreme flood estimation by the SCHADEX method in a snow-driven catchment: application to Atnasjø (Norway)

NASA Astrophysics Data System (ADS)

Paquet, Emmanuel; Lawrence, Deborah

2013-04-01

The SCHADEX method for extreme flood estimation was developed by Paquet et al. (2006, 2013), and since 2008, it is the reference method used by Electricité de France (EDF) for dam spillway design. SCHADEX is a so-called "semi-continuous" stochastic simulation method in that flood events are simulated on an event basis and are superimposed on a continuous simulation of the catchment saturation hazard usingrainfall-runoff modelling. The MORDOR hydrological model (Garçon, 1999) has thus far been used for the rainfall-runoff modelling. MORDOR is a conceptual, lumped, reservoir model with daily areal rainfall and air temperature as the driving input data. The principal hydrological processes represented are evapotranspiration, direct and indirect runoff, ground water, snow accumulation and melt, and routing. The model has been intensively used at EDF for more than 15 years, in particular for inflow forecasts for French mountainous catchments. SCHADEX has now also been applied to the Atnasjø catchment (463 km²), a well-documented inland catchment in south-central Norway, dominated by snowmelt flooding during spring/early summer. To support this application, a weather pattern classification based on extreme rainfall was first established for Norway (Fleig, 2012). This classification scheme was then used to build a Multi-Exponential Weather Pattern distribution (MEWP), as introduced by Garavaglia et al. (2010) for extreme rainfall estimation. The MORDOR model was then calibrated relative to daily discharge data for Atnasjø. Finally, a SCHADEX simulation was run to build a daily discharge distribution with a sufficient number of simulations for assessing the extreme quantiles. Detailed results are used to illustrate how SCHADEX handles the complex and interacting hydrological processes driving flood generation in this snow driven catchment. Seasonal and monthly distributions, as well as statistics for several thousand simulated events reaching a 1000 years return level value and assessment of snowmelt role in extreme floods are presented. This study illustrates the complexity of the extreme flood estimation in snow driven catchments, and the need for a good representation of snow accumulation and melting processes in simulations for design flood estimations. In particular, the SCHADEX method is able to represent a range of possible catchment conditions (representing both soil moisture and snowmelt) in which extreme flood events can occur. This study is part of a collaboration between NVE and EDF, initiated within the FloodFreq COST Action (http://www.cost-floodfreq.eu/). References: Fleig, A., Scientific Report of the Short Term Scientific Mission Anne Fleig visiting Électricité de France, FloodFreq COST action - STSM report, 2012 Garavaglia, F., Gailhard, J., Paquet, E., Lang, M., Garçon, R., and Bernardara, P., Introducing a rainfall compound distribution model based on weather patterns sub-sampling, Hydrol. Earth Syst. Sci., 14, 951-964, doi:10.5194/hess-14-951-2010, 2010 Garçon, R. Modèle global pluie-débit pour la prévision et la prédétermination des crues, La Houille Blanche, 7-8, 88-95. doi: 10.1051/lhb/1999088 Paquet, E., Gailhard, J. and Garçon, R. (2006), Evolution of the GRADEX method: improvement by atmospheric circulation classification and hydrological modeling, La Houille Blanche, 5, 80-90. doi: 10.1051/lhb/2006091 Paquet, E., Garavaglia, F., Garçon, R. and Gailhard, J. (2012), The SCHADEX method: a semi-continuous rainfall-runoff simulation for extreme food estimation, Journal of Hydrology, under revision

Probabilistic model predicts dynamics of vegetation biomass in a desert ecosystem in NW China

PubMed Central

Wang, Xin-ping; Schaffer, Benjamin Eli; Yang, Zhenlei; Rodriguez-Iturbe, Ignacio

2017-01-01

The temporal dynamics of vegetation biomass are of key importance for evaluating the sustainability of arid and semiarid ecosystems. In these ecosystems, biomass and soil moisture are coupled stochastic variables externally driven, mainly, by the rainfall dynamics. Based on long-term field observations in northwestern (NW) China, we test a recently developed analytical scheme for the description of the leaf biomass dynamics undergoing seasonal cycles with different rainfall characteristics. The probabilistic characterization of such dynamics agrees remarkably well with the field measurements, providing a tool to forecast the changes to be expected in biomass for arid and semiarid ecosystems under climate change conditions. These changes will depend—for each season—on the forecasted rate of rainy days, mean depth of rain in a rainy day, and duration of the season. For the site in NW China, the current scenario of an increase of 10% in rate of rainy days, 10% in mean rain depth in a rainy day, and no change in the season duration leads to forecasted increases in mean leaf biomass near 25% in both seasons. PMID:28584097

Rapid modification of urban land surface temperature during rainfall

NASA Astrophysics Data System (ADS)

Omidvar, H.; Bou-Zeid, E.; Song, J.; Yang, J.; Arwatz, G.; Wang, Z.; Hultmark, M.; Kaloush, K.

2017-12-01

We study the runoff dynamics and heat transfer over urban pavements during rainfall. A kinematic wave approach is combined with heat storage and transfer schemes to develop a model for impervious (with runoff) and pervious (without runoff) pavements. The resulting framework is a numerical prognostic model that can simulate the temperature fields in the subsurface and runoff layers to capture the rapid cooling of the surface, as well as the thermal pollution advected in the runoff. Extensive field measurements were then conducted over experimental pavements in Arizona to probe the physics and better represent the relevant processes in the model, and then to validate the model. The experimental data and the model results were in very good agreements, and their joint analysis elucidated the physics of the rapid heat transfer from the subsurface to the runoff layer. Finally, we apply the developed model to investigate how the various hydrological and thermal properties of the pavements, as well as ambient environmental conditions, modulate the surface and runoff thermal dynamics, what is the relative importance of each of them, and how we can apply the model mitigate the adverse impacts of urbanization.

The Impacts of Microphysics and Planetary Boundary Layer Physics on Model Simulations of U.S. Deep South Summer Convection

NASA Technical Reports Server (NTRS)

McCaul, Eugene W., Jr.; Case, Jonathan L.; Zavodsky, Bradley; Srikishen, Jayanthi; Medlin, Jeffrey; Wood, Lance

2014-01-01

Convection-allowing numerical weather simula- tions have often been shown to produce convective storms that have significant sensitivity to choices of model physical parameterizations. Among the most important of these sensitivities are those related to cloud microphysics, but planetary boundary layer parameterizations also have a significant impact on the evolution of the convection. Aspects of the simulated convection that display sensitivity to these physics schemes include updraft size and intensity, simulated radar reflectivity, timing and placement of storm initi- ation and decay, total storm rainfall, and other storm features derived from storm structure and hydrometeor fields, such as predicted lightning flash rates. In addition to the basic parameters listed above, the simulated storms may also exhibit sensitivity to im- posed initial conditions, such as the fields of soil temper- ature and moisture, vegetation cover and health, and sea and lake water surface temperatures. Some of these sensitivities may rival those of the basic physics sensi- tivities mentioned earlier. These sensitivities have the potential to disrupt the accuracy of short-term forecast simulations of convective storms, and thereby pose sig- nificant difficulties for weather forecasters. To make a systematic study of the quantitative impacts of each of these sensitivities, a matrix of simulations has been performed using all combinations of eight separate microphysics schemes, three boundary layer schemes, and two sets of initial conditions. The first version of initial conditions consists of the default data from large-scale operational model fields, while the second features specialized higher- resolution soil conditions, vegetation conditions and water surface temperatures derived from datasets created at NASA's Short-term Prediction and Operational Research Tran- sition (SPoRT) Center at the National Space Science and Technology Center (NSSTC) in Huntsville, AL. Simulations as outlined above, each 48 in number, were conducted for five midsummer weakly sheared coastal convective events each at two sites, Mobile, AL (MOB) and Houston, TX (HGX). Of special interest to operational forecasters at MOB and HGX were accuracy of timing and placement of convective storm initiation, reflectivity magnitudes and coverage, rainfall and inferred lightning threat.

Relationship Between Precipitation Chemistry and Meteorological Parameters at a Urban Site in the North of Queretaro State

NASA Astrophysics Data System (ADS)

García Martínez, R.; Hernández, G.; Solis, S.; Torres, M. D.; Padilla, H.; Báez, A.

2010-12-01

A total of 50 wet precipitation samples were collected per event at the Juriquilla site from mid-May 2009 to the end of May 2010. The Juriquilla sampling site was located on the roof of the Geoscience Building, Universidad Nacional Autónoma de México, at the Juriquilla Campus in the city of Querétaro located at 20°41'58"N and 100°27'28" W, at 1920 meters above sea level (masl). Sampling was done in passive collectors that consisted of a high density polyethylene funnel connected to a 2-liter polyethylene bottle, supported by a rod 1.5 m above the roof. One of the collectors was used to take samples for trace metals. The analysis was done in soluble and insoluble fractions. Al, Ag, As, Cd, Cr, Cu, Hg, Mn, Ni, Pb, V and Zn were analyzed by atomic absorption spectroscopy with a graphite furnace accessory. The other collector was used to measure pH and major ions (SO4-2, Cl-, NO3-, Ca2+, Mg2+, Na+, K+ and NH4+) in the soluble fractions, because it was assumed that these ions are completely soluble in rainwater. The major ions SO4-2, Cl-, and NO3-, were analyzed by a Varian Model 2010 ion chromatograph; Ca2+, Mg2+, Na+ and K+ were determined by flame atomic absorption spectrometry and NH4+ by a UV spectrophotometer. In this study, synoptic maps were used to analyze the transport of air masses before rainfall, enabling back trajectories to be used to estimate the source region of pollutants. To understand the variety of synoptic weather conditions, data were associated with the corresponding air mass back trajectories calculated by the NOAA HYSPLIT model (Hybrid Single-Particle Lagrangian Integrated Trajectory Model). Back trajectory models have very simple advection schemes to calculate the previous position of an air parcel by using estimated wind speed and direction for the time period prior to arrival at the selected site. In this study, the origin of the air mass for an event was evaluated by a three-day back-trajectory before arrival to Queretaro. Mass back trajectories were calculated for 1000 and 2000 meters above ground level (MAGL), because winds at these levels should be a good approximation to the mean transport wind, since this pressure level frequently lies near the center of the transport layer. Finally, trajectories were classified by eight different directions according to the directions of the air masses before rainfall.

Climatological Processing and Product Development for the TRMM Ground Validation Program

NASA Technical Reports Server (NTRS)

Marks, D. A.; Kulie, M. S.; Robinson, M.; Silberstein, D. S.; Wolff, D. B.; Ferrier, B. S.; Amitai, E.; Fisher, B.; Wang, J.; Augustine, D.;

The effects of low-tide rainfall on metal content of suspended sediment in the Sacramento-San Joaquin Delta

NASA Astrophysics Data System (ADS)

Moskalski, S. M.; Torres, R.; Bizimis, M.; Bergamaschi, B. A.; Fleck, J.; Goni, M. A.

2012-12-01

Rain falling near low tide is capable of eroding and transporting cohesive sediment from marsh and mudflat surfaces. Given that metals adsorb strongly to silt- and clay-sized particles, it is conceivable that lowtide rainfall may also liberate previously-deposited metals from storage in intertidal sediment. To investigate the potential for rainfall as an agent of remobilization of metals, this study tested the hypothesis of sediment, and therefore metals and nutrients, mobilization during these punctuated low-tide rainfall events. Water samples were collected during low-tide rain events in winter and wind resuspension events in summer from a marsh in central California. The concentrations of suspended sediment, particulate organic carbon and nitrogen, and total adsorbed concentration (mass of metal per volume of filtered water) of most metals were higher during a low tide rainfall event than during wind-only and fair-weather events. Metal contents (mass of metal per mass of sediment) were also greater during the rain event for most metals. Principle components analysis and the relationships between total adsorbed metals and SSC suggest rainfall during low tide can mobilize a different source of sediment than the background sediment available for tidal and wind-wave resuspension. The metal content of bulk sediment samples from around the study area could not be matched satisfactorily to the suspended sediment in any of the events, implying that bulk sediment should not be used to extrapolate to suspended sediment in terms of adsorbed metal content. Some of the adsorbed metals were present during the rain event in amounts that could be toxic, depending on the actual bioavailability of the metals.; Summary plots of measured organic parameters. (A) POC (B) PN (C) C:N (D) total leachable metal concentration, sum of all measured metals. The solid line inside box is the median and the dashed line is the mean.

Matching soil salinization and cropping systems in communally managed irrigation schemes

NASA Astrophysics Data System (ADS)

Malota, Mphatso; Mchenga, Joshua

2018-03-01

Occurrence of soil salinization in irrigation schemes can be a good indicator to introduce high salt tolerant crops in irrigation schemes. This study assessed the level of soil salinization in a communally managed 233 ha Nkhate irrigation scheme in the Lower Shire Valley region of Malawi. Soil samples were collected within the 0-0.4 m soil depth from eight randomly selected irrigation blocks. Irrigation water samples were also collected from five randomly selected locations along the Nkhate River which supplies irrigation water to the scheme. Salinity of both the soil and the irrigation water samples was determined using an electrical conductivity (EC) meter. Analysis of the results indicated that even for very low salinity tolerant crops (ECi < 2 dS/m), the irrigation water was suitable for irrigation purposes. However, root-zone soil salinity profiles depicted that leaching of salts was not adequate and that the leaching requirement for the scheme needs to be relooked and always be adhered to during irrigation operation. The study concluded that the crop system at the scheme needs to be adjusted to match with prevailing soil and irrigation water salinity levels.

Impact of potential large-scale and medium-scale irrigation on the West African Monsoon and its dependence on location of irrigated area

NASA Astrophysics Data System (ADS)

Eltahir, E. A. B.; IM, E. S.

2014-12-01

This study investigates the impact of potential large-scale (about 400,000 km2) and medium-scale (about 60,000 km2) irrigation on the climate of West Africa using the MIT Regional Climate Model. A new irrigation module is implemented to assess the impact of location and scheduling of irrigation on rainfall distribution over West Africa. A control simulation (without irrigation) and various sensitivity experiments (with irrigation) are performed and compared to discern the effects of irrigation location, size and scheduling. In general, the irrigation-induced surface cooling due to anomalously wet soil tends to suppress moist convection and rainfall, which in turn induces local subsidence and low level anti-cyclonic circulation. These local effects are dominated by a consistent reduction of local rainfall over the irrigated land, irrespective of its location. However, the remote response of rainfall distribution to irrigation exhibits a significant sensitivity to the latitudinal position of irrigation. The low-level northeasterly flow associated with anti-cyclonic circulation centered over the irrigation area can enhance the extent of low level convergence through interaction with the prevailing monsoon flow, leading to significant increase in rainfall. Despite much reduced forcing of irrigation water, the medium-scale irrigation seems to draw the same response as large-scale irrigation, which supports the robustness of the response to irrigation in our modeling system. Both large-scale and medium-scale irrigation experiments show that an optimal irrigation location and scheduling exists that would lead to a more efficient use of irrigation water. The approach of using a regional climate model to investigate the impact of location and size of irrigation schemes may be the first step in incorporating land-atmosphere interactions in the design of location and size of irrigation projects. However, this theoretical approach is still in early stages of development and further research is needed before any practical application in water resources planning. Acknowledgements.This research was supported by the National Research Foundation Singapore through the Singapore MIT Alliance for Research and Technology's Center for Environmental Sensing and Modeling interdisciplinary research program.

Observations of Heavy Rainfall in a Post Wildland Fire Area Using X-Band Polarimetric Radar

NASA Astrophysics Data System (ADS)

Cifelli, R.; Matrosov, S. Y.; Gochis, D. J.; Kennedy, P.; Moody, J. A.

2011-12-01

Polarimetric X-band radar systems have been used increasingly over the last decade for rainfall measurements. Since X-band radar systems are generally less costly, more mobile, and have narrower beam widths (for same antenna sizes) than those operating at lower frequencies (e.g., C and S-bands), they can be used for the "gap-filling" purposes for the areas when high resolution rainfall measurements are needed and existing operational radars systems lack adequate coverage and/or resolution for accurate quantitative precipitation estimation (QPE). The main drawback of X-band systems is attenuation of radar signals, which is significantly stronger compared to frequencies used by "traditional" precipitation radars operating at lower frequencies. The use of different correction schemes based on polarimetric data can, to a certain degree, overcome this drawback when attenuation does not cause total signal extinction. This presentation will focus on examining the use of high-resolution data from the NOAA Earth System Research Laboratory (ESRL) mobile X-band dual polarimetric radar for the purpose of estimating precipitation in a post-wildland fire area. The NOAA radar was deployed in the summer of 2011 to examine the impact of gap-fill radar on QPE and the resulting hydrologic response during heavy rain events in the Colorado Front Range in collaboration with colleagues from the National Center for Atmospheric Research (NCAR), Colorado State University (CSU), and the U.S. Geological Survey (USGS). A network of rain gauges installed by NCAR, the Denver Urban Drainage Flood Control District (UDFCD), and the USGS are used to compare with the radar estimates. Supplemental data from NEXRAD and the CSU-CHILL dual polarimetric radar are also used to compare with the NOAA X-band and rain gauges. It will be shown that rainfall rates and accumulations estimated from specific differential phase measurements (KDP) at X-band are in good agreement with the measurements from the gauge network during heavy rain and rain/hail mixture events. The X-band radar measurements also were generally successful in capturing the high spatial variability in convective rainfall, which caused post-fire debris flows.

System Concepts for the Advanced Post-TRMM Rainfall Profiling Radars

NASA Technical Reports Server (NTRS)

Im, Eastwood; Smith, Eric A.

2000-01-01

Global rainfall is the primary distributor of latent heat through atmospheric circulation. The recently launched Tropical Rainfall Measuring Mission satellite is dedicated to advance our understanding of tropical precipitation patterns and their implications on global climate and its change. The Precipitation Radar (PR) aboard the satellite is the first radar ever flown in space and has provided. exciting, new data on the 3-D rain structures for a variety of scientific uses. However, due to the limited mission lifetime and the dynamical nature of precipitation, the TRMM PR data acquired cannot address all the issues associated with precipitation, its related processes, and the long-term climate variability. In fact, a number of new post-TRMM mission concepts have emerged in response to the recent NASA's request for new ideas on Earth science missions at the post 2002 era. This paper will discuss the system concepts for two advanced, spaceborne rainfall profiling radars. In the first portion of this paper, we will present a system concept for a second-generation spaceborne precipitation radar for operations at the Low Earth Orbit (LEO). The key PR-2 electronics system will possess the following capabilities: (1) A 13.6/35 GHz dual frequency radar electronics that has Doppler and dual-polarization capabilities. (2) A large but light weight, dual-frequency, wide-swath scanning, deployable antenna. (3) Digital chirp generation and the corresponding on-board pulse compression scheme. This will allow a significant improvement on rain signal detection without using the traditional, high-peak-power transmitters and without sacrificing the range resolution. (4) Radar electronics and algorithm to adaptively scan the antenna so that more time can be spent to observe rain rather than clear air. and (5) Built-in flexibility on the radar parameters and timing control such that the same radar can be used by different future rain missions. This will help to reduce the overall instrument development costs. In the second portion of this paper, we will present a system concept for a geostationary rainfall monitoring radar for operations at the geosynchronous Earth Orbit (GEO). In particular, the science requirements, the observational strategy, the instrument design, and the required technologies will be discussed.

Quantifying Airborne Allergen Levels Before and After Rain Events Using TRMM/GPM and Ground-Sampled Data

NASA Technical Reports Server (NTRS)

Stewart, Randy M.

2006-01-01

Allergies affect millions of Americans, increasing health risks and also increasing absenteeism and reducing productivity in the workplace. Outdoor allergens, such as airborne pollens and mold spores, commonly trigger respiratory distress symptoms, but rainfall reduces the quantity of allergens in the air (EPA, 2003). The current NASA Tropical Rainfall Measuring Mission provides accurate information related to rain events. These capabilities will be further enhanced with the future Global Precipitation Measurement mission. This report examines the effectiveness of combining these NASA resources with established ground-based allergen/spore sampling systems to better understand the benefits that rain provides in removing allergens and spores from the air.

Comprehensive evaluation of Ensemble Multi-Satellite Precipitation Dataset using the Dynamic Bayesian Model Averaging scheme over the Tibetan plateau

NASA Astrophysics Data System (ADS)

Ma, Yingzhao; Yang, Yuan; Han, Zhongying; Tang, Guoqiang; Maguire, Lane; Chu, Zhigang; Hong, Yang

2018-01-01

The objective of this study is to comprehensively evaluate the new Ensemble Multi-Satellite Precipitation Dataset using the Dynamic Bayesian Model Averaging scheme (EMSPD-DBMA) at daily and 0.25° scales from 2001 to 2015 over the Tibetan Plateau (TP). Error analysis against gauge observations revealed that EMSPD-DBMA captured the spatiotemporal pattern of daily precipitation with an acceptable Correlation Coefficient (CC) of 0.53 and a Relative Bias (RB) of -8.28%. Moreover, EMSPD-DBMA outperformed IMERG and GSMaP-MVK in almost all metrics in the summers of 2014 and 2015, with the lowest RB and Root Mean Square Error (RMSE) values of -2.88% and 8.01 mm/d, respectively. It also better reproduced the Probability Density Function (PDF) in terms of daily rainfall amount and estimated moderate and heavy rainfall better than both IMERG and GSMaP-MVK. Further, hydrological evaluation with the Coupled Routing and Excess STorage (CREST) model in the Upper Yangtze River region indicated that the EMSPD-DBMA forced simulation showed satisfying hydrological performance in terms of streamflow prediction, with Nash-Sutcliffe coefficient of Efficiency (NSE) values of 0.82 and 0.58, compared to gauge forced simulation (0.88 and 0.60) at the calibration and validation periods, respectively. EMSPD-DBMA also performed a greater fitness for peak flow simulation than a new Multi-Source Weighted-Ensemble Precipitation Version 2 (MSWEP V2) product, indicating a promising prospect of hydrological utility for the ensemble satellite precipitation data. This study belongs to early comprehensive evaluation of the blended multi-satellite precipitation data across the TP, which would be significant for improving the DBMA algorithm in regions with complex terrain.

Enhanced object-based tracking algorithm for convective rain storms and cells

NASA Astrophysics Data System (ADS)

Muñoz, Carlos; Wang, Li-Pen; Willems, Patrick

2018-03-01

This paper proposes a new object-based storm tracking algorithm, based upon TITAN (Thunderstorm Identification, Tracking, Analysis and Nowcasting). TITAN is a widely-used convective storm tracking algorithm but has limitations in handling small-scale yet high-intensity storm entities due to its single-threshold identification approach. It also has difficulties to effectively track fast-moving storms because of the employed matching approach that largely relies on the overlapping areas between successive storm entities. To address these deficiencies, a number of modifications are proposed and tested in this paper. These include a two-stage multi-threshold storm identification, a new formulation for characterizing storm's physical features, and an enhanced matching technique in synergy with an optical-flow storm field tracker, as well as, according to these modifications, a more complex merging and splitting scheme. High-resolution (5-min and 529-m) radar reflectivity data for 18 storm events over Belgium are used to calibrate and evaluate the algorithm. The performance of the proposed algorithm is compared with that of the original TITAN. The results suggest that the proposed algorithm can better isolate and match convective rainfall entities, as well as to provide more reliable and detailed motion estimates. Furthermore, the improvement is found to be more significant for higher rainfall intensities. The new algorithm has the potential to serve as a basis for further applications, such as storm nowcasting and long-term stochastic spatial and temporal rainfall generation.

The exceptionally wet year of 2014 over Greece: a statistical and synoptical-atmospheric analysis over the region of Thessaloniki

NASA Astrophysics Data System (ADS)

Tolika, Konstantia; Maheras, Panagiotis; Anagnostopoulou, Christina

2018-05-01

The highest rainfall totals (912.2 mm) and the largest number of raindays (133 days), since 1958, were recorded in Thessaloniki during the year of 2014. Extreme precipitation heights were also observed on a seasonal, monthly and daily basis. The examined year presented the highest daily rainfall intensity, the maximum daily precipitation and the largest number of heavy precipitation days (greater than 10 mm), and it also exceeded the previous amounts of precipitation of very wet (95th percentile) and extremely wet (99th percentile) days. According to the automatic circulation type classification scheme that was used, it was found that during this exceptionally wet year, the frequency of occurrence of cyclonic types at the near surface geopotential level increases, while the same types decreased at a higher atmospheric level (500 hPa). The prevailing type was type C which is located at the centre of the study area (Greece), but several other cyclonic types changed during this year not only their frequency but also their percentage of rainfall as well as their daily precipitation intensity. It should be highlighted that these findings differentiated on the seasonal-scale analysis. Moreover, out of the three teleconnection patterns that were examined (Scandinavian Pattern, Eastern Mediterranean Teleconnection Pattern and North Sea-Caspian Pattern), the Scandinavian one (SCAND) was detected during the most of the months of 2014 meaning that it was highly associated with intense precipitation over Greece.

The Diurnal Cycle in TOGA-COARE: Regional Scale Model Simulations

NASA Technical Reports Server (NTRS)

Tao, W.-K.; Jia, Y.

1999-01-01

The diurnal variation of precipitation processes over the tropics is a well-known phenomenon and has been studied using surface rainfall data, radar reflectivity data, and satellite-derived cloudiness and precipitation. Recently, analyzed observations from Tropical Oceans and Global Atmosphere Coupled Ocean-Atmosphere Response Experiment (TOGA COARE) in the tropical western Pacific ocean to study the relevant mechanisms producing diurnal variation of precipitation. They found that the diurnal Sea surface temperature (SST) cycle is important for afternoon showers in the undisturbed periods and diurnal radiative processes for nocturnal rainfall. Cloud resolving models (CRMS) have been used to determine the mechanisms associated with diurnal variation of precipitating processes. CRMs allow explicit cloud-radiation and air-sea interactive processes. However, CRMs can be only used for idealized simulations (i.e., no feedback between clouds and their embedded large-scale environments; cyclic lateral boundary conditions and idealized initial conditions). In this study, the Penn State/NCAR Mesoscale Model (MM5) with improved physics (i.e., cloud microphysics, radiation, land-soil-vegetation-surface processes, and TOGA COARE flux scheme) and a multiple level nesting technique (covers the TOGA COARE LSA/IFA with a 54 km grid and can nest down to 18, 6 and possibly even 2 km) will be adopted for studying the diurnal variations of rainfall. We will examine precipitation processes over open ocean and over land. We will also perform sensitivity tests to determine how the radiative forcing and diurnal SST cycle affects the development of convection.

Rainfall, Discharge, and Water-Quality Data During Stormwater Monitoring, July 1, 2007, to June 30, 2008; Halawa Stream Drainage Basin and the H-1 Storm Drain, Oahu, Hawaii

USGS Publications Warehouse

Presley, Todd K.; Jamison, Marcael T.J.; Young, Stacie T.M.

2008-01-01

Storm runoff water-quality samples were collected as part of the State of Hawaii Department of Transportation Stormwater Monitoring Program. The program is designed to assess the effects of highway runoff and urban runoff on Halawa Stream and to assess the effects from the H-1 storm drain on Manoa Stream. For this program, rainfall data were collected at three stations, continuous discharge data at four stations, and water-quality data at six stations, which include the four continuous discharge stations. This report summarizes rainfall, discharge, and water-quality data collected between July 1, 2007, and June 30, 2008. A total of 16 environmental samples were collected over two storms during July 1, 2007, to June 30, 2008, within the Halawa Stream drainage area. Samples were analyzed for total suspended solids, total dissolved solids, nutrients, chemical oxygen demand, and selected trace metals (cadmium, chromium, copper, lead, and zinc). Additionally, grab samples were analyzed for oil and grease, total petroleum hydrocarbons, fecal coliform, and biological oxygen demand. Some samples were analyzed for only a partial list of these analytes because an insufficient volume of sample was collected by the automatic samplers. Three additional quality-assurance/quality-control samples were collected concurrently with the storm samples. A total of 16 environmental samples were collected over four storms during July 1, 2007, to June 30, 2008 at the H-1 Storm Drain. All samples at this site were collected using an automatic sampler. Samples generally were analyzed for total suspended solids, nutrients, chemical oxygen demand, oil and grease, total petroleum hydrocarbons, and selected trace metals (cadmium, chromium, copper, lead, nickel, and zinc), although some samples were analyzed for only a partial list of these analytes. During the storm of January 29, 2008, 10 discrete samples were collected. Varying constituent concentrations were detected for the samples collected at different times during this storm event. Two quality-assurance/quality-control samples were collected concurrently with the storm samples. Three additional quality-assurance/quality-control samples were collected during routine sampler maintenance to check the effectiveness of equipment-cleaning procedures.

Overview: Precipitation characteristics and sensitivities to environmental conditions during GoAmazon2014/5 and ACRIDICON-CHUVA

DOE PAGES

Machado, Luiz A. T.; Calheiros, Alan J. P.; Biscaro, Thiago; ...

2018-05-07

This study provides an overview of precipitation processes and their sensitivities to environmental conditions in the Central Amazon Basin near Manaus during the GoAmazon2014/5 and ACRIDICON-CHUVA experiments. Here, this study takes advantage of the numerous measurement platforms and instrument systems operating during both campaigns to sample cloud structure and environmental conditions during 2014 and 2015; the rainfall variability among seasons, aerosol loading, land surface type, and topography has been carefully characterized using these data. Differences between the wet and dry seasons were examined from a variety of perspectives. The rainfall rates distribution, total amount of rainfall, and raindrop size distribution (the mass-weightedmore » mean diameter) were quantified over both seasons. The dry season generally exhibited higher rainfall rates than the wet season and included more intense rainfall periods. However, the cumulative rainfall during the wet season was 4 times greater than that during the total dry season rainfall, as shown in the total rainfall accumulation data. The typical size and life cycle of Amazon cloud clusters (observed by satellite) and rain cells (observed by radar) were examined, as were differences in these systems between the seasons. Moreover, monthly mean thermodynamic and dynamic variables were analysed using radiosondes to elucidate the differences in rainfall characteristics during the wet and dry seasons. The sensitivity of rainfall to atmospheric aerosol loading was discussed with regard to mass-weighted mean diameter and rain rate. This topic was evaluated only during the wet season due to the insignificant statistics of rainfall events for different aerosol loading ranges and the low frequency of precipitation events during the dry season. The impacts of aerosols on cloud droplet diameter varied based on droplet size. For the wet season, we observed no dependence between land surface type and rain rate. However, during the dry season, urban areas exhibited the largest rainfall rate tail distribution, and deforested regions exhibited the lowest mean rainfall rate. Airplane measurements were taken to characterize and contrast cloud microphysical properties and processes over forested and deforested regions. Vertical motion was not correlated with cloud droplet sizes, but cloud droplet concentration correlated linearly with vertical motion. Clouds over forested areas contained larger droplets than clouds over pastures at all altitudes. Finally, the connections between topography and rain rate were evaluated, with higher rainfall rates identified at higher elevations during the dry season.« less

Overview: Precipitation characteristics and sensitivities to environmental conditions during GoAmazon2014/5 and ACRIDICON-CHUVA

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

Machado, Luiz A. T.; Calheiros, Alan J. P.; Biscaro, Thiago

This study provides an overview of precipitation processes and their sensitivities to environmental conditions in the Central Amazon Basin near Manaus during the GoAmazon2014/5 and ACRIDICON-CHUVA experiments. Here, this study takes advantage of the numerous measurement platforms and instrument systems operating during both campaigns to sample cloud structure and environmental conditions during 2014 and 2015; the rainfall variability among seasons, aerosol loading, land surface type, and topography has been carefully characterized using these data. Differences between the wet and dry seasons were examined from a variety of perspectives. The rainfall rates distribution, total amount of rainfall, and raindrop size distribution (the mass-weightedmore » mean diameter) were quantified over both seasons. The dry season generally exhibited higher rainfall rates than the wet season and included more intense rainfall periods. However, the cumulative rainfall during the wet season was 4 times greater than that during the total dry season rainfall, as shown in the total rainfall accumulation data. The typical size and life cycle of Amazon cloud clusters (observed by satellite) and rain cells (observed by radar) were examined, as were differences in these systems between the seasons. Moreover, monthly mean thermodynamic and dynamic variables were analysed using radiosondes to elucidate the differences in rainfall characteristics during the wet and dry seasons. The sensitivity of rainfall to atmospheric aerosol loading was discussed with regard to mass-weighted mean diameter and rain rate. This topic was evaluated only during the wet season due to the insignificant statistics of rainfall events for different aerosol loading ranges and the low frequency of precipitation events during the dry season. The impacts of aerosols on cloud droplet diameter varied based on droplet size. For the wet season, we observed no dependence between land surface type and rain rate. However, during the dry season, urban areas exhibited the largest rainfall rate tail distribution, and deforested regions exhibited the lowest mean rainfall rate. Airplane measurements were taken to characterize and contrast cloud microphysical properties and processes over forested and deforested regions. Vertical motion was not correlated with cloud droplet sizes, but cloud droplet concentration correlated linearly with vertical motion. Clouds over forested areas contained larger droplets than clouds over pastures at all altitudes. Finally, the connections between topography and rain rate were evaluated, with higher rainfall rates identified at higher elevations during the dry season.« less

A framework for probabilistic pluvial flood nowcasting for urban areas

NASA Astrophysics Data System (ADS)

Ntegeka, Victor; Murla, Damian; Wang, Lipen; Foresti, Loris; Reyniers, Maarten; Delobbe, Laurent; Van Herk, Kristine; Van Ootegem, Luc; Willems, Patrick

2016-04-01

Pluvial flood nowcasting is gaining ground not least because of the advancements in rainfall forecasting schemes. Short-term forecasts and applications have benefited from the availability of such forecasts with high resolution in space (~1km) and time (~5min). In this regard, it is vital to evaluate the potential of nowcasting products for urban inundation applications. One of the most advanced Quantitative Precipitation Forecasting (QPF) techniques is the Short-Term Ensemble Prediction System, which was originally co-developed by the UK Met Office and Australian Bureau of Meteorology. The scheme was further tuned to better estimate extreme and moderate events for the Belgian area (STEPS-BE). Against this backdrop, a probabilistic framework has been developed that consists of: (1) rainfall nowcasts; (2) sewer hydraulic model; (3) flood damage estimation; and (4) urban inundation risk mapping. STEPS-BE forecasts are provided at high resolution (1km/5min) with 20 ensemble members with a lead time of up to 2 hours using a 4 C-band radar composite as input. Forecasts' verification was performed over the cities of Leuven and Ghent and biases were found to be small. The hydraulic model consists of the 1D sewer network and an innovative 'nested' 2D surface model to model 2D urban surface inundations at high resolution. The surface components are categorized into three groups and each group is modelled using triangular meshes at different resolutions; these include streets (3.75 - 15 m2), high flood hazard areas (12.5 - 50 m2) and low flood hazard areas (75 - 300 m2). Functions describing urban flood damage and social consequences were empirically derived based on questionnaires to people in the region that were recently affected by sewer floods. Probabilistic urban flood risk maps were prepared based on spatial interpolation techniques of flood inundation. The method has been implemented and tested for the villages Oostakker and Sint-Amandsberg, which are part of the larger city of Gent, Belgium. After each of the different above-mentioned components were evaluated, they were combined and tested for recent historical flood events. The rainfall nowcasting, hydraulic sewer and 2D inundation modelling and socio-economical flood risk results each could be partly evaluated: the rainfall nowcasting results based on radar data and rain gauges; the hydraulic sewer model results based on water level and discharge data at pumping stations; the 2D inundation modelling results based on limited data on some recent flood locations and inundation depths; the results for the socio-economical flood consequences of the most extreme events based on claims in the database of the national disaster agency. Different methods for visualization of the probabilistic inundation results are proposed and tested.

Cesium and strontium loads into a combined sewer system from rainwater runoff.

PubMed

Kamei-Ishikawa, Nao; Yoshida, Daiki; Ito, Ayumi; Umita, Teruyuki

2016-12-01

In this study, combined sewage samples were taken with time in several rain events and sanitary sewage samples were taken with time in dry weather to calculate Cs and Sr loads to sewers from rainwater runoff. Cs and Sr in rainwater were present as particulate forms at first flush and the particulate Cs and Sr were mainly bound with inorganic suspended solids such as clay minerals in combined sewage samples. In addition, multiple linear regression analysis showed Cs and Sr loads from rainwater runoff could be estimated by the total amount of rainfall and antecedent dry weather days. The variation of the Sr load from rainwater to sewers was more sensitive to total amount of rainfall and antecedent dry weather days than that of the Cs load. Copyright © 2016 Elsevier Ltd. All rights reserved.

Errors and uncertainties in regional climate simulations of rainfall variability over Tunisia: a multi-model and multi-member approach

NASA Astrophysics Data System (ADS)

Fathalli, Bilel; Pohl, Benjamin; Castel, Thierry; Safi, Mohamed Jomâa

2018-02-01

Temporal and spatial variability of rainfall over Tunisia (at 12 km spatial resolution) is analyzed in a multi-year (1992-2011) ten-member ensemble simulation performed using the WRF model, and a sample of regional climate hindcast simulations from Euro-CORDEX. RCM errors and skills are evaluated against a dense network of local rain gauges. Uncertainties arising, on the one hand, from the different model configurations and, on the other hand, from internal variability are furthermore quantified and ranked at different timescales using simple spread metrics. Overall, the WRF simulation shows good skill for simulating spatial patterns of rainfall amounts over Tunisia, marked by strong altitudinal and latitudinal gradients, as well as the rainfall interannual variability, in spite of systematic errors. Mean rainfall biases are wet in both DJF and JJA seasons for the WRF ensemble, while they are dry in winter and wet in summer for most of the used Euro-CORDEX models. The sign of mean annual rainfall biases over Tunisia can also change from one member of the WRF ensemble to another. Skills in regionalizing precipitation over Tunisia are season dependent, with better correlations and weaker biases in winter. Larger inter-member spreads are observed in summer, likely because of (1) an attenuated large-scale control on Mediterranean and Tunisian climate, and (2) a larger contribution of local convective rainfall to the seasonal amounts. Inter-model uncertainties are globally stronger than those attributed to model's internal variability. However, inter-member spreads can be of the same magnitude in summer, emphasizing the important stochastic nature of the summertime rainfall variability over Tunisia.

Erodibility of waste (Loess) soils from construction sites under water and wind erosional forces.

PubMed

Tanner, Smadar; Katra, Itzhak; Argaman, Eli; Ben-Hur, Meni

2018-03-01

Excess soils from construction sites (waste soils) become a problem when exposed to soil erosion by water or wind. Understanding waste soil erodibility can contribute to its proper reuse for various surface applications. The general objective of the study was to provide a better understanding of the effects of soil properties on erodibility of waste soils excavated from various depths in a semiarid region under rainfall and wind erosive forces. Soil samples excavated from the topsoil (0-0.3m) and subsoil layers (0.3-0.9 and >1m depths) were subjected to simulated rainfall and wind. Under rainfall erosive forces, the subsoils were more erodible than the topsoil, in contrast to the results obtained under wind erosive forces. Exchangeable sodium percentage was the main factor controlling soil erodibility (K i ) under rainfall, and a significant logarithmic regression line was found between these two parameters. In addition, a significant, linear regression was found between K i and slaking values for the studied soil samples, suggesting that the former can be predicted from the latter. Soil erodibility under wind erosion force was controlled mainly by the dry aggregate characteristics (mean weight diameter and aggregate density): their higher values in the subsoil layers resulted in lower soil erodibility compared to the topsoil. Copyright © 2017 Elsevier B.V. All rights reserved.

RAINDROP DISTRIBUTIONS AT MAJURO ATOLL, MARSHALL ISLANDS.

DTIC Science & Technology

RAINDROPS, MARSHALL ISLANDS), (*ATMOSPHERIC PRECIPITATION, TROPICAL REGIONS), PARTICLE SIZE, SAMPLING, TABLES(DATA), WATER , ATTENUATION, DISTRIBUTION, VOLUME, RADAR REFLECTIONS, RAINFALL, PHOTOGRAPHIC ANALYSIS, COMPUTERS

Analysis of one dimension migration law from rainfall runoff on urban roof

NASA Astrophysics Data System (ADS)

Weiwei, Chen

2017-08-01

Research was taken on the hydrology and water quality process in the natural rain condition and water samples were collected and analyzed. The pollutant were included SS, COD and TN. Based on the mass balance principle, one dimension migration model was built for the rainfall runoff pollution in surface. The difference equation was developed according to the finite difference method, by applying the Newton iteration method for solving it. The simulated pollutant concentration process was in consistent with the measured value on model, and Nash-Sutcliffe coefficient was higher than 0.80. The model had better practicability, which provided evidence for effectively utilizing urban rainfall resource, non-point source pollution of making management technologies and measures, sponge city construction, and so on.

Radar volume reflectivity estimation using an array of ground-based rainfall drop size detectors

NASA Astrophysics Data System (ADS)

Lane, John; Merceret, Francis; Kasparis, Takis; Roy, D.; Muller, Brad; Jones, W. Linwood

2000-08-01

Rainfall drop size distribution (DSD) measurements made by single disdrometers at isolated ground sites have traditionally been used to estimate the transformation between weather radar reflectivity Z and rainfall rate R. Despite the immense disparity in sampling geometries, the resulting Z-R relation obtained by these single point measurements has historically been important in the study of applied radar meteorology. Simultaneous DSD measurements made at several ground sites within a microscale area may be used to improve the estimate of radar reflectivity in the air volume surrounding the disdrometer array. By applying the equations of motion for non-interacting hydrometers, a volume estimate of Z is obtained from the array of ground based disdrometers by first calculating a 3D drop size distribution. The 3D-DSD model assumes that only gravity and terminal velocity due to atmospheric drag within the sampling volume influence hydrometer dynamics. The sampling volume is characterized by wind velocities, which are input parameters to the 3D-DSD model, composed of vertical and horizontal components. Reflectivity data from four consecutive WSR-88D volume scans, acquired during a thunderstorm near Melbourne, FL on June 1, 1997, are compared to data processed using the 3D-DSD model and data form three ground based disdrometers of a microscale array.

Tropical Mosquito Assemblages Demonstrate ‘Textbook’ Annual Cycles

PubMed Central

Franklin, Donald C.; Whelan, Peter I.

2009-01-01

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

Trench 'bathtubbing' and surface plutonium contamination at a legacy radioactive waste site.

PubMed

Payne, Timothy E; Harrison, Jennifer J; Hughes, Catherine E; Johansen, Mathew P; Thiruvoth, Sangeeth; Wilsher, Kerry L; Cendón, Dioni I; Hankin, Stuart I; Rowling, Brett; Zawadzki, Atun

2013-01-01

Radioactive waste containing a few grams of plutonium (Pu) was disposed between 1960 and 1968 in trenches at the Little Forest Burial Ground (LFBG), near Sydney, Australia. A water sampling point installed in a former trench has enabled the radionuclide content of trench water and the response of the water level to rainfall to be studied. The trench water contains readily measurable Pu activity (~12 Bq/L of (239+240)Pu in 0.45 μm-filtered water), and there is an associated contamination of Pu in surface soils. The highest (239+240)Pu soil activity was 829 Bq/kg in a shallow sample (0-1 cm depth) near the trench sampling point. Away from the trenches, the elevated concentrations of Pu in surface soils extend for tens of meters down-slope. The broader contamination may be partly attributable to dispersion events in the first decade after disposal, after which a layer of soil was added above the trenched area. Since this time, further Pu contamination has occurred near the trench-sampler within this added layer. The water level in the trench-sampler responds quickly to rainfall and intermittently reaches the surface, hence the Pu dispersion is attributed to saturation and overflow of the trenches during extreme rainfall events, referred to as the 'bathtub' effect.

Relating rainfall characteristics to cloud top temperatures at different scales

NASA Astrophysics Data System (ADS)

Klein, Cornelia; Belušić, Danijel; Taylor, Christopher

2017-04-01

Extreme rainfall from mesoscale convective systems (MCS) poses a threat to lives and livelihoods of the West African population through increasingly frequent devastating flooding and loss of crops. However, despite the significant impact of such extreme events, the dominant processes favouring their occurrence are still under debate. In the data-sparse West African region, rainfall radar data from the Tropical Rainfall Measuring Mission (TRMM) gives invaluable information on the distribution and frequency of extreme rainfall. The TRMM 2A25 product provides a 15-year dataset of snapshots of surface rainfall from 2-4 overpasses per day. Whilst this sampling captures the overall rainfall characteristics, it is neither long nor frequent enough to diagnose changes in MCS properties, which may be linked to the trend towards rainfall intensification in the region. On the other hand, Meteosat geostationary satellites provide long-term sub-hourly records of cloud top temperatures, raising the possibility of combining these with the high-quality rainfall data from TRMM. In this study, we relate TRMM 2A25 rainfall to Meteosat Second Generation (MSG) cloud top temperatures, which are available from 2004 at 15 minutes intervals, to get a more detailed picture of the structure of intense rainfall within the life cycle of MCS. We find TRMM rainfall intensities within an MCS to be strongly coupled with MSG cloud top temperatures: the probability for extreme rainfall increases from <10% for minimum temperatures warmer than -40°C to over 70% when temperatures drop below -70°C, confirming the potential in analysing cloud-top temperatures as a proxy for extreme rain. The sheer size of MCS raises the question which scales of sub-cloud structures are more likely to be associated with extreme rain than others. In the end, this information could help to associate scale changes in cloud top temperatures with processes that affect the probability of extreme rain. We use 2D continuous wavelets to decompose cloud top temperatures into power spectra at scales between 15 and 200km. From these, cloud sub-structures are identified as circular areas of respective scale with local power maxima in their centre. These areas are then mapped onto coinciding TRMM rainfall, allowing us to assign rainfall fields to sub-cloud features of different scales. We find a higher probability for extreme rainfall for cloud features above a scale of 30km, with features 100km contributing most to the number of extreme rainfall pixels. Over the average diurnal cycle, the number of smaller cloud features between 15-60km shows an increase between 15 - 1700UTC, gradually developing into larger ones. The maximum of extreme rainfall pixels around 1900UTC coincides with a peak for scales 100km, suggesting a dominant role of these scales for intense rain for the analysed cloud type. Our results demonstrate the suitability of 2D wavelet decomposition for the analysis of sub-cloud structures and their relation to rainfall characteristics, and help us to understand long-term changes in the properties of MCS.

Multiple regression and Artificial Neural Network for long-term rainfall forecasting using large scale climate modes

NASA Astrophysics Data System (ADS)

Mekanik, F.; Imteaz, M. A.; Gato-Trinidad, S.; Elmahdi, A.

2013-10-01

In this study, the application of Artificial Neural Networks (ANN) and Multiple regression analysis (MR) to forecast long-term seasonal spring rainfall in Victoria, Australia was investigated using lagged El Nino Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) as potential predictors. The use of dual (combined lagged ENSO-IOD) input sets for calibrating and validating ANN and MR Models is proposed to investigate the simultaneous effect of past values of these two major climate modes on long-term spring rainfall prediction. The MR models that did not violate the limits of statistical significance and multicollinearity were selected for future spring rainfall forecast. The ANN was developed in the form of multilayer perceptron using Levenberg-Marquardt algorithm. Both MR and ANN modelling were assessed statistically using mean square error (MSE), mean absolute error (MAE), Pearson correlation (r) and Willmott index of agreement (d). The developed MR and ANN models were tested on out-of-sample test sets; the MR models showed very poor generalisation ability for east Victoria with correlation coefficients of -0.99 to -0.90 compared to ANN with correlation coefficients of 0.42-0.93; ANN models also showed better generalisation ability for central and west Victoria with correlation coefficients of 0.68-0.85 and 0.58-0.97 respectively. The ability of multiple regression models to forecast out-of-sample sets is compatible with ANN for Daylesford in central Victoria and Kaniva in west Victoria (r = 0.92 and 0.67 respectively). The errors of the testing sets for ANN models are generally lower compared to multiple regression models. The statistical analysis suggest the potential of ANN over MR models for rainfall forecasting using large scale climate modes.

Methods, quality assurance, and data for assessing atmospheric deposition of pesticides in the Central Valley of California

USGS Publications Warehouse

Zamora, Celia; Majewski, Michael S.; Foreman, William T.

2013-01-01

The U.S. Geological Survey monitored atmospheric deposition of pesticides in the Central Valley of California during two studies in 2001 and 2002–04. The 2001 study sampled wet deposition (rain) and storm-drain runoff in the Modesto, California, area during the orchard dormant-spray season to examine the contribution of pesticide concentrations to storm runoff from rainfall. In the 2002–04 study, the number and extent of collection sites in the Central Valley were increased to determine the areal distribution of organophosphate insecticides and other pesticides, and also five more sample types were collected. These were dry deposition, bulk deposition, and three sample types collected from a soil box: aqueous phase in runoff, suspended sediment in runoff, and surficial-soil samples. This report provides concentration data and describes methods and quality assurance of sample collection and laboratory analysis for pesticide compounds in all samples collected from 16 sites. Each sample was analyzed for 41 currently used pesticides and 23 pesticide degradates, including oxygen analogs (oxons) of 9 organophosphate insecticides. Analytical results are presented by sample type and study period. The median concentrations of both chloryprifos and diazinon sampled at four urban (0.067 micrograms per liter [μg/L] and 0.515 μg/L, respectively) and four agricultural sites (0.079 μg/L and 0.583 μg/L, respectively) during a January 2001 storm event in and around Modesto, Calif., were nearly identical, indicating that the overall atmospheric burden in the region appeared to be fairly similar during the sampling event. Comparisons of median concentrations in the rainfall to those in the McHenry storm-drain runoff showed that, for some compounds, rainfall contributed a substantial percentage of the concentration in the runoff; for other compounds, the concentrations in rainfall were much greater than in the runoff. For example, diazinon concentrations in rainfall were about 70 percent of the diazinon concentration in the runoff, whereas the chlorpyrifos concentration in the rain was 1.8 times greater than in the runoff. The more water-soluble pesticides—carbaryl, metolachlor, napropamide, and simazine—followed the same pattern as diazinon and had lower concentrations in rain compared to runoff. Similar to chlorpyrifos,compounds with low water solubilities and higher soil-organic carbon partition coefficients, including dacthal, pendimethalin, and trifluralin, were found to have higher concentrations in rain than in runoff water and were presumed to partition to the suspended sediments and organic matter on the ground. During the 2002–04 study period, the herbicide dacthal had the highest detection frequencies for all sample types collected from the Central Valley sites (67–100 percent). The most frequently detected compounds in the wet-deposition samples were dacthal, diazinon, chlorpyrifos, and simazine (greater than 90 percent). The median wet-deposition amounts for these compounds were 0.044 micrograms per square meter per day (μg/m2/day), 0.209 μg/m2/day, 0.079 μg/m2/day, and 0.172 μg/m2/day, respectively. For the dry-deposition samples, detection frequencies were greater than 73 percent for the compounds dacthal, metolachor, and chlorpyrifos, and median deposition amounts were an order of magnitude less than for wet deposition. The differences between wet deposition and dry deposition appeared to be closely related to the Henry’s Law (H) constant of each compound, although the mass deposited by dry deposition takes place over a much longer time frame. Pesticides detected in rainfall usually were detected in the aqueous phase of the soil-box runoff water, and the runoff concentrations were generally similar to those in the rainfall. For compounds detected in the aqueous phase and suspended-sediment samples of soil-box runoff, concentrations of pesticides in the aqueous phase generally were detected in low concentrations and had few corresponding detections in the suspended- sediment samples. Dacthal, diazinon, chlorpyrifos, and simazine were the most frequently detected pesticides (greater than 83 percent) in the aqueous-phase samples, with median concentrations of 0.010 μg/L, 0.045 μg/L, 0.016 μg/L, and 0.077 μg/L, respectively. Simazine was the most frequently detected compound in the suspended-sediment samples (69 percent), with a median concentration of 0.232 μg/L. Results for compounds detected in the surficial-soil samples collected throughout the study period showed that there was an increase in concentration for some compounds, indicating atmospheric deposition of these compounds onto the soil-box surface. In the San Joaquin Valley, the compounds chlorpyrifos, dacthal, and iprodione were detected at higher concentrations (between 1.4 and 2 times greater) than were found in the background samples collected from the San Joaquin Valley soil-box sites. In the Sacramento Valley, the compounds chlorpyrifos, dacthal, iprodione, parathionmethyl, and its oxygen analog, paraoxon-methyl, were detected in samples collected during the study period in low concentrations, but were not detected in the background concentration of the Sacramento Valley soil mix.

Should Bouchet's hypothesis be taken into account in rainfall-runoff modelling? An assessment over 308 catchments

NASA Astrophysics Data System (ADS)

Oudin, Ludovic; Michel, Claude; Andréassian, Vazken; Anctil, François; Loumagne, Cécile

2005-12-01

An implementation of the complementary relationship hypothesis (Bouchet's hypothesis) for estimating regional evapotranspiration within two rainfall-runoff models is proposed and evaluated in terms of streamflow simulation efficiency over a large sample of 308 catchments located in Australia, France and the USA. Complementary relationship models are attractive approaches to estimating actual evapotranspiration because they rely solely on climatic variables. They are even more interesting since they are supported by a conceptual description underlying the interactions between the evapotranspirating surface and the atmospheric boundary layer, which was highlighted by Bouchet (1963). However, these approaches appear to be in contradiction with the methods prevailing in rainfall-runoff models, which compute actual evapotranspiration using soil moisture accounting procedures. The approach adopted in this article is to introduce the estimation of actual evapotranspiration provided by complementary relationship models (complementary relationship for areal evapotranspiration and advection aridity) into two rainfall-runoff models. Results show that directly using the complementary relationship approach to estimate actual evapotranspiration does not give better results than the soil moisture accounting procedures. Finally, we discuss feedback mechanisms between potential evapotranspiration and soil water availability, and their possible impact on rainfall-runoff modelling. Copyright

Monthly variability and possible sources of nitrate in ground water beneath mixed agricultural land use, Suwannee and Lafayette Counties, Florida

USGS Publications Warehouse

Katz, Brian G.; Böhlke, J.K.

2000-01-01

In an area of mixed agricultural land use in Suwannee and Lafayette Counties of northern Florida, water samples were collected monthly from 14 wells tapping the Upper Floridan aquifer during July 1998 through June 1999 to assess hydrologic and land-use factors affecting the variability in nitrate concentrations in ground water. Unusually high amounts of rainfall in September and October 1998 (43.5 centimeters total for both months) resulted in an increase in water levels in all wells in October 1998. This was followed by unusually low amounts of rainfall during November 1998 through May 1999, when rainfall was 40.7 centimeters below 30-year mean monthly values. The presence of karst features (sinkholes, springs, solution conduits) and the highly permeable sands that overlie the Upper Floridan aquifer provide for rapid movement of water containing elevated nitrate concentrations to the aquifer. Nitrate was the dominant form of nitrogen in ground water collected at all sites and nitrate concentrations ranged from less than 0.02 to 22 milligrams per liter (mg/L), as nitrogen. Water samples from most wells showed substantial monthly or seasonal fluctuations in nitrate concentrations. Generally, water samples from wells with nitrate concentrations higher than 10 mg/L showed the greatest amount of monthly fluctuation. For example, water samples from six of eight wells had monthly nitrate concentrations that varied by at least 5 mg/L during the study period. Water from most wells with lower nitrate concentrations (less than 6 mg/L) also showed large monthly fluctuations. For instance, nitrate concentrations in water from four sites showed monthly variations of more than 50 percent. Large fluctuations in nitrate concentrations likely result from seasonal agricultural practices (fertilizer application and animal waste spreading) at a particular site. For example, an increase in nitrate concentrations observed in water samples from seven sites in February or March 1999 most likely results from application of synthetic fertilizers during the late winter months. Lower nitrate concentrations were detected in water samples from five of eight wells sampled during high-flow conditions for the Suwannee River in March 1998 compared to low-flow conditions in November 1998. Evidence for reduction of nitrate due to denitrification reactions was observed at one site (AC-1), as indicated by elevated concentrations of nitrogen gas and a corresponding increase in nitrogen isotope (d15N-NO3) values with a decrease in nitrate concentrations. Denitrification is unlikely at other sites based on the presence of dissolved oxygen concentrations greater than 2 mg/L in ground water and no observed trend between nitrate concentrations and values d15N-NO3 values. Nitrate was the dominant nitrogen species in most monthly rainfall samples; however, ammonium concentrations were similar or greater than nitrate during November and December 1998. During February through May 1999, both nitrate and ammonium concentrations were substantially higher in monthly rainfall samples collected at the study area compared to mean monthly concentrations at the Bradford Forest site located east of the study area, which is part of the National Atmospheric Deposition Program/National Trends Network. Also, higher nitrogen deposition rates in the study area compared to those at Bradford Forest could indicate that substantial amounts of ammonia are volatilized from fertilizers and animal wastes, released to the atmosphere, and incorporated as nitrate and ammonium in rainfall deposited in the middle Suwannee River Basin. Ground-water samples from most sites had d15N-NO3 values that indicated a mixture of inorganic and organic sources of nitrogen, which corresponded to multiple land uses where both synthetic fertilizers and manure are used on fields near these sites. Distinct d15N-NO3 signatures, however, were observed at some sites. For example, water samples from areas of row-crop farmin

Analyzing Hydraulic Conductivity Sampling Schemes in an Idealized Meandering Stream Model

NASA Astrophysics Data System (ADS)

Stonedahl, S. H.; Stonedahl, F.

2017-12-01

Hydraulic conductivity (K) is an important parameter affecting the flow of water through sediments under streams, which can vary by orders of magnitude within a stream reach. Measuring heterogeneous K distributions in the field is limited by time and resources. This study investigates hypothetical sampling practices within a modeling framework on a highly idealized meandering stream. We generated three sets of 100 hydraulic conductivity grids containing two sands with connectivity values of 0.02, 0.08, and 0.32. We investigated systems with twice as much fast (K=0.1 cm/s) sand as slow sand (K=0.01 cm/s) and the reverse ratio on the same grids. The K values did not vary with depth. For these 600 cases, we calculated the homogenous K value, Keq, that would yield the same flux into the sediments as the corresponding heterogeneous grid. We then investigated sampling schemes with six weighted probability distributions derived from the homogenous case: uniform, flow-paths, velocity, in-stream, flux-in, and flux-out. For each grid, we selected locations from these distributions and compared the arithmetic, geometric, and harmonic means of these lists to the corresponding Keq using the root-mean-square deviation. We found that arithmetic averaging of samples outperformed geometric or harmonic means for all sampling schemes. Of the sampling schemes, flux-in (sampling inside the stream in an inward flux-weighted manner) yielded the least error and flux-out yielded the most error. All three sampling schemes outside of the stream yielded very similar results. Grids with lower connectivity values (fewer and larger clusters) showed the most sensitivity to the choice of sampling scheme, and thus improved the most with the flux-insampling. We also explored the relationship between the number of samples taken and the resulting error. Increasing the number of sampling points reduced error for the arithmetic mean with diminishing returns, but did not substantially reduce error associated with geometric and harmonic means.

Improving Landslide Susceptibility Modeling Using an Empirical Threshold Scheme for Excluding Landslide Deposition

NASA Astrophysics Data System (ADS)

Tsai, F.; Lai, J. S.; Chiang, S. H.

2015-12-01

Landslides are frequently triggered by typhoons and earthquakes in Taiwan, causing serious economic losses and human casualties. Remotely sensed images and geo-spatial data consisting of land-cover and environmental information have been widely used for producing landslide inventories and causative factors for slope stability analysis. Landslide susceptibility, on the other hand, can represent the spatial likelihood of landslide occurrence and is an important basis for landslide risk assessment. As multi-temporal satellite images become popular and affordable, they are commonly used to generate landslide inventories for subsequent analysis. However, it is usually difficult to distinguish different landslide sub-regions (scarp, debris flow, deposition etc.) directly from remote sensing imagery. Consequently, the extracted landslide extents using image-based visual interpretation and automatic detections may contain many depositions that may reduce the fidelity of the landslide susceptibility model. This study developed an empirical thresholding scheme based on terrain characteristics for eliminating depositions from detected landslide areas to improve landslide susceptibility modeling. In this study, Bayesian network classifier is utilized to build a landslide susceptibility model and to predict sequent rainfall-induced shallow landslides in the Shimen reservoir watershed located in northern Taiwan. Eleven causative factors are considered, including terrain slope, aspect, curvature, elevation, geology, land-use, NDVI, soil, distance to fault, river and road. Landslide areas detected using satellite images acquired before and after eight typhoons between 2004 to 2008 are collected as the main inventory for training and verification. In the analysis, previous landslide events are used as training data to predict the samples of the next event. The results are then compared with recorded landslide areas in the inventory to evaluate the accuracy. Experimental results demonstrate that the accuracies of landslide susceptibility analysis in all sequential predictions have been improved significantly after eliminating landslide depositions.

Statistical Analysis for Collision-free Boson Sampling.

PubMed

Huang, He-Liang; Zhong, Han-Sen; Li, Tan; Li, Feng-Guang; Fu, Xiang-Qun; Zhang, Shuo; Wang, Xiang; Bao, Wan-Su

2017-11-10

Boson sampling is strongly believed to be intractable for classical computers but solvable with photons in linear optics, which raises widespread concern as a rapid way to demonstrate the quantum supremacy. However, due to its solution is mathematically unverifiable, how to certify the experimental results becomes a major difficulty in the boson sampling experiment. Here, we develop a statistical analysis scheme to experimentally certify the collision-free boson sampling. Numerical simulations are performed to show the feasibility and practicability of our scheme, and the effects of realistic experimental conditions are also considered, demonstrating that our proposed scheme is experimentally friendly. Moreover, our broad approach is expected to be generally applied to investigate multi-particle coherent dynamics beyond the boson sampling.

Public attitudes toward stuttering in Turkey: probability versus convenience sampling.

PubMed

Ozdemir, R Sertan; St Louis, Kenneth O; Topbaş, Seyhun

2011-12-01

A Turkish translation of the Public Opinion Survey of Human Attributes-Stuttering (POSHA-S) was used to compare probability versus convenience sampling to measure public attitudes toward stuttering. A convenience sample of adults in Eskişehir, Turkey was compared with two replicates of a school-based, probability cluster sampling scheme. The two replicates of the probability sampling scheme yielded similar demographic samples, both of which were different from the convenience sample. Components of subscores on the POSHA-S were significantly different in more than half of the comparisons between convenience and probability samples, indicating important differences in public attitudes. If POSHA-S users intend to generalize to specific geographic areas, results of this study indicate that probability sampling is a better research strategy than convenience sampling. The reader will be able to: (1) discuss the difference between convenience sampling and probability sampling; (2) describe a school-based probability sampling scheme; and (3) describe differences in POSHA-S results from convenience sampling versus probability sampling. Copyright © 2011 Elsevier Inc. All rights reserved.

A Satellite Infrared Technique for Diurnal Rainfall Variability Studies

NASA Technical Reports Server (NTRS)

Anagnostou, Emmanouil

1998-01-01

Reliable information on the distribution of precipitation at high temporal resolution (

Optimization of the time series NDVI-rainfall relationship using linear mixed-effects modeling for the anti-desertification area in the Beijing and Tianjin sandstorm source region

NASA Astrophysics Data System (ADS)

Wang, Jin; Sun, Tao; Fu, Anmin; Xu, Hao; Wang, Xinjie

2018-05-01

Degradation in drylands is a critically important global issue that threatens ecosystem and environmental in many ways. Researchers have tried to use remote sensing data and meteorological data to perform residual trend analysis and identify human-induced vegetation changes. However, complex interactions between vegetation and climate, soil units and topography have not yet been considered. Data used in the study included annual accumulated Moderate Resolution Imaging Spectroradiometer (MODIS) 250 m normalized difference vegetation index (NDVI) from 2002 to 2013, accumulated rainfall from September to August, digital elevation model (DEM) and soil units. This paper presents linear mixed-effect (LME) modeling methods for the NDVI-rainfall relationship. We developed linear mixed-effects models that considered the random effects of sample points nested in soil units for nested two-level modeling and single-level modeling of soil units and sample points, respectively. Additionally, three functions, including the exponential function (exp), the power function (power), and the constant plus power function (CPP), were tested to remove heterogeneity, and an additional three correlation structures, including the first-order autoregressive structure [AR(1)], a combination of first-order autoregressive and moving average structures [ARMA(1,1)] and the compound symmetry structure (CS), were used to address the spatiotemporal correlations. It was concluded that the nested two-level model considering both heteroscedasticity with (CPP) and spatiotemporal correlation with [ARMA(1,1)] showed the best performance (AMR = 0.1881, RMSE = 0.2576, adj- R 2 = 0.9593). Variations between soil units and sample points that may have an effect on the NDVI-rainfall relationship should be included in model structures, and linear mixed-effects modeling achieves this in an effective and accurate way.

The interaction rainfall vs. weight as determinant of total mercury concentration in fish from a tropical estuary.

PubMed

Barletta, M; Lucena, L R R; Costa, M F; Barbosa-Cintra, S C T; Cysneiros, F J A

2012-08-01

Mercury loads in tropical estuaries are largely controlled by the rainfall regime that may cause biodilution due to increased amounts of organic matter (both live and non-living) in the system. Top predators, as Trichiurus lepturus, reflect the changing mercury bioavailability situations in their muscle tissues. In this work two variables [fish weight (g) and monthly total rainfall (mm)] are presented as being important predictors of total mercury concentration (T-Hg) in fish muscle. These important explanatory variables were identified by a Weibull Regression model, which best fit the dataset. A predictive model using readily available variables as rainfall is important, and can be applied for human and ecological health assessments and decisions. The main contribution will be to further protect vulnerable groups as pregnant women and children. Nature conservation directives could also improve by considering monitoring sample designs that include this hypothesis, helping to establish complete and detailed mercury contamination scenarios. Copyright © 2012 Elsevier Ltd. All rights reserved.

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.

Spatial variability of summer Florida precipitation and its impact on microwave radiometer rainfall-measurement systems

NASA Technical Reports Server (NTRS)

Turner, B. J.; Austin, G. L.

1993-01-01

Three-dimensional radar data for three summer Florida storms are used as input to a microwave radiative transfer model. The model simulates microwave brightness observations by a 19-GHz, nadir-pointing, satellite-borne microwave radiometer. The statistical distribution of rainfall rates for the storms studied, and therefore the optimal conversion between microwave brightness temperatures and rainfall rates, was found to be highly sensitive to the spatial resolution at which observations were made. The optimum relation between the two quantities was less sensitive to the details of the vertical profile of precipitation. Rainfall retrievals were made for a range of microwave sensor footprint sizes. From these simulations, spatial sampling-error estimates were made for microwave radiometers over a range of field-of-view sizes. The necessity of matching the spatial resolution of ground truth to radiometer footprint size is emphasized. A strategy for the combined use of raingages, ground-based radar, microwave, and visible-infrared (VIS-IR) satellite sensors is discussed.

Hydrograph simulation models of the Hillsborough and Alafia Rivers, Florida: a preliminary report

USGS Publications Warehouse

Turner, James F.

1972-01-01

Mathematical (digital) models that simulate flood hydrographs from rainfall records have been developed for the following gaging stations in the Hillsborough and Alafia River basins of west-central Florida: Hillsborough River near Tampa, Alafia River at Lithia, and north Prong Alafia River near Keysville. These models, which were developed from historical streamflow and and rainfall records, are based on rainfall-runoff and unit-hydrograph procedures involving an arbitrary separation of the flood hydrograph. These models assume the flood hydrograph to be composed of only two flow components, direct (storm) runoff, and base flow. Expressions describing these two flow components are derived from streamflow and rainfall records and are combined analytically to form algorithms (models), which are programmed for processing on a digital computing system. Most Hillsborough and Alafia River flood discharges can be simulated with expected relative errors less than or equal to 30 percent and flood peaks can be simulated with average relative errors less than 15 percent. Because of the inadequate rainfall network that is used in obtaining input data for the North Prong Alafia River model, simulated peaks are frequently in error by more than 40 percent, particularly for storms having highly variable areal rainfall distribution. Simulation errors are the result of rainfall sample errors and, to a lesser extent, model inadequacy. Data errors associated with the determination of mean basin precipitation are the result of the small number and poor areal distribution of rainfall stations available for use in the study. Model inadequacy, however, is attributed to the basic underlying theory, particularly the rainfall-runoff relation. These models broaden and enhance existing water-management capabilities within these basins by allowing the establishment and implementation of programs providing for continued development in these areas. Specifically, the models serve not only as a basis for forecasting floods, but also for simulating hydrologic information needed in flood-plain mapping and delineating and evaluating alternative flood control and abatement plans.

Evaluation of Surface Runoff Generation Processes Using a Rainfall Simulator: A Small Scale Laboratory Experiment

NASA Astrophysics Data System (ADS)

Danáčová, Michaela; Valent, Peter; Výleta, Roman

2017-12-01

Nowadays, rainfall simulators are being used by many researchers in field or laboratory experiments. The main objective of most of these experiments is to better understand the underlying runoff generation processes, and to use the results in the process of calibration and validation of hydrological models. Many research groups have assembled their own rainfall simulators, which comply with their understanding of rainfall processes, and the requirements of their experiments. Most often, the existing rainfall simulators differ mainly in the size of the irrigated area, and the way they generate rain drops. They can be characterized by the accuracy, with which they produce a rainfall of a given intensity, the size of the irrigated area, and the rain drop generating mechanism. Rainfall simulation experiments can provide valuable information about the genesis of surface runoff, infiltration of water into soil and rainfall erodibility. Apart from the impact of physical properties of soil, its moisture and compaction on the generation of surface runoff and the amount of eroded particles, some studies also investigate the impact of vegetation cover of the whole area of interest. In this study, the rainfall simulator was used to simulate the impact of the slope gradient of the irrigated area on the amount of generated runoff and sediment yield. In order to eliminate the impact of external factors and to improve the reproducibility of the initial conditions, the experiments were conducted in laboratory conditions. The laboratory experiments were carried out using a commercial rainfall simulator, which was connected to an external peristaltic pump. The pump maintained a constant and adjustable inflow of water, which enabled to overcome the maximum volume of simulated precipitation of 2.3 l, given by the construction of the rainfall simulator, while maintaining constant characteristics of the simulated precipitation. In this study a 12-minute rainfall with a constant intensity of 5 mm/min was used to irrigate a corrupted soil sample. The experiment was undertaken for several different slopes, under the condition of no vegetation cover. The results of the rainfall simulation experiment complied with the expectations of a strong relationship between the slope gradient, and the amount of surface runoff generated. The experiments with higher slope gradients were characterised by larger volumes of surface runoff generated, and by shorter times after which it occurred. The experiments with rainfall simulators in both laboratory and field conditions play an important role in better understanding of runoff generation processes. The results of such small scale experiments could be used to estimate some of the parameters of complex hydrological models, which are used to model rainfall-runoff and erosion processes at catchment scale.

Comparison of Two Stochastic Daily Rainfall Models and their Ability to Preserve Multi-year Rainfall Variability

NASA Astrophysics Data System (ADS)

Kamal Chowdhury, AFM; Lockart, Natalie; Willgoose, Garry; Kuczera, George; Kiem, Anthony; Parana Manage, Nadeeka

2016-04-01

Stochastic simulation of rainfall is often required in the simulation of streamflow and reservoir levels for water security assessment. As reservoir water levels generally vary on monthly to multi-year timescales, it is important that these rainfall series accurately simulate the multi-year variability. However, the underestimation of multi-year variability is a well-known issue in daily rainfall simulation. Focusing on this issue, we developed a hierarchical Markov Chain (MC) model in a traditional two-part MC-Gamma Distribution modelling structure, but with a new parameterization technique. We used two parameters of first-order MC process (transition probabilities of wet-to-wet and dry-to-dry days) to simulate the wet and dry days, and two parameters of Gamma distribution (mean and standard deviation of wet day rainfall) to simulate wet day rainfall depths. We found that use of deterministic Gamma parameter values results in underestimation of multi-year variability of rainfall depths. Therefore, we calculated the Gamma parameters for each month of each year from the observed data. Then, for each month, we fitted a multi-variate normal distribution to the calculated Gamma parameter values. In the model, we stochastically sampled these two Gamma parameters from the multi-variate normal distribution for each month of each year and used them to generate rainfall depth in wet days using the Gamma distribution. In another study, Mehrotra and Sharma (2007) proposed a semi-parametric Markov model. They also used a first-order MC process for rainfall occurrence simulation. But, the MC parameters were modified by using an additional factor to incorporate the multi-year variability. Generally, the additional factor is analytically derived from the rainfall over a pre-specified past periods (e.g. last 30, 180, or 360 days). They used a non-parametric kernel density process to simulate the wet day rainfall depths. In this study, we have compared the performance of our hierarchical MC model with the semi-parametric model in preserving rainfall variability in daily, monthly, and multi-year scales. To calibrate the parameters of both models and assess their ability to preserve observed statistics, we have used ground based data from 15 raingauge stations around Australia, which consist a wide range of climate zones including coastal, monsoonal, and arid climate characteristics. In preliminary results, both models show comparative performances in preserving the multi-year variability of rainfall depth and occurrence. However, the semi-parametric model shows a tendency of overestimating the mean rainfall depth, while our model shows a tendency of overestimating the number of wet days. We will discuss further the relative merits of the both models for hydrology simulation in the presentation.

An Overview of Recent Advances in Event-Triggered Consensus of Multiagent Systems.

PubMed

Ding, Lei; Han, Qing-Long; Ge, Xiaohua; Zhang, Xian-Ming

2018-04-01

Event-triggered consensus of multiagent systems (MASs) has attracted tremendous attention from both theoretical and practical perspectives due to the fact that it enables all agents eventually to reach an agreement upon a common quantity of interest while significantly alleviating utilization of communication and computation resources. This paper aims to provide an overview of recent advances in event-triggered consensus of MASs. First, a basic framework of multiagent event-triggered operational mechanisms is established. Second, representative results and methodologies reported in the literature are reviewed and some in-depth analysis is made on several event-triggered schemes, including event-based sampling schemes, model-based event-triggered schemes, sampled-data-based event-triggered schemes, and self-triggered sampling schemes. Third, two examples are outlined to show applicability of event-triggered consensus in power sharing of microgrids and formation control of multirobot systems, respectively. Finally, some challenging issues on event-triggered consensus are proposed for future research.

The weak acid nature of precipitation

Treesearch

John O. Frohliger; Robert L. Kane

1976-01-01

Recent measurements of the pH of precipitation leave no doubt that rainfall is acidic. Evidence will be presented that precipitation is a weak acid system. The results of this research indicate the need to establish standard sampling procedures to provide uniform sampling of precipitation

Cloud-resolving model intercomparison of an MC3E squall line case: Part I-Convective updrafts: CRM Intercomparison of a Squall Line

DOE PAGES

Fan, Jiwen; Han, Bin; Varble, Adam; ...

2017-09-06

An intercomparison study of a midlatitude mesoscale squall line is performed using the Weather Research and Forecasting (WRF) model at 1 km horizontal grid spacing with eight different cloud microphysics schemes to investigate processes that contribute to the large variability in simulated cloud and precipitation properties. All simulations tend to produce a wider area of high radar reflectivity (Z e > 45 dBZ) than observed but a much narrower stratiform area. Furthermore, the magnitude of the virtual potential temperature drop associated with the gust front passage is similar in simulations and observations, while the pressure rise and peak wind speedmore » are smaller than observed, possibly suggesting that simulated cold pools are shallower than observed. Most of the microphysics schemes overestimate vertical velocity and Z e in convective updrafts as compared with observational retrievals. Simulated precipitation rates and updraft velocities have significant variability across the eight schemes, even in this strongly dynamically driven system. Differences in simulated updraft velocity correlate well with differences in simulated buoyancy and low-level vertical perturbation pressure gradient, which appears related to cold pool intensity that is controlled by the evaporation rate. Simulations with stronger updrafts have a more optimal convective state, with stronger cold pools, ambient low-level vertical wind shear, and rear-inflow jets. We found that updraft velocity variability between schemes is mainly controlled by differences in simulated ice-related processes, which impact the overall latent heating rate, whereas surface rainfall variability increases in no-ice simulations mainly because of scheme differences in collision-coalescence parameterizations.« less

Evaluation of spot and passive sampling for monitoring, flux estimation and risk assessment of pesticides within the constraints of a typical regulatory monitoring scheme.

PubMed

Zhang, Zulin; Troldborg, Mads; Yates, Kyari; Osprey, Mark; Kerr, Christine; Hallett, Paul D; Baggaley, Nikki; Rhind, Stewart M; Dawson, Julian J C; Hough, Rupert L

2016-11-01

In many agricultural catchments of Europe and North America, pesticides occur at generally low concentrations with significant temporal variation. This poses several challenges for both monitoring and understanding ecological risks/impacts of these chemicals. This study aimed to compare the performance of passive and spot sampling strategies given the constraints of typical regulatory monitoring. Nine pesticides were investigated in a river currently undergoing regulatory monitoring (River Ugie, Scotland). Within this regulatory framework, spot and passive sampling were undertaken to understand spatiotemporal occurrence, mass loads and ecological risks. All the target pesticides were detected in water by both sampling strategies. Chlorotoluron was observed to be the dominant pesticide by both spot (maximum: 111.8ng/l, mean: 9.35ng/l) and passive sampling (maximum: 39.24ng/l, mean: 4.76ng/l). The annual pesticide loads were estimated to be 2735g and 1837g based on the spot and passive sampling data, respectively. The spatiotemporal trend suggested that agricultural activities were the primary source of the compounds with variability in loads explained in large by timing of pesticide applications and rainfall. The risk assessment showed chlorotoluron and chlorpyrifos posed the highest ecological risks with 23% of the chlorotoluron spot samples and 36% of the chlorpyrifos passive samples resulting in a Risk Quotient greater than 0.1. This suggests that mitigation measures might need to be taken to reduce the input of pesticides into the river. The overall comparison of the two sampling strategies supported the hypothesis that passive sampling tends to integrate the contaminants over a period of exposure and allows quantification of contamination at low concentration. The results suggested that within a regulatory monitoring context passive sampling was more suitable for flux estimation and risk assessment of trace contaminants which cannot be diagnosed by spot sampling and for determining if long-term average concentrations comply with specified standards. Copyright © 2016 Elsevier B.V. All rights reserved.

Impact of the rainfall pattern on synthetic pesticides and copper runoff from a vineyard catchment

NASA Astrophysics Data System (ADS)

Payraudeau, Sylvain; Meite, Fatima; Wiegert, Charline; Imfeld, Gwenaël

2017-04-01

Runoff is a major process of pesticide transport from agricultural land to downstream aquatic ecosystems. The impact of rainfall characteristics on the transport of runoff-related pesticide is rarely evaluated at the catchment scale. Here, we evaluate the influence of rainfall pattern on the mobilization of synthetic pesticides and copper fungicides in runoff from a small vineyard catchment, both at the plot and catchment scales. During two vineyard growing seasons in 2015 and 2016 (from March to October), we monitored rainfall, runoff, and concentrations of copper and 20 fungicides and herbicides applied by winegrowers at the Rouffach vineyard catchment (France, Alsace; 42.5 ha). Rainfall data were recorded within the catchment while runoff measurement and flow-proportional water sampling were carried out at the outlet of the plot (1486 m2; 87.5 × 17 m) and the catchment. In total, discharges of the 14 runoff events were continuously monitored between March and October 2015 using bubbler flow modules combined with Venturi channels. Detailed and distributed dataset on pesticide applications were extracted from survey (copper formulations and type of pesticides, amount and application dates). Pools of copper and synthetic pesticides were quantified weekly in the topsoil (0-3 cm) by systematic sampling across the catchment. The concentrations of copper (10 mg.kg-1 dried soil) and synthetic pesticides (close to the quantification limit, i.e. 0.05 µg.L-1) available in the top soil for off-site transport largely differed over time. Between March and October, an accumulation of copper of 10% was observed in the top-soil while pesticide concentration decreased below the quantification limits after a few days or weeks following application, depending of the compounds. The average runoff generated at the plot scale was very low (0.13% ± 0.30). The maximum runoff reached 1.37% during the storm of July 22, 2015. Synthetic pesticides exported by runoff was less than 1‰ of the applications. The copper mass exported represented about 1% (i.e. 2,085 g at the plot's scale) of the seasonal input, and mainly occurred during the major storm event. Copper were mainly exported in association with suspended particulate matter (SPM) (>80% of the total load). The partitioning between dissolved and SPM phases differs for the synthetic pesticides as expected by their properties. The rainfall pattern influences concentrations and loads of copper and the pesticides. Dissolved pesticide loads normalized by the pesticide mass in soil varied with larger rainfall intensities, runoff discharges and volumes. Contrasted relationships between rainfall characteristics (i.e. intensity, duration and total amount) and the load exported suggest that mechanisms of contaminant delivery from the vineyard soil differs among the pesticides and for copper. The results support the idea that, even in small catchment areas, the rainfall pattern (i.e. rainfall intensity and duration) partly controls the transport of pesticide and copper loads in runoff. Though other factors, such as the chemical characteristics and the amount and timing of applications, are important drivers for pesticide runoff, the rainfall patterns also determine the transport of pesticides from catchment to downstream aquatic ecosystems, and thus the ecotoxicological risk.

Local influence of south-east France topography and land cover on the distribution and characteristics of intense rainfall cells

NASA Astrophysics Data System (ADS)

Renard, Florent

2017-04-01

The Greater Lyon area is strongly built up, grouping 58 communes and a population of 1.3 million in approximately 500 km2. The flood risk is high as the territory is crossed by two large watercourses and by streams with torrential flow. Floods may also occur in case of runoff after heavy rain or because of a rise in the groundwater level. The whole territory can therefore be affected, and it is necessary to possess in-depth knowledge of the depths, causes and consequences of rainfall to achieve better management of precipitation in urban areas and to reduce flood risk. This study is thus focused on the effects of topography and land cover on the occurrence, intensity and area of intense rainfall cells. They are identified by local radar meteorology (C-band) combined with a processing algorithm running in a geographic information system (GIS) which identified 109,979 weighted mean centres of them in a sample composed of the five most intense rainfall events from 2001 to 2005. First, analysis of spatial distribution at an overall scale is performed, completed by study at a more detailed scale. The results show that the distribution of high-intensity rainfall cells is spread in cluster form. Subsequently, comparison of intense rainfall cells with the topography shows that cell density is closely linked with land slope but that, above all, urbanised zones feature nearly twice as many rainfall cells as farm land or forest, with more intense intensity.

Optimal updating magnitude in adaptive flat-distribution sampling

NASA Astrophysics Data System (ADS)

Zhang, Cheng; Drake, Justin A.; Ma, Jianpeng; Pettitt, B. Montgomery

2017-11-01

We present a study on the optimization of the updating magnitude for a class of free energy methods based on flat-distribution sampling, including the Wang-Landau (WL) algorithm and metadynamics. These methods rely on adaptive construction of a bias potential that offsets the potential of mean force by histogram-based updates. The convergence of the bias potential can be improved by decreasing the updating magnitude with an optimal schedule. We show that while the asymptotically optimal schedule for the single-bin updating scheme (commonly used in the WL algorithm) is given by the known inverse-time formula, that for the Gaussian updating scheme (commonly used in metadynamics) is often more complex. We further show that the single-bin updating scheme is optimal for very long simulations, and it can be generalized to a class of bandpass updating schemes that are similarly optimal. These bandpass updating schemes target only a few long-range distribution modes and their optimal schedule is also given by the inverse-time formula. Constructed from orthogonal polynomials, the bandpass updating schemes generalize the WL and Langfeld-Lucini-Rago algorithms as an automatic parameter tuning scheme for umbrella sampling.

Optimal updating magnitude in adaptive flat-distribution sampling.

PubMed

Zhang, Cheng; Drake, Justin A; Ma, Jianpeng; Pettitt, B Montgomery

2017-11-07

We present a study on the optimization of the updating magnitude for a class of free energy methods based on flat-distribution sampling, including the Wang-Landau (WL) algorithm and metadynamics. These methods rely on adaptive construction of a bias potential that offsets the potential of mean force by histogram-based updates. The convergence of the bias potential can be improved by decreasing the updating magnitude with an optimal schedule. We show that while the asymptotically optimal schedule for the single-bin updating scheme (commonly used in the WL algorithm) is given by the known inverse-time formula, that for the Gaussian updating scheme (commonly used in metadynamics) is often more complex. We further show that the single-bin updating scheme is optimal for very long simulations, and it can be generalized to a class of bandpass updating schemes that are similarly optimal. These bandpass updating schemes target only a few long-range distribution modes and their optimal schedule is also given by the inverse-time formula. Constructed from orthogonal polynomials, the bandpass updating schemes generalize the WL and Langfeld-Lucini-Rago algorithms as an automatic parameter tuning scheme for umbrella sampling.

A cloud and radiation model-based algorithm for rainfall retrieval from SSM/I multispectral microwave measurements

NASA Technical Reports Server (NTRS)

Xiang, Xuwu; Smith, Eric A.; Tripoli, Gregory J.

1992-01-01

A hybrid statistical-physical retrieval scheme is explored which combines a statistical approach with an approach based on the development of cloud-radiation models designed to simulate precipitating atmospheres. The algorithm employs the detailed microphysical information from a cloud model as input to a radiative transfer model which generates a cloud-radiation model database. Statistical procedures are then invoked to objectively generate an initial guess composite profile data set from the database. The retrieval algorithm has been tested for a tropical typhoon case using Special Sensor Microwave/Imager (SSM/I) data and has shown satisfactory results.

Environmental Factors Affecting Efficacy of Bifenthrin-Treated Vegetation for Mosquito Control

DTIC Science & Technology

2009-01-01

and Surgeoner 1983, Ander- son et al. 1991, Perich et al. 1993, Cilek and Hallmon 2006), lambda cyhalothrin (Trout et al. 2007, Cilek and Hallmon 2008...insecticide treatment. Leaves were sampled 1–2 days before treatment, on the day of treatment, and at weeks 1, 2, 4, 6, and 7. All plants were watered ...were divided into 2 groups: those with no rainfall and those with heavy rainfall characteris- tic for June–September in north central Florida. Water

Stochastic modeling of hourly rainfall times series in Campania (Italy)

NASA Astrophysics Data System (ADS)

Giorgio, M.; Greco, R.

2009-04-01

Occurrence of flowslides and floods in small catchments is uneasy to predict, since it is affected by a number of variables, such as mechanical and hydraulic soil properties, slope morphology, vegetation coverage, rainfall spatial and temporal variability. Consequently, landslide risk assessment procedures and early warning systems still rely on simple empirical models based on correlation between recorded rainfall data and observed landslides and/or river discharges. Effectiveness of such systems could be improved by reliable quantitative rainfall prediction, which can allow gaining larger lead-times. Analysis of on-site recorded rainfall height time series represents the most effective approach for a reliable prediction of local temporal evolution of rainfall. Hydrological time series analysis is a widely studied field in hydrology, often carried out by means of autoregressive models, such as AR, ARMA, ARX, ARMAX (e.g. Salas [1992]). Such models gave the best results when applied to the analysis of autocorrelated hydrological time series, like river flow or level time series. Conversely, they are not able to model the behaviour of intermittent time series, like point rainfall height series usually are, especially when recorded with short sampling time intervals. More useful for this issue are the so-called DRIP (Disaggregated Rectangular Intensity Pulse) and NSRP (Neymann-Scott Rectangular Pulse) model [Heneker et al., 2001; Cowpertwait et al., 2002], usually adopted to generate synthetic point rainfall series. In this paper, the DRIP model approach is adopted, in which the sequence of rain storms and dry intervals constituting the structure of rainfall time series is modeled as an alternating renewal process. Final aim of the study is to provide a useful tool to implement an early warning system for hydrogeological risk management. Model calibration has been carried out with hourly rainfall hieght data provided by the rain gauges of Campania Region civil protection agency meteorological warning network. ACKNOWLEDGEMENTS The research was co-financed by the Italian Ministry of University, by means of the PRIN 2006 PRIN program, within the research project entitled ‘Definition of critical rainfall thresholds for destructive landslides for civil protection purposes'. REFERENCES Cowpertwait, P.S.P., Kilsby, C.G. and O'Connell, P.E., 2002. A space-time Neyman-Scott model of rainfall: Empirical analysis of extremes, Water Resources Research, 38(8):1-14. Salas, J.D., 1992. Analysis and modeling of hydrological time series, in D.R. Maidment, ed., Handbook of Hydrology, McGraw-Hill, New York. Heneker, T.M., Lambert, M.F. and Kuczera G., 2001. A point rainfall model for risk-based design, Journal of Hydrology, 247(1-2):54-71.

Influences of Hydrological Regime on Runoff Quality and Pollutant Loadings in Tropical Urban Areas

NASA Astrophysics Data System (ADS)

Chow, M.; Yusop, Z.

2011-12-01

Experience in many developed countries suggests that non point source (NPS) pollution is still the main contributor to pollutant loadings into water bodies in urban areas. However, the mechanism of NPS pollutant transport and the influences of hydrologic regime on the pollutant loading are still unclear. Understanding these interactions will be useful for improving design criteria and strategies for controlling NPS pollution in urban areas. This issue is also extremely relevant in tropical environment because its rainfall and the runoff generation processes are so different from the temperate regions where most of the studies on NPS pollutant have been carried out. In this regard, an intensive study to investigate the extent of this pollution was carried out in Skudai, Johor, Malaysia. Three small catchments, each represents commercial, residential and industrial land use were selected. Stormwater samples and flow rate data were collected at these catchments over 52 storm events from year 2008 to 2009. Samples were analyzed for ten water quality constituents including total suspended solids, 5-day biochemical oxygen demand, chemical oxygen demand, oil and grease, nitrate nitrogen, nitrite nitrogen, ammonia nitrogen, soluble phosphorus, total phosphorus and zinc. Quality of stormwater runoff is estimated using Event Mean Concentration (EMC) value. The storm characteristics analyzed included rainfall depth, rainfall duration, mean intensity, max 5 minutes intensity, antecedent dry day, runoff volume and peak flow. Correlation coefficients were determined between storm parameters and EMCs for the residential, commercial and industrial catchments. Except for the antecedent storm mean intensity and antecedent dry days, the other rainfall and runoff variables were negatively correlated with EMCs of most pollutants. This study reinforced the earlier findings on the importance of antecedent dry days for causing greater EMC values with exceptions for oil and grease, nitrate nitrogen, total phosphorus and zinc. There is no positive correlation between rainfall intensity and EMC of constituents in all the studied catchments. In contrast, the pollutant loadings are influenced primarily by the rainfall and runoff characteristics. Rainfall depth, mean intensity, max 5 minute intensity, runoff volume and peak flow were positively correlated with the loadings of most of the constituents. Antecedent storm mean intensity and antecedent dry days seemed to be less important for estimating the pollutant loadings. Such study should be further conducted for acquiring a long term monitoring data related to storm runoff quality during rainfall, in order to have a better understanding on NPS pollution in urban areas.

Rainfall interception, and its modeling, in Pine and Eucalypt stands in Portugal

NASA Astrophysics Data System (ADS)

de Coninck, H. L.; Keizer, J. J.; Coelho, C. O. A.; van Dijck, S. J. E.; Jetten, V. G.; Warmerdam, P. M. M.; Ferreira, A. J. D.; Boulet, A. K.

2003-04-01

Within the framework of the EU-funded CLIMED project (ICA3-2000-30005), concerning the water management implications of foreseeable climate and land-use changes in central Portugal and northern Africa, the event-based Limburg Soil Erosion Model (LISEM; www.geog.uu.nl/lisem) is intended to provide further insight into water yields, peak flow and timing under possible future rainfall regimes. In the Portuguese study area, LISEM is being applied to two small (< 1km2) catchments with contrasting land covers, dominated by Pinus pinaster Ait. and Eucalyptus globulus Labill. tree stands, respectively. In LISEM, cumulative interception is modelled using the empirical formula by Ashton (1979), i.e. as a function of vegetation cover and canopy storage capacity, which in turn is estimated from the Leaf Area Index using the Von Hoyningen-Huenes (1981) formula. Besides that the appropriateness of the LISEM interception module for forested areas may be questioned, its (optional) substitution in LISEM by a more process-based model like that of Rutter would be more in line with LISEM’s overall model structure. This study has as main aims to assess the suitability of (1) the Ashton formula and (2) the sparse variants of the Gash and Rutter interception models to model rainfall interception measurements carried out in a Pinus pinaster Ait. stand as well as a Eucalyptus globulus Labill. stand. Unlike in the bulk of published studies on forest interception, the experimental set-up structures the sampling space in below-canopy and gaps. The below-canopy sampling space is further divided into two classes on the basis of dendrometric data from a prior inventory of 20x20 m. The two stands are equipped with 15 below-canopy and 5 gap rainfall collectors, 3 of which are automated tipping-buckets gauges. Stemflow is measured for 10 trees per stand, which includes 2 trees with automated tipping-bucket (0.5 l/tip). Between November 2002 and the present time, 31 rainfall events totaling about 850 mm were recorded. Interestingly, these preliminary results reveal that below-canopy rainfall may exceed gap rainfall. This phenomenon can be explained by non-vertical rainfall, increasing the probability of droplets hitting the tree canopy instead of the forest floor. If further measurements confirm it to occur regularly, the suitability of not only the LISEM interception module but also the sparse Rutter and Gash models will, at least conceptually, be in doubt.

Estimating the occupancy of spotted owl habitat areas by sampling and adjusting for bias

Treesearch

David L. Azuma; James A. Baldwin; Barry R. Noon

1990-01-01

A basic sampling scheme is proposed to estimate the proportion of sampled units (Spotted Owl Habitat Areas (SOHAs) or randomly sampled 1000-acre polygon areas (RSAs)) occupied by spotted owl pairs. A bias adjustment for the possibility of missing a pair given its presence on a SOHA or RSA is suggested. The sampling scheme is based on a fixed number of visits to a...

Rainfall and snow-melt triggered glacial lake outbursts: a systematic analysis of the Kedarnath (Uttarakhand, India), June 2013 disaster

NASA Astrophysics Data System (ADS)

Allen, Simon; Rastner, Philipp; Arora, Manohar; Huggel, Christian; Stoffel, Markus

2015-04-01

Heavy rainfall in early June 2013 triggered flash flooding and landslides throughout the Indian Himalayan state of Uttarakhand, killing more than 6000 people. The destruction of roads and trekking routes left around 100,000 pilgrims and tourists stranded. Most fatalities and damages resulted directly from a lake outburst and debris flow disaster originating from above the village of Kedarnath on June 16 and 17. Here we provide a first systematic analysis of the contributing factors leading to the Kedarnath disaster, both in terms of hydro-meteorological triggering (rainfall, snowmelt, and temperature) and topographic predisposition. Specifically, the topographic characteristics of the Charobari lake watershed above Kedarnath are compared with other glacial lakes across the northwestern Indian Himalayan states of Uttarakhand and Himachal Pradesh, and implications for glacier lake outburst hazard assessment in a changing climate are discussed. Our analysis suggests that the early onset of heavy monsoon rainfall (390 mm, June 10 - 17) immediately following a prolonged four week period of unusually rapid snow cover depletion and elevated streamflow is the crucial hydro-meteorological factor, resulting in slope saturation and significant runoff into the small seasonal glacial lake. Over a four week period the MODIS-derived snow covered area above Kedarnath decreased nearly 50%, from above average coverage in mid-May to well below average coverage by the second week of June. Such a rapid decrease has not been observed in the previous 13-year record, where the average decrease in snow covered area over the same four week window is only 15%. The unusual situation of the lake being dammed in a steep, unstable paraglacial environment, but fed entirely from snow-melt and rainfall within a fluvial dominated watershed is important in the context of this disaster. A simple scheme enabling large-scale recognition of such an unfavorable topographic setting is presented, and on the basis of all assessed watershed parameters, the situation at Charobari lake indicates an anomalous predisposition towards rapid runoff and infilling during enhanced snowmelt or heavy rainfall. In view of projected 21st century changes in monsoon timing and heavy precipitation in South Asia, more emphasis should be given to potential hydro-meteorological triggering of lake outburst and related debris flow disasters in the Himalayas. The potential for Kedarnath-type lake breaching may further increase as glaciers recede or ultimately disappear, and watersheds become increasingly rainfall dominated. Hence, a long-term perspective to glacier lake outburst hazard assessment and management is required, as the greatest threat from hydro-meteorological triggering of related disasters may only be realized in an ice-free environment.

An object-based approach for areal rainfall estimation and validation of atmospheric models

NASA Astrophysics Data System (ADS)

Troemel, Silke; Simmer, Clemens

2010-05-01

An object-based approach for areal rainfall estimation is applied to pseudo-radar data simulated of a weatherforecast model as well as to real radar volume data. The method aims at an as fully as possible exploitation of three-dimensional radar signals produced by precipitation generating systems during their lifetime to enhance areal rainfall estimation. Therefore tracking of radar-detected precipitation-centroids is performed and rain events are investigated using so-called Integral Radar Volume Descriptors (IRVD) containing relevant information of the underlying precipitation process. Some investigated descriptors are statistical quantities from the radar reflectivities within the boundary of a tracked rain cell like the area mean reflectivity or the compactness of a cell; others evaluate the mean vertical structure during the tracking period at the near surface reflectivity-weighted center of the cell like the mean effective efficiency or the mean echo top height. The stage of evolution of a system is given by the trend in the brightband fraction or related quantities. Furthermore, two descriptors not directly derived from radar data are considered: the mean wind shear and an orographic rainfall amplifier. While in case of pseudo-radar data a model based on a small set of IRVDs alone provides rainfall estimates of high accuracy, the application of such a model to the real world remains within the accuracies achievable with a constant Z-R-relationship. However, a combined model based on single IRVDs and the Marshall-Palmer Z-R-estimator already provides considerable enhancements even though the resolution of the data base used has room for improvement. The mean echo top height, the mean effective efficiency, the empirical standard deviation and the Marshall-Palmer estimator are detected for the final rainfall estimator. High correlations between storm height and rain rates, a shift of the probability distribution to higher values with increasing effective efficiency, and the possibility to classify continental and maritime systems using the effective efficiency confirm the informative value of the qualified descriptors. The IRVDs especially correct for the underestimation in case of intense rain events, and the information content of descriptors is most likely higher than demonstrated so far. We used quite sparse information about meteorological variables needed for the calculation of some IRVDs from single radiosoundings, and several descriptors suffered from the range-dependent vertical resolution of the reflectivity profile. Inclusion of neighbouring radars and assimilation runs of weather forecasting models will further enhance the accuracy of rainfall estimates. Finally, the clear difference between the IRVD selection from the pseudo-radar data and from the real world data hint to a new object-based avenue for the validation of higher resolution atmospheric models and for evaluating their potential to digest radar observations in data assimilation schemes.

A Noise-Filtered Under-Sampling Scheme for Imbalanced Classification.

PubMed

Kang, Qi; Chen, XiaoShuang; Li, SiSi; Zhou, MengChu

2017-12-01

Under-sampling is a popular data preprocessing method in dealing with class imbalance problems, with the purposes of balancing datasets to achieve a high classification rate and avoiding the bias toward majority class examples. It always uses full minority data in a training dataset. However, some noisy minority examples may reduce the performance of classifiers. In this paper, a new under-sampling scheme is proposed by incorporating a noise filter before executing resampling. In order to verify the efficiency, this scheme is implemented based on four popular under-sampling methods, i.e., Undersampling + Adaboost, RUSBoost, UnderBagging, and EasyEnsemble through benchmarks and significance analysis. Furthermore, this paper also summarizes the relationship between algorithm performance and imbalanced ratio. Experimental results indicate that the proposed scheme can improve the original undersampling-based methods with significance in terms of three popular metrics for imbalanced classification, i.e., the area under the curve, -measure, and -mean.

Optical sectioning in induced coherence tomography with frequency-entangled photons

NASA Astrophysics Data System (ADS)

Vallés, Adam; Jiménez, Gerard; Salazar-Serrano, Luis José; Torres, Juan P.

2018-02-01

We demonstrate a different scheme to perform optical sectioning of a sample based on the concept of induced coherence [Zou et al., Phys. Rev. Lett. 67, 318 (1991), 10.1103/PhysRevLett.67.318]. This can be viewed as a different type of optical coherence tomography scheme where the varying reflectivity of the sample along the direction of propagation of an optical beam translates into changes of the degree of first-order coherence between two beams. As a practical advantage the scheme allows probing the sample with one wavelength and measuring photons with another wavelength. In a bio-imaging scenario, this would result in a deeper penetration into the sample because of probing with longer wavelengths, while still using the optimum wavelength for detection. The scheme proposed here could achieve submicron axial resolution by making use of nonlinear parametric sources with broad spectral bandwidth emission.

Spatial and temporal trends in occurrence of emerging and legacy contaminants in the Lower Columbia River 2008-2010

USGS Publications Warehouse

Alvarez, David A.; Perkins, Stephanie D.; Nilsen, Elena B.; Morace, Jennifer L.

2014-01-01

The Lower Columbia River in Oregon and Washington, USA, is an important resource for aquatic and terrestrial organisms, agriculture, and commerce. An 86-mile stretch of the river was sampled over a 3 year period in order to determine the spatial and temporal trends in the occurrence and concentration of water-borne organic contaminants. Sampling occurred at 10 sites along this stretch and at 1 site on the Willamette River using the semipermeable membrane device (SPMD) and the polar organic chemical integrative sampler (POCIS) passive samplers. Contaminant profiles followed the predicted trends of lower numbers of detections and associated concentrations in the rural areas to higher numbers and concentrations at the more urbanized sites. Industrial chemicals, plasticizers, and PAHs were present at the highest concentrations. Differences in concentrations between sampling periods were related to the amount of rainfall during the sampling period. In general, water concentrations of wastewater-related contaminants decreased and concentrations of legacy contaminants slightly increased with increasing rainfall amounts.

Hydrological and nutrient fluxes in the soil-atmosphere interface in Brazilian semiarid

NASA Astrophysics Data System (ADS)

Leal, Karinne; Borma, Laura; Forti, Cristina

2014-05-01

Semiarids are water stress regions caused by the association of high potential evapotranspiration, high temperatures (in summer) and generally low rainfall. Although unfavorable climatic conditions, semiarid regions represent about 14% global population and has been suffering land transformation, such as replacement by pastures and croplands. Crescent demand for agricultural and forests products in Brazilian semiarid has taken Caatinga deforestations, typical vegetation of that area that covers about 10% of Brazilian territory, with consequences in hydrology and biogeochemistry. The effect of these disruptions are poorly understood. The aim of this research is to characterize the differences in transfers of water and nutrients, in soil-atmosphere interface, between a typical Caatinga vegetation and pasture. Two field campaigns were made to sample and measure the water from rainfall, throughfall, stemflow, runoff and soil water. The collections were conducted during the rainy season, extended from April to August in 2012 and 2013, in São João, a county in the semiarid region of Pernambuco State, in the northeast of Brazil. The samples are being analyzed in order to determine their major cations and anions concentrations, total dissolved carbon (TDC), total organic carbon (TOC), total nitrogen (TN), alkalinity and pH. The observed precipitation represented about 40% and 50% of the historical average precipitation, in 2012 and 2013, respectively. This observations highlight the severe drought experienced in the region, mainly in the first year of sampling. The throughfall represented about 35% of the rainfall in 2012, and about 25% in 2013. In semiarid vegetations the average throughfall is about 49%, with variation coefficient of ±32%, so the observed data are consistent with those reported in the literature. These observations suggests that in drier years the vegetation holds more moisture than in wetter years. However, these data must be correlated with others parameters that influence the relationship between rainfall and troughfall, such as intensity and duration of the rain, wind speed and air humidity before the rainfall. The runoff was an order of magnitude lower in 2012 than in 2013. The chemical analyzes are still being processed. Key-words: Caatinga, carbon, nitrogen, land transformation.

Progressive compressive imager

NASA Astrophysics Data System (ADS)

Evladov, Sergei; Levi, Ofer; Stern, Adrian

2012-06-01

We have designed and built a working automatic progressive sampling imaging system based on the vector sensor concept, which utilizes a unique sampling scheme of Radon projections. This sampling scheme makes it possible to progressively add information resulting in tradeoff between compression and the quality of reconstruction. The uniqueness of our sampling is that in any moment of the acquisition process the reconstruction can produce a reasonable version of the image. The advantage of the gradual addition of the samples is seen when the sparsity rate of the object is unknown, and thus the number of needed measurements. We have developed the iterative algorithm OSO (Ordered Sets Optimization) which employs our sampling scheme for creation of nearly uniform distributed sets of samples, which allows the reconstruction of Mega-Pixel images. We present the good quality reconstruction from compressed data ratios of 1:20.

Disappearance of dislodgable residues of five organophosphate pesticides on citrus leaves and fruit during dry and wet weather in Florida.

PubMed

Thompson, N P

1976-01-01

Citrus leaf discs and fruit taken from trees sprayed at recommended levels and twice recommended levels with ethion, parathion, azinphosmethyl, carbophenothion, and dioxathion were shaken with water and wetting agent for removal of dislodgable residues at 0, 1, 3, 5, 7, 14 and 21 days following treatment. The first portion of the field experiment was performed during a period of no rainfall (April) and the second when there was rainfall (July) in 1973. Four replicates of 50 leaf discs and 4 fruit, respectively, were averaged from each sampling to give data reported. A gas chromatograph equipped with a flame photometric detector was used for analysis. Dislodgable residues found decreased with increasing time following application and samples from the wet period were lower than those from the dry period. Moisture and temperature could account for the differences in the two sampling period.

Factors Affecting the Evolution of Hurricane Erin and the Distributions of Hydrometeors: Role of Microphysical Processes

NASA Technical Reports Server (NTRS)

McFarquhar, Greg M.; Zhang, Henian; Dudhia, Jimy; Halverson, Jeffrey B.; Heymsfield, Gerald; Hood, Robbie; Marks, Frank, Jr.

2003-01-01

Fine-resolution simulations of Hurricane Erin 2001 are conducted using the Penn State University/National Center for Atmospheric Research mesoscale model version 3.5 to investigate the role of thermodynamic, boundary layer and microphysical processes in Erin's growth and maintenance, and their effects on the horizontal and vertical distributions of hydrometeors. Through comparison against radar, radiometer, and dropsonde data collected during the Convection and Moisture Experiment 4, it is seen that realistic simulations of Erin are obtained provided that fine resolution simulations with detailed representations of physical processes are conducted. The principle findings of the study are as follows: 1) a new iterative condensation scheme, which limits the unphysical increase of equivalent potential temperature associated with most condensation schemes, increases the horizontal size of the hurricane, decreases its maximum rainfall rate, reduces its intensity, and makes its eye more moist; 2) in general, microphysical parameterization schemes with more categories of hydrometeors produce more intense hurricanes, larger hydrometeor mixing ratios, and more intense updrafts and downdrafts; 3) the choice of coefficients describing hydrometeor fall velocities has as big of an impact on the hurricane simulations as does choice of microphysical parameterization scheme with no clear relationship between fall velocity and hurricane intensity; and 4) in order for a tropical cyclone to adequately intensify, an advanced boundary layer scheme (e.g., Burk-Thompson scheme) must be used to represent boundary layer processes. The impacts of varying simulations on the horizontal and vertical distributions of different categories of hydrometeor species, on equivalent potential temperature, and on storm updrafts and downdrafts are examined to determine how the release of latent heat feedbacks upon the structure of Erin. In general, all simulations tend to overpredict precipitation rate and hydrometeor mixing ratios. The ramifications of these findings for quantitative precipitation forecasts (QPFs) of tropical cyclones are discussed.

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

Varble, Adam; Zipser, Edward J.; Fridlind, Ann

Ten 3D cloud-resolving model (CRM) simulations and four 3D limited area model (LAM) simulations of an intense mesoscale convective system observed on January 23-24, 2006 during the Tropical Warm Pool – International Cloud Experiment (TWP-ICE) are compared with each other and with observations and retrievals from a scanning polarimetric radar, co-located UHF and VHF vertical profilers, and a Joss-Waldvogel disdrometer in an attempt to explain published results showing a low bias in simulated stratiform rainfall. Despite different forcing methodologies, similar precipitation microphysics errors appear in CRMs and LAMs with differences that depend on the details of the bulk microphysics schememore » used. One-moment schemes produce too many small raindrops, which biases Doppler velocities low, but produces rain water contents (RWCs) that are similar to observed. Two-moment rain schemes with a gamma shape parameter (μ) of 0 produce excessive size sorting, which leads to larger Doppler velocities than those produced in one-moment schemes, but lower RWCs than observed. Two moment schemes also produce a convective median volume diameter distribution that is too broad relative to observations and thus, may have issues balancing raindrop formation, collision coalescence, and raindrop breakup. Assuming a μ of 2.5 rather than 0 for the raindrop size distribution improves one-moment scheme biases, and allowing μ to have values greater than 0 may improve two-moment schemes. Under-predicted stratiform rain rates are associated with under-predicted ice water contents at the melting level rather than excessive rain evaporation, in turn likely associated with convective detrainment that is too high in the troposphere and mesoscale circulations that are too weak. In addition to stronger convective updrafts than observed, limited domain size prevents a large, well-developed stratiform region from developing in CRMs, while a dry bias in ECMWF analyses does the same to the LAMs.« less

Extreme precipitation in WRF during the Newcastle East Coast Low of 2007

NASA Astrophysics Data System (ADS)

Gilmore, James B.; Evans, Jason P.; Sherwood, Steven C.; Ekström, Marie; Ji, Fei

2016-08-01

In the context of regional downscaling, we study the representation of extreme precipitation in the Weather Research and Forecasting (WRF) model, focusing on a major event that occurred on the 8th of June 2007 along the coast of eastern Australia (abbreviated "Newy"). This was one of the strongest extra-tropical low-pressure systems off eastern Australia in the last 30 years and was one of several storms comprising a test bed for the WRF ensemble that underpins the regional climate change projections for eastern Australia (New South Wales/Australian Capital Territory Regional Climate Modelling Project, NARCliM). Newy provides an informative case study for examining precipitation extremes as simulated by WRF set up for regional downscaling. Here, simulations from the NARCliM physics ensemble of Newy available at ˜10 km grid spacing are used. Extremes and spatio-temporal characteristics are examined using land-based daily and hourly precipitation totals, with a particular focus on hourly accumulations. Of the different physics schemes assessed, the cumulus and the boundary layer schemes cause the largest differences. Although the Betts-Miller-Janjic cumulus scheme produces better rainfall totals over the entire storm, the Kain-Fritsch cumulus scheme promotes higher and more realistic hourly extreme precipitation totals. Analysis indicates the Kain-Fritsch runs are correlated with larger resolved grid-scale vertical moisture fluxes, which are produced through the influence of parameterized convection on the larger-scale circulation and the subsequent convergence and ascent of moisture. Results show that WRF qualitatively reproduces spatial precipitation patterns during the storm, albeit with some errors in timing. This case study indicates that whilst regional climate simulations of an extreme event such as Newy in WRF may be well represented at daily scales irrespective of the physics scheme used, the representation at hourly scales is likely to be physics scheme dependent.

Systolic MOLLI T1 mapping with heart-rate-dependent pulse sequence sampling scheme is feasible in patients with atrial fibrillation.

PubMed

Zhao, Lei; Li, Songnan; Ma, Xiaohai; Greiser, Andreas; Zhang, Tianjing; An, Jing; Bai, Rong; Dong, Jianzeng; Fan, Zhanming

2016-03-15

T1 mapping enables assessment of myocardial characteristics. As the most common type of arrhythmia, atrial fibrillation (AF) is often accompanied by a variety of cardiac pathologies, whereby the irregular and usually rapid ventricle rate of AF may cause inaccurate T1 estimation due to mis-triggering and inadequate magnetization recovery. We hypothesized that systolic T1 mapping with a heart-rate-dependent (HRD) pulse sequence scheme may overcome this issue. 30 patients with AF and 13 healthy volunteers were enrolled and underwent cardiovascular magnetic resonance (CMR) at 3 T. CMR was repeated for 3 patients after electric cardioversion and for 2 volunteers after lowering heart rate (HR). A Modified Look-Locker Inversion Recovery (MOLLI) sequence was acquired before and 15 min after administration of 0.1 mmol/kg gadopentetate dimeglumine. For AF patients, both the fixed 5(3)3/4(1)3(1)2 and the HRD sampling scheme were performed at diastole and systole, respectively. The HRD pulse sequence sampling scheme was 5(n)3/4(n)3(n)2, where n was determined by the heart rate to ensure adequate magnetization recovery. Image quality of T1 maps was assessed. T1 times were measured in myocardium and blood. Extracellular volume fraction (ECV) was calculated. In volunteers with repeated T1 mapping, the myocardial native T1 and ECV generated from the 1st fixed sampling scheme were smaller than from the 1st HRD and 2nd fixed sampling scheme. In healthy volunteers, the overall native T1 times and ECV of the left ventricle (LV) in diastolic T1 maps were greater than in systolic T1 maps (P < 0.01, P < 0.05). In the 3 AF patients that had received electrical cardioversion therapy, the myocardial native T1 times and ECV generated from the fixed sampling scheme were smaller than in the 1st and 2nd HRD sampling scheme (all P < 0.05). In patients with AF (HR: 88 ± 20 bpm, HR fluctuation: 12 ± 9 bpm), more T1 maps with artifact were found in diastole than in systole (P < 0.01). The overall native T1 times and ECV of the left ventricle (LV) in diastolic T1 maps were greater than systolic T1 maps, either with fixed or HRD sampling scheme (all P < 0.05). Systolic MOLLI T1 mapping with heart-rate-dependent pulse sequence scheme can improve image quality and avoid T1 underestimation. It is feasible and with further validation may extend clinical applicability of T1 mapping to patients with atrial fibrillation.

Using high-frequency sampling to detect effects of atmospheric pollutants on stream chemistry

Treesearch

Stephen D. Sebestyen; James B. Shanley; Elizabeth W. Boyer

2009-01-01

We combined information from long-term (weekly over many years) and short-term (high-frequency during rainfall and snowmelt events) stream water sampling efforts to understand how atmospheric deposition affects stream chemistry. Water samples were collected at the Sleepers River Research Watershed, VT, a temperate upland forest site that receives elevated atmospheric...

Mechanism of shallow disrupted slide induced by extreme rainfall

NASA Astrophysics Data System (ADS)

Igwe, O.; Fukuoka, H.

2010-12-01

On July 16, 2010, extreme rainfall attacked western Japan and it caused very intense rainfall in Shobara city, Hiroshima prefecture, Japan. This rainfall induced hundreds of shallow disrupted slides and many of those became debris flows. One of this debris flows attacked a house standing in front of the exit of a channel, and claimed a resident’s life. Western Japan had repeatedly similar disasters in the past. Last event took place from July 19 to 26, 2009, when western Japan had a severe rainstorms and caused floods and landslides. Most of the landslides are debris slide - debris flows. Most devastated case took place in Hofu city, Japan. On July 21, extremely intense rainstorm caused numerous debris flows and mud flows in the hillslopes. Some of the debris flows destroyed residential houses and home for elderly people, and finally killed 14 residents. One of the unusual feature of both disaster was that landslides are distributed in very narrow area. In the 2010 Shobara city disaster, all of the landslides were distributed in 5 km x 3 km, and in the 2009 Hofu city disaster, most devastated zone of landslides were 10 km x 5 km. Rain radars of Meteorological Agency of Government of Japan detected the intense rainfall, however, the spatial resolution is usually larger than 5 km and the disaster area is too small to predict landslides nor issue warning. Furthermore, it was found that the growth rate of baby clouds was very quick. The geology of both areas are rhyolite (Shobara) and granite (Hofu), so the areal assessment of landslide hazard should be prepared before those intense rainfall will come. As for the Hofu city case, it was proved that debris flows took place in the high precipitation area and covered by covered by weathered granite sands and silts which is called “masa". This sands has been proved susceptible against landslides under extreme rainfall conditions. However, the transition from slide - debris flow process is not well revealed, except authors past experiment on the similar masa samples in June 1999 Hiroshima debris flow case. Authors have embedded pore pressure control system for the undrained ring shear apparatus. Strongly weathered sandy soils were sampled just on the smooth and flat granitic sliding surface of one of the upstream small-scale landslides. Those contained finer grains and lower permeability rather than the one sampled in the Hiroshima case. Sample was consolidated by smaller stress corresponding to the site condition, and saturated by overnight circulating de-aired water. Normal stress and shear stress corresponding the slope condition was given, then, pore pressure (back pressure) was raised artificially at constant rate. When the effective stress reached the failure line, suddenly measured pore pressure monitored at about 2 mm above the shear plane, quickly increased. This sudden change abruptly accelerate the shear displacement. Stress condition soon reached the steady state and remained there thereafter. The reason of the excess pore pressure generation was the negative dilatancy, following a slight positive dilatancy. Most of the negative dilatancy could be explained by collapse of loose soil skelton as well as grain crushing during deformation and shearing.

Sediment rating curve & Co. - a contest of prediction methods

NASA Astrophysics Data System (ADS)

Francke, T.; Zimmermann, A.

2012-04-01

In spite of the recent technological progress in sediment monitoring, often the calculation of sediment yield (SSY) still relies on intermittent measurements because of the use of historic records, instrument-failure in continuous recording or financial constraints. Therefore, available measurements are usually inter- and even extrapolated using the sediment rating curve approach, which uses continuously available discharge data to predict sediment concentrations. Extending this idea by further aspects like the inclusion of other predictors (e.g. rainfall, discharge-characteristics, etc.), or the consideration of prediction uncertainty led to a variety of new methods. Now, with approaches such as Fuzzy Logic, Artificial Neural Networks, Tree-based regression, GLMs, etc., the user is left to decide which method to apply. Trying multiple approaches is usually not an option, as considerable effort and expertise may be needed for their application. To establish a helpful guideline in selecting the most appropriate method for SSY-computation, we initiated a study to compare and rank available methods. Depending on problem attributes like hydrological and sediment regime, number of samples, sampling scheme, and availability of ancillary predictors, the performance of different methods is compared. Our expertise allowed us to "register" Random Forests, Quantile Regression Forests and GLMs for the contest. To include many different methods and ensure their sophisticated use we invite scientists that are willing to benchmark their favourite method(s) with us. The more diverse the participating methods are, the more exciting the contest will be.

Implementation of the Short-Term Ensemble Prediction System (STEPS) in Belgium and verification of case studies

NASA Astrophysics Data System (ADS)

Foresti, Loris; Reyniers, Maarten; Delobbe, Laurent

2014-05-01

The Short-Term Ensemble Prediction System (STEPS) is a probabilistic precipitation nowcasting scheme developed at the Australian Bureau of Meteorology in collaboration with the UK Met Office. In order to account for the multiscaling nature of rainfall structures, the radar field is decomposed into an 8 levels multiplicative cascade using a Fast Fourier Transform. The cascade is advected using the velocity field estimated with optical flow and evolves stochastically according to a hierarchy of auto-regressive processes. This allows reproducing the empirical observation that the rate of temporal evolution of the small scales is faster than the large scales. The uncertainty in radar rainfall measurement and the unknown future development of the velocity field are also considered by stochastic modelling in order to reflect their typical spatial and temporal variability. Recently, a 4 years national research program has been initiated by the University of Leuven, the Royal Meteorological Institute (RMI) of Belgium and 3 other partners: PLURISK ("forecasting and management of extreme rainfall induced risks in the urban environment"). The project deals with the nowcasting of rainfall and subsequent urban inundations, as well as socio-economic risk quantification, communication, warning and prevention. At the urban scale it is widely recognized that the uncertainty of hydrological and hydraulic models is largely driven by the input rainfall estimation and forecast uncertainty. In support to the PLURISK project the RMI aims at integrating STEPS in the current operational deterministic precipitation nowcasting system INCA-BE (Integrated Nowcasting through Comprehensive Analysis). This contribution will illustrate examples of STEPS ensemble and probabilistic nowcasts for a few selected case studies of stratiform and convective rain in Belgium. The paper focuses on the development of STEPS products for potential hydrological users and a preliminary verification of the nowcasts, especially to analyze the spatial distribution of forecast errors. The analysis of nowcast biases reveals the locations where the convective initiation, rainfall growth and decay processes significantly reduce the forecast accuracy, but also points out the need for improving the radar-based quantitative precipitation estimation product that is used both to generate and verify the nowcasts. The collection of fields of verification statistics is implemented using an online update strategy, which potentially enables the system to learn from forecast errors as the archive of nowcasts grows. The study of the spatial or temporal distribution of nowcast errors is a key step to convey to the users an overall estimation of the nowcast accuracy and to drive future model developments.

Levels of organochlorine pesticides in the blood of people living in areas of intensive pesticide use in Sudan.

PubMed

Elbashir, Ahmed B; Abdelbagi, Azhari O; Hammad, Ahmed M A; Elzorgani, Gafar A; Laing, Mark D

2015-03-01

Ninety-six human blood samples were collected from six locations that represent areas of intensive pesticide use in Sudan, which included irrigated cotton schemes (Wad Medani, Hasaheesa, Elmanagil, and Elfaw) and sugarcane schemes (Kenana and Gunaid). Blood samples were analyzed for organochlorine pesticide residues by gas liquid chromatography (GLC) equipped with an electron capture detector (ECD). Residues of p,p'-dichlorodiphenyldichloroethylene (DDE), heptachlor epoxide, γ-HCH, and dieldrin were detected in blood from all locations surveyed. Aldrin was not detected in any of the samples analyzed, probably due to its conversion to dieldrin. The levels of total organochlorine burden detected were higher in the blood from people in the irrigated cotton schemes (mean 261 ng ml(-1), range 38-641 ng ml(-1)) than in the blood of people from the irrigated sugarcane schemes (mean 204 ng ml(-1), range 59-365 ng ml(-1)). The highest levels of heptachlor epoxide (170 ng ml(-1)) and γ-HCH (92 ng ml(-1)) were observed in blood samples from Hasaheesa, while the highest levels of DDE (618 ng ml(-1)) and dieldrin (82 ng ml(-1)) were observed in blood samples from Wad Medani and Kenana, respectively. The organochlorine levels in blood samples seemed to decrease with increasing distance from the old irrigated cotton schemes (Wad Medani, Hasaheesa, and Elmanagil) where the heavy application of these pesticides took place historically.

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.

Hydrologic and water-quality data, Honey Creek State Natural Area, Comal County, Texas, August 2001-September 2003

USGS Publications Warehouse

Slattery, Richard N.; Furlow, Allen L.; Ockerman, Darwin J.

2006-01-01

The U.S. Geological Survey collected rainfall, streamflow, evapotranspiration, and rainfall and stormflow water-quality data from seven sites in two adjacent watersheds in the Honey Creek State Natural Area, Comal County, Texas, during August 2001–September 2003, in cooperation with the U.S. Department of Agriculture, Natural Resources Conservation Service, and the San Antonio Water System. Data collected during this period represent baseline hydrologic and water-quality conditions before proposed removal of ashe juniper (Juniperus ashei) from one of the two watersheds. Juniper removal is intended as a best-management practice to increase water quantity (aquifer recharge and streamflow) and to protect water quality. Continuous (5-minute interval) rainfall data are collected at four sites; continuous (5-minute interval) streamflow data are collected at three sites. Fifteen-minute averages of meteorological and solar-energy-related data recorded at two sites are used to compute moving 30-minute evapotranspiration values on the basis of the energy-balance Bowen ratio method. Periodic rainfall water-quality data are collected at one site and stormflow water-quality data at three sites. Daily rainfall, streamflow, and evapotranspiration totals are presented in tables; detailed data are listed in an appendix. Results of analyses of the periodic rainfall and stormflow water-quality samples collected during runoff events are summarized in the appendix; not all data types were collected at all sites nor were all data types collected during the entire 26-month period.

Practical continuous-variable quantum key distribution without finite sampling bandwidth effects.

PubMed

Li, Huasheng; Wang, Chao; Huang, Peng; Huang, Duan; Wang, Tao; Zeng, Guihua

2016-09-05

In a practical continuous-variable quantum key distribution system, finite sampling bandwidth of the employed analog-to-digital converter at the receiver's side may lead to inaccurate results of pulse peak sampling. Then, errors in the parameters estimation resulted. Subsequently, the system performance decreases and security loopholes are exposed to eavesdroppers. In this paper, we propose a novel data acquisition scheme which consists of two parts, i.e., a dynamic delay adjusting module and a statistical power feedback-control algorithm. The proposed scheme may improve dramatically the data acquisition precision of pulse peak sampling and remove the finite sampling bandwidth effects. Moreover, the optimal peak sampling position of a pulse signal can be dynamically calibrated through monitoring the change of the statistical power of the sampled data in the proposed scheme. This helps to resist against some practical attacks, such as the well-known local oscillator calibration attack.

Aircraft Observations of Soil Hydrological Influence on the Atmosphere in Northern India

NASA Astrophysics Data System (ADS)

Taylor, Christopher M.; Barton, Emma J.; Belusic, Danijel; Böing, Steven J.; Hunt, Kieran M. R.; Mitra, Ashis K.; Parker, Douglas J.; Turner, Andrew G.

2017-04-01

India is considered to be a region of the world where the influence of land surface fluxes of sensible and latent heat play an important role in regional weather and climate. Indian rainfall simulations in GCMs are known to be particularly sensitive to soil moisture. However, in a monsoon region where seasonal convective rainfall dominates, it is a big challenge for GCMs to capture, on the one hand, a realistic depiction of surface fluxes during wetting up and drying down at seasonal and sub-seasonal scales, and on the other, the sensitivity of convective rainfall and regional circulations to space-time fluctuations in land surface fluxes. On top of this, most GCMs and operational atmospheric forecast models don't explicitly consider irrigation. In the Indo-Gangetic plains of the Indian sub-continent, irrigated agriculture has become the dominant land use. Irrigation suppresses temporal flux variability for much of the year, and at the same time enhances spatial heterogeneity. One of the key objectives of the Anglo-Indian Interaction of Convective Organization and Monsoon Precipitation, Atmosphere, Surface and Sea (INCOMPASS) collaborative project is to better understand the coupling between the land surface and the Indian summer monsoon, and build this understanding into improved prediction of rainfall on multiple time and space scales. During June and July 2016, a series of research flights was performed across the sub-continent using the NERC/Met Office BAe146 aircraft. Here we will present results for a case study from a flight on 30th June which sampled the Planetary Boundary Layer (PBL) on a 700 km low level transect, from the semi-arid region of Rajasthan eastwards into the extensively irrigated state of Uttar Pradesh. As well as crossing different land uses, the flight also sampled mesoscale regions with contrasting recent rainfall conditions. Here we will show how variations in surface hydrology, driven by both irrigation and rainfall, influence the temperature, humidity and winds in the PBL. These unique observations will provide a powerful tool for understanding the dominant land-atmosphere coupling mechanisms operating on a range of multiple length scales, and which help to shape the Indian monsoon.

Accuration of Time Series and Spatial Interpolation Method for Prediction of Precipitation Distribution on the Geographical Information System

NASA Astrophysics Data System (ADS)

Prasetyo, S. Y. J.; Hartomo, K. D.

2018-01-01

The Spatial Plan of the Province of Central Java 2009-2029 identifies that most regencies or cities in Central Java Province are very vulnerable to landslide disaster. The data are also supported by other data from Indonesian Disaster Risk Index (In Indonesia called Indeks Risiko Bencana Indonesia) 2013 that suggest that some areas in Central Java Province exhibit a high risk of natural disasters. This research aims to develop an application architecture and analysis methodology in GIS to predict and to map rainfall distribution. We propose our GIS architectural application of “Multiplatform Architectural Spatiotemporal” and data analysis methods of “Triple Exponential Smoothing” and “Spatial Interpolation” as our significant scientific contribution. This research consists of 2 (two) parts, namely attribute data prediction using TES method and spatial data prediction using Inverse Distance Weight (IDW) method. We conduct our research in 19 subdistricts in the Boyolali Regency, Central Java Province, Indonesia. Our main research data is the biweekly rainfall data in 2000-2016 Climatology, Meteorology, and Geophysics Agency (In Indonesia called Badan Meteorologi, Klimatologi, dan Geofisika) of Central Java Province and Laboratory of Plant Disease Observations Region V Surakarta, Central Java. The application architecture and analytical methodology of “Multiplatform Architectural Spatiotemporal” and spatial data analysis methodology of “Triple Exponential Smoothing” and “Spatial Interpolation” can be developed as a GIS application framework of rainfall distribution for various applied fields. The comparison between the TES and IDW methods show that relative to time series prediction, spatial interpolation exhibit values that are approaching actual. Spatial interpolation is closer to actual data because computed values are the rainfall data of the nearest location or the neighbour of sample values. However, the IDW’s main weakness is that some area might exhibit the rainfall value of 0. The representation of 0 in the spatial interpolation is mainly caused by the absence of rainfall data in the nearest sample point or too far distance that produces smaller weight.

A study of Bangladesh's sub-surface water storages using satellite products and data assimilation scheme.

PubMed

Khaki, M; Forootan, E; Kuhn, M; Awange, J; Papa, F; Shum, C K

2018-06-01

Climate change can significantly influence terrestrial water changes around the world particularly in places that have been proven to be more vulnerable such as Bangladesh. In the past few decades, climate impacts, together with those of excessive human water use have changed the country's water availability structure. In this study, we use multi-mission remotely sensed measurements along with a hydrological model to separately analyze groundwater and soil moisture variations for the period 2003-2013, and their interactions with rainfall in Bangladesh. To improve the model's estimates of water storages, terrestrial water storage (TWS) data obtained from the Gravity Recovery And Climate Experiment (GRACE) satellite mission are assimilated into the World-Wide Water Resources Assessment (W3RA) model using the ensemble-based sequential technique of the Square Root Analysis (SQRA) filter. We investigate the capability of the data assimilation approach to use a non-regional hydrological model for a regional case study. Based on these estimates, we investigate relationships between the model derived sub-surface water storage changes and remotely sensed precipitations, as well as altimetry-derived river level variations in Bangladesh by applying the empirical mode decomposition (EMD) method. A larger correlation is found between river level heights and rainfalls (78% on average) in comparison to groundwater storage variations and rainfalls (57% on average). The results indicate a significant decline in groundwater storage (∼32% reduction) for Bangladesh between 2003 and 2013, which is equivalent to an average rate of 8.73 ± 2.45mm/year. Copyright © 2018 Elsevier B.V. All rights reserved.

Regional simulation of Indian summer monsoon intraseasonal oscillations at gray-zone resolution

NASA Astrophysics Data System (ADS)

Chen, Xingchao; Pauluis, Olivier M.; Zhang, Fuqing

2018-01-01

Simulations of the Indian summer monsoon by the cloud-permitting Weather Research and Forecasting (WRF) model at gray-zone resolution are described in this study, with a particular emphasis on the model ability to capture the monsoon intraseasonal oscillations (MISOs). Five boreal summers are simulated from 2007 to 2011 using the ERA-Interim reanalysis as the lateral boundary forcing data. Our experimental setup relies on a horizontal grid spacing of 9 km to explicitly simulate deep convection without the use of cumulus parameterizations. When compared to simulations with coarser grid spacing (27 km) and using a cumulus scheme, the 9 km simulations reduce the biases in mean precipitation and produce more realistic low-frequency variability associated with MISOs. Results show that the model at the 9 km gray-zone resolution captures the salient features of the summer monsoon. The spatial distributions and temporal evolutions of monsoon rainfall in the WRF simulations verify qualitatively well against observations from the Tropical Rainfall Measurement Mission (TRMM), with regional maxima located over Western Ghats, central India, Himalaya foothills, and the west coast of Myanmar. The onset, breaks, and withdrawal of the summer monsoon in each year are also realistically captured by the model. The MISO-phase composites of monsoon rainfall, low-level wind, and precipitable water anomalies in the simulations also agree qualitatively with the observations. Both the simulations and observations show a northeastward propagation of the MISOs, with the intensification and weakening of the Somali Jet over the Arabian Sea during the active and break phases of the Indian summer monsoon.

A process-based investigation into the impact of the Congo basin deforestation on surface climate

NASA Astrophysics Data System (ADS)

Bell, Jean P.; Tompkins, Adrian M.; Bouka-Biona, Clobite; Sanda, I. Seidou

2015-06-01

The sensitivity of climate to the loss of the Congo basin rainforest through changes in land cover properties is examined using a regional climate model. The complete removal of the Congo basin rainforest results in a dipole rainfall anomaly pattern, characterized by a decrease (˜-42%) in rainfall over the western Congo and an increase (˜10%) in the basin's eastern part. Three further experiments systematically examine the individual response to the changes in albedo, surface roughness, and evapotranspiration efficiency that accompany deforestation. The increased albedo (˜) caused by the Congo basin rainforest clearance results in cooler and drier climate conditions over the entire basin. The drying is accompanied with a reduction in available surface energy. Reducing evapotranspiration efficiency or roughness length produces similar positive air temperature anomaly patterns. The decreased evapotranspiration efficiency leads to a dipole response in rainfall, similar to that resulting from a reduced surface roughness following Congo basin rainforest clearance. This precipitation anomaly pattern is strongly linked to the change in low-level water vapor transport, the influence of the Rift valley highlands, and the spatial pattern of water recycling activity. The climate responds linearly to the separate albedo, surface roughness, and evapotranspiration efficiency changes, which can be summed to produce a close approximation to the impact of the full deforestation experiment. It is suggested that the widely contrasting climate responses to deforestation in the literature could be partly due to the relative magnitude of change of the radiative and nonradiative parameterizations in their respective land surface schemes.

Effect of rainfall timing and tillage on the transport of steroid hormones in runoff from manure amended row crop fields.

PubMed

Biswas, Sagor; Kranz, William L; Shapiro, Charles A; Snow, Daniel D; Bartelt-Hunt, Shannon L; Mamo, Mitiku; Tarkalson, David D; Zhang, Tian C; Shelton, David P; van Donk, Simon J; Mader, Terry L

2017-02-15

Runoff generated from livestock manure amended row crop fields is one of the major pathways of hormone transport to the aquatic environment. The study determined the effects of manure handling, tillage methods, and rainfall timing on the occurrence and transport of steroid hormones in runoff from the row crop field. Stockpiled and composted manure from hormone treated and untreated animals were applied to test plots and subjected to two rainfall simulation events 30days apart. During the two rainfall simulation events, detection of any steroid hormone or metabolites was identified in 8-86% of runoff samples from any tillage and manure treatment. The most commonly detected hormones were 17β-estradiol, estrone, estriol, testosterone, and α-zearalenol at concentrations ranging up to 100-200ngL -1 . Considering the maximum detected concentrations in runoff, no more than 10% of the applied hormone can be transported through the dissolved phase of runoff. Results from the study indicate that hormones can persist in soils receiving livestock manure over an extended period of time and the dissolved phase of hormone in runoff is not the preferred pathway of transport from the manure applied fields irrespective of tillage treatments and timing of rainfall. Copyright © 2016 Elsevier B.V. All rights reserved.

Trench ‘Bathtubbing’ and Surface Plutonium Contamination at a Legacy Radioactive Waste Site

PubMed Central

2013-01-01

Radioactive waste containing a few grams of plutonium (Pu) was disposed between 1960 and 1968 in trenches at the Little Forest Burial Ground (LFBG), near Sydney, Australia. A water sampling point installed in a former trench has enabled the radionuclide content of trench water and the response of the water level to rainfall to be studied. The trench water contains readily measurable Pu activity (∼12 Bq/L of 239+240Pu in 0.45 μm-filtered water), and there is an associated contamination of Pu in surface soils. The highest 239+240Pu soil activity was 829 Bq/kg in a shallow sample (0–1 cm depth) near the trench sampling point. Away from the trenches, the elevated concentrations of Pu in surface soils extend for tens of meters down-slope. The broader contamination may be partly attributable to dispersion events in the first decade after disposal, after which a layer of soil was added above the trenched area. Since this time, further Pu contamination has occurred near the trench-sampler within this added layer. The water level in the trench-sampler responds quickly to rainfall and intermittently reaches the surface, hence the Pu dispersion is attributed to saturation and overflow of the trenches during extreme rainfall events, referred to as the ‘bathtub’ effect. PMID:24256473

Distribution and Prevalence of Parasitic Nematodes of Cowpea (Vigna unguiculata) in Burkina Faso.

PubMed

Sawadogo, A; Thio, B; Kiemde, S; Drabo, I; Dabire, C; Ouedraogo, J; Mullens, T R; Ehlers, J D; Roberts, P A

2009-06-01

A comprehensive survey of the plant parasitic nematodes associated with cowpea (Vigna unguiculata) production fields was carried out in the three primary agro-climatic zones of Burkina Faso in West Africa. Across the three zones, a total of 109 samples were collected from the farms of 32 villages to provide a representative coverage of the cowpea production areas. Samples of rhizosphere soil and samples of roots from actively growing cowpea plants were collected during mid- to late-season. Twelve plant-parasitic nematode genera were identified, of which six appeared to have significant parasitic potential on cowpea based on their frequency and abundance. These included Helicotylenchus, Meloidogyne, Pratylenchus, Scutellonema, Telotylenchus, and Tylenchorhynchus. Criconemella and Rotylenchulus also had significant levels of abundance and frequency, respectively. Of the primary genera, Meloidogyne, Pratylenchus, and Scutellonema contained species which are known or suspected to cause losses of cowpea yield in other parts of the world. According to the prevalence and distribution of these genera in Burkina Faso, their potential for damage to cowpea increased from the dry Sahelian semi-desert zone in the north (annual rainfall < 600 mm/year), through the north-central Soudanian zone (annual rainfall of 600-800 mm/year), to the wet Soudanian zone (annual rainfall ≥ 1000 mm) in the more humid south-western region of the country. This distribution trend was particularly apparent for the endoparasitic nematode Meloidogyne and the migratory endoparasite Pratylenchus.

Effects of rainfalls variability and physical-chemical parameters on enteroviruses in sewage and lagoon in Yopougon, Côte d'Ivoire

NASA Astrophysics Data System (ADS)

Momou, Kouassi Julien; Akoua-Koffi, Chantal; Traoré, Karim Sory; Akré, Djako Sosthène; Dosso, Mireille

2017-07-01

The aim of this study was to assess the variability of the content of nutrients, oxidizable organic and particulate matters in raw sewage and the lagoon on the effect of rainfall. Then evaluate the impact of these changes in the concentration of enteroviruses (EVs) in waters. The sewage samples were collected at nine sampling points along the channel, which flows, into a tropical lagoon in Yopougon. Physical-chemical parameters (5-day Biochemical Oxygen Demand, Chemical Oxygen Demand, Suspended Particulate Matter, Total Phosphorus, Orthophosphate, Total Kjeldahl Nitrogen and Nitrate) as well as the concentration of EV in these waters were determined. The average numbers of EV isolated from the outlet of the channel were 9.06 × 104 PFU 100 ml-1. Consequently, EV was present in 55.55 and 33.33 % of the samples in the 2 brackish lagoon collection sites. The effect of rainfall on viral load at the both sewage and brackish lagoon environments is significant correlate (two-way ANOVA, P < 0.05). Furthermore, in lagoon environment, nutrients (Orthophosphate, Total Phosphorus), 5-day Biochemical Oxygen Demand, Chemical Oxygen Demand and Suspended Particulate Matter were significant correlated with EVs loads ( P < 0.05 by Pearson test). The overall results highlight the problem of sewage discharge into the lagoon and correlation between viral loads and water quality parameters in sewage and lagoon.

Probabilistic modelling of overflow, surcharge and flooding in urban drainage using the first-order reliability method and parameterization of local rain series.

PubMed

Thorndahl, S; Willems, P

2008-01-01

Failure of urban drainage systems may occur due to surcharge or flooding at specific manholes in the system, or due to overflows from combined sewer systems to receiving waters. To quantify the probability or return period of failure, standard approaches make use of the simulation of design storms or long historical rainfall series in a hydrodynamic model of the urban drainage system. In this paper, an alternative probabilistic method is investigated: the first-order reliability method (FORM). To apply this method, a long rainfall time series was divided in rainstorms (rain events), and each rainstorm conceptualized to a synthetic rainfall hyetograph by a Gaussian shape with the parameters rainstorm depth, duration and peak intensity. Probability distributions were calibrated for these three parameters and used on the basis of the failure probability estimation, together with a hydrodynamic simulation model to determine the failure conditions for each set of parameters. The method takes into account the uncertainties involved in the rainstorm parameterization. Comparison is made between the failure probability results of the FORM method, the standard method using long-term simulations and alternative methods based on random sampling (Monte Carlo direct sampling and importance sampling). It is concluded that without crucial influence on the modelling accuracy, the FORM is very applicable as an alternative to traditional long-term simulations of urban drainage systems.

Bacterial contamination of tile drainage water and shallow groundwater under different application methods of liquid swine manure.

PubMed

Samarajeewa, A D; Glasauer, S M; Lauzon, J D; O'Halloran, I P; Parkin, Gary W; Dunfield, K E

2012-05-01

A 2 year field experiment evaluated liquid manure application methods on the movement of manure-borne pathogens (Salmonella sp.) and indicator bacteria (Escherichia coli and Clostridium perfringens) to subsurface water. A combination of application methods including surface application, pre-application tillage, and post-application incorporation were applied in a randomized complete block design on an instrumented field site in spring 2007 and 2008. Tile and shallow groundwater were sampled immediately after manure application and after rainfall events. Bacterial enumeration from water samples showed that the surface-applied manure resulted in the highest concentration of E. coli in tile drainage water. Pre-tillage significantly (p < 0.05) reduced the movement of manure-based E. coli and C. perfringens to tile water and to shallow groundwater within 3 days after manure application (DAM) in 2008 and within 10 DAM in 2007. Pre-tillage also decreased the occurrence of Salmonella sp. in tile water samples. Indicator bacteria and pathogens reached nondetectable levels within 50 DAM. The results suggest that tillage before application of liquid swine manure can minimize the movement of bacteria to tile and groundwater, but is effective only for the drainage events immediately after manure application or initial rainfall-associated drainage flows. Furthermore, the study highlights the strong association between bacterial concentrations in subsurface waters and rainfall timing and volume after manure application.

Integration of electromagnetic induction sensor data in soil sampling scheme optimization using simulated annealing.

PubMed

Barca, E; Castrignanò, A; Buttafuoco, G; De Benedetto, D; Passarella, G

2015-07-01

Soil survey is generally time-consuming, labor-intensive, and costly. Optimization of sampling scheme allows one to reduce the number of sampling points without decreasing or even increasing the accuracy of investigated attribute. Maps of bulk soil electrical conductivity (EC a ) recorded with electromagnetic induction (EMI) sensors could be effectively used to direct soil sampling design for assessing spatial variability of soil moisture. A protocol, using a field-scale bulk EC a survey, has been applied in an agricultural field in Apulia region (southeastern Italy). Spatial simulated annealing was used as a method to optimize spatial soil sampling scheme taking into account sampling constraints, field boundaries, and preliminary observations. Three optimization criteria were used. the first criterion (minimization of mean of the shortest distances, MMSD) optimizes the spreading of the point observations over the entire field by minimizing the expectation of the distance between an arbitrarily chosen point and its nearest observation; the second criterion (minimization of weighted mean of the shortest distances, MWMSD) is a weighted version of the MMSD, which uses the digital gradient of the grid EC a data as weighting function; and the third criterion (mean of average ordinary kriging variance, MAOKV) minimizes mean kriging estimation variance of the target variable. The last criterion utilizes the variogram model of soil water content estimated in a previous trial. The procedures, or a combination of them, were tested and compared in a real case. Simulated annealing was implemented by the software MSANOS able to define or redesign any sampling scheme by increasing or decreasing the original sampling locations. The output consists of the computed sampling scheme, the convergence time, and the cooling law, which can be an invaluable support to the process of sampling design. The proposed approach has found the optimal solution in a reasonable computation time. The use of bulk EC a gradient as an exhaustive variable, known at any node of an interpolation grid, has allowed the optimization of the sampling scheme, distinguishing among areas with different priority levels.

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.

The association of weather and mortality in Bangladesh from 1983–2009

PubMed Central

Alam, Nurul; Begum, Dilruba; Streatfield, Peter Kim

2012-01-01

Introduction The association of weather and mortality have not been widely studied in subtropical monsoon regions, particularly in Bangladesh. This study aims to assess the association of weather and mortality (measured with temperature and rainfall), adjusting for time trend and seasonal patterns in Abhoynagar, Bangladesh. Material and methods A sample vital registration system (SVRS) was set up in 1982 to facilitate operational research in family planning and maternal and child health. SVRS provided data on death counts and population from 1983–2009. The Bangladesh Meteorological Department provided data on daily temperature and rainfall for the same period. Time series Poisson regression with cubic spline functions was used, allowing for over-dispersion, including lagged weather parameters, and adjusting for time trends and seasonal patterns. Analysis was carried out using R statistical software. Results Both weekly mean temperature and rainfall showed strong seasonal patterns. After adjusting for seasonal pattern and time trend, weekly mean temperatures (lag 0) below the 25th percentile and between the 25th and 75th percentiles were associated with increased mortality risk, particularly in females and adults aged 20–59 years by 2.3–2.4% for every 1°C decrease. Temperature above the 75th percentile did not increase the risk. Every 1 mm increase in rainfall up to 14 mm of weekly average rainfall over lag 0–4 weeks was associated with decreased mortality risks. Rainfall above 14 mm was associated with increased mortality risk. Conclusion The relationships between temperature, rainfall and mortality reveal the importance of understanding the current factors contributing to adaptation and acclimatization, and how these can be enhanced to reduce negative impacts from weather. PMID:23195512

Stable Isotopes as Indicators of Groundwater Recharge Mechanisms in Arid and Semi-arid Australia

NASA Astrophysics Data System (ADS)

Harrington, G. A.; Herczeg, A. L.

2001-05-01

The isotopic compositions of soil water and groundwaters in arid and semi-arid zones are always different from the mean composition of rainfall. Although evaporative processes always remove the lighter isotopes (1H and 16O) to the vapour phase, arid zone groundwaters are invariably depleted in the heavy isotopes (2H and 18O) relative to mean present day rainfall. We compare two sites, one in semi-arid South Australia and the other in arid Central Australia that have a similar mean annual rainfall (250 to 300 mm/a), very high potential evapotranspiration (2500 and 3500 mm/a respectively) but very different rainfall patterns (winter dominated versus summer monsoonal). We aim to evaluate whether inferences from groundwater \\delta2H and \\delta18O reveal information about palaeorecharge, or recharge mechanisms or a combination of both. Recharge to the unconfined limestone aquifer in the Mallee area of South Australia occurs annually via widespread (diffuse) infiltration of winter dominant rainfall. This process is reflected in soil and groundwater isotopic compositions that plot relatively close to both the Local Meteoric Water Line and the volume-weighted mean composition of winter rainfall, and have a deuterium excess (\\delta2H-8.\\delta18O) of between +2 and +8 for the freshest samples. Groundwater recharge to the arid Ti-Tree Basin occurs predominantly by inputs of partially-evaporated surface water from ephemeral rivers and flood-plains following rare, high-intensity storms that are derived from monsoonal activity to the north of Australia. These extreme events result in groundwater and soil water stable isotope compositions being significantly depleted in the heavy isotopes relative to the mean composition of rainfall and a deuterium excess of between minus 8 and +3 in the freshest groundwaters.

Decadal prediction of Sahel rainfall: where does the skill (or lack thereof) come from?

NASA Astrophysics Data System (ADS)

Mohino, Elsa; Keenlyside, Noel; Pohlmann, Holger

2016-12-01

Previous works suggest decadal predictions of Sahel rainfall could be skillful. However, the sources of such skill are still under debate. In addition, previous results are based on short validation periods (i.e. less than 50 years). In this work we propose a framework based on multi-linear regression analysis to study the potential sources of skill for predicting Sahel trends several years ahead. We apply it to an extended decadal hindcast performed with the MPI-ESM-LR model that span from 1901 to 2010 with 1 year sampling interval. Our results show that the skill mainly depends on how well we can predict the timing of the global warming (GW), the Atlantic multidecadal variability (AMV) and, to a lesser extent, the inter-decadal Pacific oscillation signals, and on how well the system simulates the associated SST and West African rainfall response patterns. In the case of the MPI-ESM-LR decadal extended hindcast, the observed timing is well reproduced only for the GW and AMV signals. However, only the West African rainfall response to the AMV is correctly reproduced. Thus, for most of the lead times the main source of skill in the decadal hindcast of West African rainfall is from the AMV. The GW signal degrades skill because the response of West African rainfall to GW is incorrectly captured. Our results also suggest that initialized decadal predictions of West African rainfall can be further improved by better simulating the response of global SST to GW and AMV. Furthermore, our approach may be applied to understand and attribute prediction skill for other variables and regions.

Responses of hydrochemical inorganic ions in the rainfall-runoff processes of the experimental catchments and its significance for tracing

USGS Publications Warehouse

Gu, W.-Z.; Lu, J.-J.; Zhao, X.; Peters, N.E.

2007-01-01

Aimed at the rainfall-runoff tracing using inorganic ions, the experimental study is conducted in the Chuzhou Hydrology Laboratory with special designed experimental catchments, lysimeters, etc. The various runoff components including the surface runoff, interflow from the unsaturated zone and the groundwater flow from saturated zone were monitored hydrometrically. Hydrochemical inorganic ions including Na+, K+, Ca2+, Mg2+, Cl-, SO42-, HCO3- + CO32-, NO3-, F-, NH4-, PO42-, SiO2 and, pH, EC, 18O were measured within a one month period for all processes of rainfall, various runoff components and groundwater within the catchment from 17 boreholes distributed in the Hydrohill Catchment, few soil water samples were also included. The results show that: (a) all the runoff components are distinctly identifiable from both the relationships of Ca2+ versus Cl-/SO42-, EC versus Na+/(Na+ + Ca2+) and, from most inorganic ions individually; (b) the variation of inorganic ions in surface runoff is the biggest than that in other flow components; (c) most ions has its lowermost concentration in rainfall process but it increases as the generation depths of runoff components increased; (d) quantitatively, ion processes of rainfall and groundwater flow display as two end members of that of other runoff components; and (e) the 18O processes of rainfall and runoff components show some correlation with that of inorganic ions. The results also show that the rainfall input is not always the main source of inorganic ions of various runoff outputs due to the process of infiltration and dissolution resulted from the pre-event processes. The amount and sources of Cl- of runoff components with various generation mechanisms challenge the current method of groundwater recharge estimation using Cl-.

Sampling for area estimation: A comparison of full-frame sampling with the sample segment approach

NASA Technical Reports Server (NTRS)

Hixson, M.; Bauer, M. E.; Davis, B. J. (Principal Investigator)

1979-01-01

The author has identified the following significant results. Full-frame classifications of wheat and non-wheat for eighty counties in Kansas were repetitively sampled to simulate alternative sampling plans. Evaluation of four sampling schemes involving different numbers of samples and different size sampling units shows that the precision of the wheat estimates increased as the segment size decreased and the number of segments was increased. Although the average bias associated with the various sampling schemes was not significantly different, the maximum absolute bias was directly related to sampling size unit.

An Empirical Cumulus Parameterization Scheme for a Global Spectral Model

NASA Technical Reports Server (NTRS)

Rajendran, K.; Krishnamurti, T. N.; Misra, V.; Tao, W.-K.

2004-01-01

Realistic vertical heating and drying profiles in a cumulus scheme is important for obtaining accurate weather forecasts. A new empirical cumulus parameterization scheme based on a procedure to improve the vertical distribution of heating and moistening over the tropics is developed. The empirical cumulus parameterization scheme (ECPS) utilizes profiles of Tropical Rainfall Measuring Mission (TRMM) based heating and moistening derived from the European Centre for Medium- Range Weather Forecasts (ECMWF) analysis. A dimension reduction technique through rotated principal component analysis (RPCA) is performed on the vertical profiles of heating (Q1) and drying (Q2) over the convective regions of the tropics, to obtain the dominant modes of variability. Analysis suggests that most of the variance associated with the observed profiles can be explained by retaining the first three modes. The ECPS then applies a statistical approach in which Q1 and Q2 are expressed as a linear combination of the first three dominant principal components which distinctly explain variance in the troposphere as a function of the prevalent large-scale dynamics. The principal component (PC) score which quantifies the contribution of each PC to the corresponding loading profile is estimated through a multiple screening regression method which yields the PC score as a function of the large-scale variables. The profiles of Q1 and Q2 thus obtained are found to match well with the observed profiles. The impact of the ECPS is investigated in a series of short range (1-3 day) prediction experiments using the Florida State University global spectral model (FSUGSM, T126L14). Comparisons between short range ECPS forecasts and those with the modified Kuo scheme show a very marked improvement in the skill in ECPS forecasts. This improvement in the forecast skill with ECPS emphasizes the importance of incorporating realistic vertical distributions of heating and drying in the model cumulus scheme. This also suggests that in the absence of explicit models for convection, the proposed statistical scheme improves the modeling of the vertical distribution of heating and moistening in areas of deep convection.

Application of a medium-range global hydrologic probabilistic forecast scheme to the Ohio River Basin

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

Voisin, Nathalie; Pappenberger, Florian; Lettenmaier, D. P.

2011-08-15

A 10-day globally applicable flood prediction scheme was evaluated using the Ohio River basin as a test site for the period 2003-2007. The Variable Infiltration Capacity (VIC) hydrology model was initialized with the European Centre for Medium Range Weather Forecasts (ECMWF) analysis temperatures and wind, and Tropical Rainfall Monitoring Mission Multi Satellite Precipitation Analysis (TMPA) precipitation up to the day of forecast. In forecast mode, the VIC model was then forced with a calibrated and statistically downscaled ECMWF ensemble prediction system (EPS) 10-day ensemble forecast. A parallel set up was used where ECMWF EPS forecasts were interpolated to the spatialmore » scale of the hydrology model. Each set of forecasts was extended by 5 days using monthly mean climatological variables and zero precipitation in order to account for the effect of initial conditions. The 15-day spatially distributed ensemble runoff forecasts were then routed to four locations in the basin, each with different drainage areas. Surrogates for observed daily runoff and flow were provided by the reference run, specifically VIC simulation forced with ECMWF analysis fields and TMPA precipitation fields. The flood prediction scheme using the calibrated and downscaled ECMWF EPS forecasts was shown to be more accurate and reliable than interpolated forecasts for both daily distributed runoff forecasts and daily flow forecasts. Initial and antecedent conditions dominated the flow forecasts for lead times shorter than the time of concentration depending on the flow forecast amounts and the drainage area sizes. The flood prediction scheme had useful skill for the 10 following days at all sites.« less

Statistical Determination of Rainfall-Runoff Erosivity Indices for Single Storms in the Chinese Loess Plateau

PubMed Central

Zheng, Mingguo; Chen, Xiaoan

2015-01-01

Correlation analysis is popular in erosion- or earth-related studies, however, few studies compare correlations on a basis of statistical testing, which should be conducted to determine the statistical significance of the observed sample difference. This study aims to statistically determine the erosivity index of single storms, which requires comparison of a large number of dependent correlations between rainfall-runoff factors and soil loss, in the Chinese Loess Plateau. Data observed at four gauging stations and five runoff experimental plots were presented. Based on the Meng’s tests, which is widely used for comparing correlations between a dependent variable and a set of independent variables, two methods were proposed. The first method removes factors that are poorly correlated with soil loss from consideration in a stepwise way, while the second method performs pairwise comparisons that are adjusted using the Bonferroni correction. Among 12 rainfall factors, I 30 (the maximum 30-minute rainfall intensity) has been suggested for use as the rainfall erosivity index, although I 30 is equally correlated with soil loss as factors of I 20, EI 10 (the product of the rainfall kinetic energy, E, and I 10), EI 20 and EI 30 are. Runoff depth (total runoff volume normalized to drainage area) is more correlated with soil loss than all other examined rainfall-runoff factors, including I 30, peak discharge and many combined factors. Moreover, sediment concentrations of major sediment-producing events are independent of all examined rainfall-runoff factors. As a result, introducing additional factors adds little to the prediction accuracy of the single factor of runoff depth. Hence, runoff depth should be the best erosivity index at scales from plots to watersheds. Our findings can facilitate predictions of soil erosion in the Loess Plateau. Our methods provide a valuable tool while determining the predictor among a number of variables in terms of correlations. PMID:25781173

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

Statistical determination of rainfall-runoff erosivity indices for single storms in the Chinese Loess Plateau.

PubMed

Zheng, Mingguo; Chen, Xiaoan

2015-01-01

Correlation analysis is popular in erosion- or earth-related studies, however, few studies compare correlations on a basis of statistical testing, which should be conducted to determine the statistical significance of the observed sample difference. This study aims to statistically determine the erosivity index of single storms, which requires comparison of a large number of dependent correlations between rainfall-runoff factors and soil loss, in the Chinese Loess Plateau. Data observed at four gauging stations and five runoff experimental plots were presented. Based on the Meng's tests, which is widely used for comparing correlations between a dependent variable and a set of independent variables, two methods were proposed. The first method removes factors that are poorly correlated with soil loss from consideration in a stepwise way, while the second method performs pairwise comparisons that are adjusted using the Bonferroni correction. Among 12 rainfall factors, I30 (the maximum 30-minute rainfall intensity) has been suggested for use as the rainfall erosivity index, although I30 is equally correlated with soil loss as factors of I20, EI10 (the product of the rainfall kinetic energy, E, and I10), EI20 and EI30 are. Runoff depth (total runoff volume normalized to drainage area) is more correlated with soil loss than all other examined rainfall-runoff factors, including I30, peak discharge and many combined factors. Moreover, sediment concentrations of major sediment-producing events are independent of all examined rainfall-runoff factors. As a result, introducing additional factors adds little to the prediction accuracy of the single factor of runoff depth. Hence, runoff depth should be the best erosivity index at scales from plots to watersheds. Our findings can facilitate predictions of soil erosion in the Loess Plateau. Our methods provide a valuable tool while determining the predictor among a number of variables in terms of correlations.

Analysis of the influence of rainfall variables on urban effluents concentrations and fluxes in wet weather

NASA Astrophysics Data System (ADS)

Gooré Bi, Eustache; Monette, Frédéric; Gasperi, Johnny

2015-04-01

Urban rainfall runoff has been a topic of increasing importance over the past years, a result of both the increase in impervious land area arising from constant urban growth and the effects of climate change on urban drainage. The main goal of the present study is to assess and analyze the correlations between rainfall variables and common indicators of urban water quality, namely event mean concentrations (EMCs) and event fluxes (EFs), in order to identify and explain the impacts of each of the main rainfall variables on the generation process of urban pollutants during wet periods. To perform this analysis, runoff from eight summer rainfall events that resulted in combined sewer overflow (CSO) was sampled simultaneously from two distinct catchment areas in order to quantify discharges at the respective outfalls. Pearson statistical analysis of total suspended solids (TSS), chemical oxygen demand (COD), carbonaceous biochemical oxygen demand at 5 days (CBOD5), total phosphorus (Ptot) and total kedjal nitrogen (N-TKN) showed significant correlations (ρ = 0.05) between dry antecedent time (DAT) and EMCs on one hand, and between total rainfall (TR) and the volume discharged (VD) during EFs, on the other. These results show that individual rainfall variables strongly affect either EMCs or EFs and are good predictors to consider when selecting variables for statistical modeling of urban runoff quality. The results also show that in a combined sewer network, there is a linear relationship between TSS event fluxes and COD, CBOD5, Ptot, and N-TKN event fluxes; this explains 97% of the variability of these pollutants which adsorb onto TSS during wet weather, which therefore act as tracers. Consequently, the technological solution selected for TSS removal will also lead to a reduction of these pollutants. Given the huge volumes involved, urban runoffs contribute substantially to pollutant levels in receiving water bodies, a situation which, in a climate change context, may get much worse as a result of more frequent, shorter, but more intense rainfall events.

Numerical Solution of Dyson Brownian Motion and a Sampling Scheme for Invariant Matrix Ensembles

NASA Astrophysics Data System (ADS)

Li, Xingjie Helen; Menon, Govind

2013-12-01

The Dyson Brownian Motion (DBM) describes the stochastic evolution of N points on the line driven by an applied potential, a Coulombic repulsion and identical, independent Brownian forcing at each point. We use an explicit tamed Euler scheme to numerically solve the Dyson Brownian motion and sample the equilibrium measure for non-quadratic potentials. The Coulomb repulsion is too singular for the SDE to satisfy the hypotheses of rigorous convergence proofs for tamed Euler schemes (Hutzenthaler et al. in Ann. Appl. Probab. 22(4):1611-1641, 2012). Nevertheless, in practice the scheme is observed to be stable for time steps of O(1/ N 2) and to relax exponentially fast to the equilibrium measure with a rate constant of O(1) independent of N. Further, this convergence rate appears to improve with N in accordance with O(1/ N) relaxation of local statistics of the Dyson Brownian motion. This allows us to use the Dyson Brownian motion to sample N× N Hermitian matrices from the invariant ensembles. The computational cost of generating M independent samples is O( MN 4) with a naive scheme, and O( MN 3log N) when a fast multipole method is used to evaluate the Coulomb interaction.

Classical and generalized Horton laws for peak flows in rainfall-runoff events.

PubMed

Gupta, Vijay K; Ayalew, Tibebu B; Mantilla, Ricardo; Krajewski, Witold F

2015-07-01

The discovery of the Horton laws for hydrologic variables has greatly lagged behind geomorphology, which began with Robert Horton in 1945. We define the classical and the generalized Horton laws for peak flows in rainfall-runoff events, which link self-similarity in network geomorphology with river basin hydrology. Both the Horton laws are tested in the Iowa River basin in eastern Iowa that drains an area of approximately 32 400 km(2) before it joins the Mississippi River. The US Geological Survey continuously monitors the basin through 34 stream gauging stations. We select 51 rainfall-runoff events for carrying out the tests. Our findings support the existence of the classical and the generalized Horton laws for peak flows, which may be considered as a new hydrologic discovery. Three different methods are illustrated for estimating the Horton peak-flow ratio due to small sample size issues in peak flow data. We illustrate an application of the Horton laws for diagnosing parameterizations in a physical rainfall-runoff model. The ideas and developments presented here offer exciting new directions for hydrologic research and education.

The impact of air pollutants on rainwater chemistry during "urban-induced heavy rainfall" in downtown Tokyo, Japan

NASA Astrophysics Data System (ADS)

Uchiyama, Ryunosuke; Okochi, Hiroshi; Katsumi, Naoya; Ogata, Hiroko

2017-06-01

In order to clarify the impact of air pollution on the formation of sudden and locally distributed heavy rain in urban areas (hereafter UHR = urban-induced heavy rain), we analyzed inorganic ions in rainwater samples collected on an event basis over 5 years from October 2012 to December 2016 in Shinjuku, Tokyo. Hourly rainfall amounts and wet deposition fluxes of acidic components (the sum of H+, NH4+, NO3-, and nonsea-salt SO42-) in UHR were 13.1 and 17.8 times larger than those in normal rainfall, respectively, indicating that large amount of air pollutants were scavenged and deposited by UHR with large amounts of rainfall. The level of air pollutants, such as NO2, SO2, and potential ozone, in the ambient air increased just before the formation of UHR and decreased sharply at the end of the UHR event. These results indicate that NO2, which was formed secondarily by oxidants, was further oxidized by HO radicals and formed HNO3 just before the formation of UHR, which was subsequently scavenged by UHR.

Lentic small water bodies: Variability of pesticide transport and transformation patterns.

PubMed

Ulrich, Uta; Hörmann, Georg; Unger, Malte; Pfannerstill, Matthias; Steinmann, Frank; Fohrer, Nicola

2018-03-15

Lentic small water bodies have a high ecological potential as they fulfill several ecosystem services such as the retention of water and pollutants. They serve as a hot spot of biodiversity. Due to their location in or adjacent to agricultural fields, they can be influenced by inputs of pesticides and their transformation products. Since small water bodies have rarely been part of monitorings/campaigns up to now, their current exposure and processes guiding the pesticide input are not understood, yet. This study presents results of a sampling campaign of 10 lentic small water bodies from 2015 to 2016. They were sampled once after the spring application for a pesticide target screening, before autumn application and three times after rainfall events following the application. The autumn sampling focused on the herbicides metazachlor, flufenacet and their transformation products - oxalic acid and - sulfonic acid as representatives for common pesticides in the study region. The concentrations were associated with rainfall before and after application, characteristics of the site and the water bodies, physicochemical parameters and the applied amount of pesticides. The key results of the pesticide screening in spring indicate positive detections of pesticides which have not been applied for years to the single fields. The autumn sampling showed frequent occurrences of the transformation products, which are formed in soil, from 39% to 94% of all samples (n=71). Discharge patterns were observed for metazachlor with highest concentrations in the first sample after application and then decreasing, but not for flufenacet. The concentrations of the transformation products increased over time and revealed highest values mainly in the last sample. Besides rainfall patterns right after application, the spatial and temporal dissemination of the pesticides to the water bodies seems to play a major role to understand the exposure of lentic small water bodies. Copyright © 2017 Elsevier B.V. All rights reserved.

Sampling strategies for subsampled segmented EPI PRF thermometry in MR guided high intensity focused ultrasound

PubMed Central

Odéen, Henrik; Todd, Nick; Diakite, Mahamadou; Minalga, Emilee; Payne, Allison; Parker, Dennis L.

2014-01-01

Purpose: To investigate k-space subsampling strategies to achieve fast, large field-of-view (FOV) temperature monitoring using segmented echo planar imaging (EPI) proton resonance frequency shift thermometry for MR guided high intensity focused ultrasound (MRgHIFU) applications. Methods: Five different k-space sampling approaches were investigated, varying sample spacing (equally vs nonequally spaced within the echo train), sampling density (variable sampling density in zero, one, and two dimensions), and utilizing sequential or centric sampling. Three of the schemes utilized sequential sampling with the sampling density varied in zero, one, and two dimensions, to investigate sampling the k-space center more frequently. Two of the schemes utilized centric sampling to acquire the k-space center with a longer echo time for improved phase measurements, and vary the sampling density in zero and two dimensions, respectively. Phantom experiments and a theoretical point spread function analysis were performed to investigate their performance. Variable density sampling in zero and two dimensions was also implemented in a non-EPI GRE pulse sequence for comparison. All subsampled data were reconstructed with a previously described temporally constrained reconstruction (TCR) algorithm. Results: The accuracy of each sampling strategy in measuring the temperature rise in the HIFU focal spot was measured in terms of the root-mean-square-error (RMSE) compared to fully sampled “truth.” For the schemes utilizing sequential sampling, the accuracy was found to improve with the dimensionality of the variable density sampling, giving values of 0.65 °C, 0.49 °C, and 0.35 °C for density variation in zero, one, and two dimensions, respectively. The schemes utilizing centric sampling were found to underestimate the temperature rise, with RMSE values of 1.05 °C and 1.31 °C, for variable density sampling in zero and two dimensions, respectively. Similar subsampling schemes with variable density sampling implemented in zero and two dimensions in a non-EPI GRE pulse sequence both resulted in accurate temperature measurements (RMSE of 0.70 °C and 0.63 °C, respectively). With sequential sampling in the described EPI implementation, temperature monitoring over a 192 × 144 × 135 mm3 FOV with a temporal resolution of 3.6 s was achieved, while keeping the RMSE compared to fully sampled “truth” below 0.35 °C. Conclusions: When segmented EPI readouts are used in conjunction with k-space subsampling for MR thermometry applications, sampling schemes with sequential sampling, with or without variable density sampling, obtain accurate phase and temperature measurements when using a TCR reconstruction algorithm. Improved temperature measurement accuracy can be achieved with variable density sampling. Centric sampling leads to phase bias, resulting in temperature underestimations. PMID:25186406

Salivary hormone and immune responses to three resistance exercise schemes in elite female athletes.

PubMed

Nunes, João A; Crewther, Blair T; Ugrinowitsch, Carlos; Tricoli, Valmor; Viveiros, Luís; de Rose, Dante; Aoki, Marcelo S

2011-08-01

This study examined the salivary hormone and immune responses of elite female athletes to 3 different resistance exercise schemes. Fourteen female basketball players each performed an endurance scheme (ES-4 sets of 12 reps, 60% of 1 repetition maximum (1RM) load, 1-minute rest periods), a strength-hypertrophy scheme (SHS-1 set of 5RM, 1 set of 4RM, 1 set of 3RM, 1 set of 2RM, and 1set of 1RM with 3-minute rest periods, followed by 3 sets of 10RM with 2-minute rest periods) and a power scheme (PS-3 sets of 10 reps, 50% 1RM load, 3-minute rest periods) using the same exercises (bench press, squat, and biceps curl). Saliva samples were collected at 07:30 hours, pre-exercise (Pre) at 09:30 hours, postexercise (Post), and at 17:30 hours. Matching samples were also taken on a nonexercising control day. The samples were analyzed for testosterone, cortisol (C), and immunoglobulin A concentrations. The total volume of load lifted differed among the 3 schemes (SHS > ES > PS, p < 0.05). Postexercise C concentrations increased after all schemes, compared to control values (p < 0.05). In the SHS, the postexercise C response was also greater than pre-exercise data (p < 0.05). The current findings confirm that high-volume resistance exercise schemes can stimulate greater C secretion because of higher metabolic demand. In terms of practical applications, acute changes in C may be used to evaluate the metabolic demands of different resistance exercise schemes, or as a tool for monitoring training strain.

Real-time photonic sampling with improved signal-to-noise and distortion ratio using polarization-dependent modulators

NASA Astrophysics Data System (ADS)

Liang, Dong; Zhang, Zhiyao; Liu, Yong; Li, Xiaojun; Jiang, Wei; Tan, Qinggui

2018-04-01

A real-time photonic sampling structure with effective nonlinearity suppression and excellent signal-to-noise ratio (SNR) performance is proposed. The key points of this scheme are the polarization-dependent modulators (P-DMZMs) and the sagnac loop structure. Thanks to the polarization sensitive characteristic of P-DMZMs, the differences between transfer functions of the fundamental signal and the distortion become visible. Meanwhile, the selection of specific biases in P-DMZMs is helpful to achieve a preferable linearized performance with a low noise level for real-time photonic sampling. Compared with the quadrature-biased scheme, the proposed scheme is capable of valid nonlinearity suppression and is able to provide a better SNR performance even in a large frequency range. The proposed scheme is proved to be effective and easily implemented for real time photonic applications.

Implementation of a cryo-electron tomography tilt-scheme optimized for high resolution subtomogram averaging.

PubMed

Hagen, Wim J H; Wan, William; Briggs, John A G

2017-02-01

Cryo-electron tomography (cryoET) allows 3D structural information to be obtained from cells and other biological samples in their close-to-native state. In combination with subtomogram averaging, detailed structures of repeating features can be resolved. CryoET data is collected as a series of images of the sample from different tilt angles; this is performed by physically rotating the sample in the microscope between each image. The angles at which the images are collected, and the order in which they are collected, together are called the tilt-scheme. Here we describe a "dose-symmetric tilt-scheme" that begins at low tilt and then alternates between increasingly positive and negative tilts. This tilt-scheme maximizes the amount of high-resolution information maintained in the tomogram for subsequent subtomogram averaging, and may also be advantageous for other applications. We describe implementation of the tilt-scheme in combination with further data-collection refinements including setting thresholds on acceptable drift and improving focus accuracy. Requirements for microscope set-up are introduced, and a macro is provided which automates the application of the tilt-scheme within SerialEM. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Predictive performance of rainfall thresholds for shallow landslide triggering in Switzerland from daily gridded precipitation data

NASA Astrophysics Data System (ADS)

Leonarduzzi, E.; Molnar, P.; McArdell, B. W.

2017-12-01

In Switzerland floods are responsible for most of the damage caused by rainfall-triggered natural hazards (89%), followed by landslides (6%, almost 600 M USD) as reported in Hilker et al. (2009) for the period 1972-2007. A high-resolution gridded daily precipitation dataset is combined with a landslide inventory containing over 2000 events in the period 1972-2012 to analyze rainfall thresholds that lead to landsliding in Switzerland. First triggering rainfall and landslides are co-located obtaining the distributions of triggering and non-triggering rainfall event properties at the scale of the precipitation data (2*2 km2) and considering 1 day as the interarrival time to separate events. Then rainfall thresholds are obtained by maximizing true positives (accurate predictions) while minimizing false negatives (false alarms), using the True Skill Statistic. The best predictive performance is obtained by the intensity-duration ID threshold curve, followed by peak daily intensity (Imax) and mean event intensity (Imean). Event duration by itself has very low predictive power. In addition to country-wide thresholds, local ones are also defined by regionalization based on surface erodibility and local long-term climate (mean daily precipitation). Different Imax thresholds are determined for each of the regions separately. It is found that wetter local climate and lower erodibility lead to significantly higher rainfall thresholds required to trigger landslides. However, the improvement in model performance due to regionalization is marginal and much lower than what can be achieved by having a high quality landslide database. In order to validate the performance of the Imax rainfall threshold model, reference cases will be presented in which the landslide locations and timing are randomized and the landslide sample size is reduced. Jack-knife and cross-validation experiments demonstrate that the model is robust. The results highlight the potential of using rainfall I-D threshold curves and Imax threshold values for predicting the occurrence of landslides on a country or regional scale even with daily precipitation data, with possible applications in landslide warning systems.

Sampling strategies for efficient estimation of tree foliage biomass

Treesearch

Hailemariam Temesgen; Vicente Monleon; Aaron Weiskittel; Duncan Wilson

2011-01-01

Conifer crowns can be highly variable both within and between trees, particularly with respect to foliage biomass and leaf area. A variety of sampling schemes have been used to estimate biomass and leaf area at the individual tree and stand scales. Rarely has the effectiveness of these sampling schemes been compared across stands or even across species. In addition,...

Performance Analysis of a Citywide Real-time Landslide Early Warning System in Korea

NASA Astrophysics Data System (ADS)

Park, Joon-Young; Lee, Seung-Rae; Kang, Sinhang; Lee, Deuk-hwan; Nedumpallile Vasu, Nikhil

2017-04-01

Rainfall-induced landslide has been one of the major disasters in Korea since the beginning of 21st century when the global climate change started to give rise to the growth of the magnitude and frequency of extreme precipitation events. In order to mitigate the increasing damage to properties and loss of lives and to provide an effective tool for public officials to manage the landslide disasters, a real-time landslide early warning system with an advanced concept has been developed by taking into account for Busan, the second largest metropolitan city in Korea, as an operational test-bed. The system provides with warning information based on a five-level alert scheme (Normal, Attention, Watch, Alert, and Emergency) using the forecasted/observed rainfall data or the data obtained from ground monitoring (volumetric water content and matric suction). The alert levels are determined by applying seven different thresholds in a step-wise manner following a decision tree. In the pursuit of improved reliability of an early warning level assigned to a specific area, the system makes assessments repetitively using the thresholds of different theoretical backgrounds including statistical(empirical), physically-based, and mathematical analyses as well as direct measurement-based approaches. By mapping the distribution of the five early warning levels determined independently for each of tens of millions grids covering the entire mountainous area of Busan, the regional-scale system can also provide with the early warning information for a specific local area. The fact that the highest warning level is determined by using a concept of a numerically-modelled potential debris-flow risk is another distinctive feature of the system. This study tested the system performance by applying it for four previous rainy seasons in order to validate the operational applicability. During the rainy seasons of 2009, 2011, and 2014, the number of landslides recorded throughout Busan's territory reached 156, 64, and 37, respectively. In 2016, only three landslides were recorded even though the city experienced a couple of heavy rainfall events during the rainy season. The system performance test results show good agreement with the observation results for the past rainfall events. It seems that the system can also provide with reliable warning information for the future rainfall events.

Studies on the effects of air pollution on limestone degradation in Great Britain

NASA Astrophysics Data System (ADS)

Webb, A. H.; Bawden, R. J.; Busby, A. K.; Hopkins, J. N.

The CEGB and the Cathedrals Advisory Commission for England formed a Joint Working Party in 1985 to promote a research programme aimed at improving the understanding of the relationships between stone decay, atmospheric pollution and other factors. The programme has included exposure of limestone samples at York Minster and eight other sites in England and Scotland selected to give a mix of urban, marine and rural locations. All of the sites have comprehensive air pollution and meteorological monitoring and measurement of rainfall chemistry. At two sites samples have been fumigated with controlled levels of sulphur dioxide. Over all sites, there was a significant trend to increased weight loss with increase in average sulphur dioxide concentration, but a negative trend with total nitrogen oxides and with nitrogen dioxide. For sample exposures longer than 200 days, the sulphur dioxide dependence at the inland Liphook fumigation site was about half that found near the coast at Littlehampton. There was no significant trend to increase weight loss with total rainfall amount for the complete data set, but the analysis was dominated by the very wet Scottish site, which experienced the lowest average concentrations of air pollutants. A theoretical model for the chemical dissolution of rainwashed limestone has been derived from consideration of the ion and mass balances between the incident rain water and run-off water. The model has been fitted to the measured loss rates from the stonework field trials. With the exception of the very wet Scottish site, the difference between the stone loss rate, calculated from the model, and the mean measured loss rate for any particular exposure was generally smaller than the variation between the triplicate samples. Variation in the dry deposition velocity between sites and exposure periods does not appear to have been a very significant factor, and no residual effect due to the concentrations of nitrogen oxides was found. The natural solubility of limestone in water was the dominant term in describing the stone loss, and neutralization of the rainfall acidity the least significant. The volume of the intercepted rainfall and the variation in the pH of the run-off water with rainfall intensity have been identified as the two most significant terms which require more precise quantification. The data from the inland fumigation site used in the model predict a stone loss due to sulphur dioxide in the air of less than 1 μm yr -1 surface recession per ppb SO 2.

Distribution and transport of water vapor in the UTLS over the Tibetan Plateau as inferred from the MLS satellite data and WRF model simulations

NASA Astrophysics Data System (ADS)

Jain, S.; Kar, S. C.

2016-12-01

Water vapor is an important minor constituent in the lower stratosphere as it influences the stratospheric chemistry and total radiation budget. The spatial distribution of water vapor mixing ratio (WVMR) obtained from Aura Microwave Limb Sounder (MLS) satellite at 100 hPa level shows prominent maxima over the Tibetan Plateau during August 2015. The Asian monsoon upper level anticyclone is also known to occur over this region during this period. The Indian Meteorological Department (IMD) and National Centre of Medium Range Weather Forecasting (NCMRWF) observed daily gridded rainfall data shows moderate to heavy rainfall over the Tibetan Plateau, suggesting active convection from 26 July to 10 August 2015. The atmospheric conditions are simulated over the Asian region for the 15-day period using the Weather Research Forecasting (WRF) model. The simulations are carried out using two nested domains with resolution of 12 km and 4 km. The initial and boundary conditions are taken from the NGFS (up-graded version of the NCEP GFS) data. The WRF WVMR profiles are observed to be comparatively moist than the MLS profiles in the UTLS region over the Tibetan Plateau. This may be due to the relatively higher temperatures (1-2 K) simulated in the WRF model near 100 hPa level. It is noted that the WRF model has a drying tendency at all the levels. The UTLS WVMR and temperatures show poor sensitivity to the convective schemes. The parent domain and the explicit convective scheme simulate almost same moisture over time in the inner domain. The cloud micro-physics is observed to play a rather important role in controlling the UTLS water vapor content. The WSM-6 convective scheme is observed to simulate the UTLS moisture comparatively well and therefore the processes associated with the formation of ice, snow and graupel formation may be of much more importance in controlling the UTLS WVMR in the WRF model. The 24 hr, 48 hr and 72 hr forecast averaged for the 15-day period shows that over the Tibetan Plateau, high WVMR in the UTLS is not centered within the anticyclone, contrary to what has been shown by earlier studies. Similar simulations are also being carried out using the Era-interim initial and boundary conditions to confirm the above findings.

Contribution of hydrological data to the understanding of the spatio-temporal dynamics of F-specific RNA bacteriophages in river water during rainfall-runoff events.

PubMed

Fauvel, Blandine; Cauchie, Henry-Michel; Gantzer, Christophe; Ogorzaly, Leslie

2016-05-01

Heavy rainfall events were previously reported to bring large amounts of microorganisms in surface water, including viruses. However, little information is available on the origin and transport of viral particles in water during such rain events. In this study, an integrative approach combining microbiological and hydrological measurements was investigated to appreciate the dynamics and origins of F-specific RNA bacteriophage fluxes during two distinct rainfall-runoff events. A high frequency sampling (automatic sampler) was set up to monitor the F-specific RNA bacteriophages fluxes at a fine temporal scale during the whole course of the rainfall-runoff events. A total of 276 rainfall-runoff samples were collected and analysed using both infectivity and RT-qPCR assays. The results highlight an increase of 2.5 log10 and 1.8 log10 of infectious F-specific RNA bacteriophage fluxes in parallel of an increase of the water flow levels for both events. Faecal pollution was characterised as being mainly from anthropic origin with a significant flux of phage particles belonging to the genogroup II. At the temporal scale, two successive distinct waves of phage pollution were established and identified through the hydrological measurements. The first arrival of phages in the water column was likely to be linked to the resuspension of riverbed sediments that was responsible for a high input of genogroup II. Surface runoff contributed further to the second input of phages, and more particularly of genogroup I. In addition, an important contribution of infectious phage particles has been highlighted. These findings imply the existence of a close relationship between the risk for human health and the viral contamination of flood water. Copyright © 2016 Luxembourg institute of Science and Technology. Published by Elsevier Ltd.. All rights reserved.

Salmonella enteritidis surveillance by egg immunology: impact of the sampling scheme on the release of contaminated table eggs.

PubMed

Klinkenberg, Don; Thomas, Ekelijn; Artavia, Francisco F Calvo; Bouma, Annemarie

2011-08-01

Design of surveillance programs to detect infections could benefit from more insight into sampling schemes. We address the effect of sampling schemes for Salmonella Enteritidis surveillance in laying hens. Based on experimental estimates for the transmission rate in flocks, and the characteristics of an egg immunological test, we have simulated outbreaks with various sampling schemes, and with the current boot swab program with a 15-week sampling interval. Declaring a flock infected based on a single positive egg was not possible because test specificity was too low. Thus, a threshold number of positive eggs was defined to declare a flock infected, and, for small sample sizes, eggs from previous samplings had to be included in a cumulative sample to guarantee a minimum flock level specificity. Effectiveness of surveillance was measured by the proportion of outbreaks detected, and by the number of contaminated table eggs brought on the market. The boot swab program detected 90% of the outbreaks, with 75% fewer contaminated eggs compared to no surveillance, whereas the baseline egg program (30 eggs each 15 weeks) detected 86%, with 73% fewer contaminated eggs. We conclude that a larger sample size results in more detected outbreaks, whereas a smaller sampling interval decreases the number of contaminated eggs. Decreasing sample size and interval simultaneously reduces the number of contaminated eggs, but not indefinitely: the advantage of more frequent sampling is counterbalanced by the cumulative sample including less recently laid eggs. Apparently, optimizing surveillance has its limits when test specificity is taken into account. © 2011 Society for Risk Analysis.

A Possible Explanation for the Z -R Parameter Inconsistency when Comparing Stratiform and Convective Rainfall

NASA Astrophysics Data System (ADS)

Lane, John; Kasparis, Takis; Michaelides, Silas

2016-04-01

The well-known Z -R power law Z = ARb uses two parameters, A and b, in order to relate rainfall rate R to measured weather radar reflectivity Z. A common method used by researchers is to compute Z and R from disdrometer data and then extract the A-bparameter pair from a log-linear line fit to a scatter plot of Z -R pairs. Even though it may seem far more truthful to extract the parameter pair from a fit of radar ZR versus gauge rainfall rate RG, the extreme difference in spatial and temporal sampling volumes between radar and rain gauge creates a slew of problems that can generally only be solved by using rain gauge arrays and long sampling averages. Disdrometer derived A - b parameters are easily obtained and can provide information for the study of stratiform versus convective rainfall. However, an inconsistency appears when comparing averaged A - b pairs from various researchers. Values of b range from 1.26 to 1.51 for both stratiform and convective events. Paradoxically the values of Afall into three groups: 150 to 200 for convective; 200 to 400 for stratiform; and 400 to 500 again for convective. This apparent inconsistency can be explained by computing the A - b pair using the gamma DSD coupled with a modified drop terminal velocity model, v(D) = αDβ - w, where w is a somewhat artificial constant vertical velocity of the air above the disdrometer. This model predicts three regions of A, corresponding to w < 0, w = 0, and w > 0, which approximately matches observed data.

Water resources of the Palau Islands

USGS Publications Warehouse

Van der Brug, Otto

1984-01-01

The Palau Islands are a group of 350 islands, ranging in size from a few hundred square feet to the 153-square-mile island of Babelthuap. Babelthuap is the second largest island in the Western Pacific and comprises more than 80 percent of the total land area of the Palau Islands. Most of the islands are uninhabited limestone ridges covered with dense vegetation. These islands have no freshwater resources and are not included in this report. The island of Koror with an area of 3.6 square miles is the administrative, commercial, and population center of Palau and has an annual average rainfall of 148 inches. Short-term rainfall records at other locations in the islands indicate little variation in annual rainfall throughout the Palau Islands. Runoff-to-rainfall ratios for streams on Babelthuap show that about 70 percent of the rain falling on the island runs off to the ocean. The uniformity of rainfall and basin characteristics is shown by the excellent correlation between mean annual rainfall on Koror and streamflow on Babelthuap and by the close correlations between discharge at gaging stations and partial-record sites. Surface water quality is generally very good as shown by 55 chemical analyses of water from 18 sources. The dissolved solids concentration of water samples did not exceed 66 milligrams per liter. This report summarizes in one volume hydrologic data collection in a 14-year period of study and provides interpretations of the data than can be used by planners and public works officials as a basis for making decisions on the development and management of the islands ' water resources.

Some Advances in Downscaling Probabilistic Climate Forecasts for Agricultural Decision Support

NASA Astrophysics Data System (ADS)

Han, E.; Ines, A.

2015-12-01

Seasonal climate forecasts, commonly provided in tercile-probabilities format (below-, near- and above-normal), need to be translated into more meaningful information for decision support of practitioners in agriculture. In this paper, we will present two new novel approaches to temporally downscale probabilistic seasonal climate forecasts: one non-parametric and another parametric method. First, the non-parametric downscaling approach called FResampler1 uses the concept of 'conditional block sampling' of weather data to create daily weather realizations of a tercile-based seasonal climate forecasts. FResampler1 randomly draws time series of daily weather parameters (e.g., rainfall, maximum and minimum temperature and solar radiation) from historical records, for the season of interest from years that belong to a certain rainfall tercile category (e.g., being below-, near- and above-normal). In this way, FResampler1 preserves the covariance between rainfall and other weather parameters as if conditionally sampling maximum and minimum temperature and solar radiation if that day is wet or dry. The second approach called predictWTD is a parametric method based on a conditional stochastic weather generator. The tercile-based seasonal climate forecast is converted into a theoretical forecast cumulative probability curve. Then the deviates for each percentile is converted into rainfall amount or frequency or intensity to downscale the 'full' distribution of probabilistic seasonal climate forecasts. Those seasonal deviates are then disaggregated on a monthly basis and used to constrain the downscaling of forecast realizations at different percentile values of the theoretical forecast curve. As well as the theoretical basis of the approaches we will discuss sensitivity analysis (length of data and size of samples) of them. In addition their potential applications for managing climate-related risks in agriculture will be shown through a couple of case studies based on actual seasonal climate forecasts for: rice cropping in the Philippines and maize cropping in India and Kenya.

Climate Change Effects on Stream and River Biological Indicators: A Preliminary Analysis (External Review Draft)

EPA Science Inventory

This draft report is a preliminary assessment that describes how biological indicators are likely to respond to climate change, how well current sampling schemes may detect climate-driven changes, and how likely it is that these sampling schemes will continue to detect impairment...

Corrections to the General (2,4) and (4,4) FDTD Schemes

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

Meierbachtol, Collin S.; Smith, William S.; Shao, Xuan-Min

The sampling weights associated with two general higher order FDTD schemes were derived by Smith, et al. and published in a IEEE Transactions on Antennas and Propagation article in 2012. Inconsistencies between governing equations and their resulting solutions were discovered within the article. In an effort to track down the root cause of these inconsistencies, the full three-dimensional, higher order FDTD dispersion relation was re-derived using Mathematica TM. During this process, two errors were identi ed in the article. Both errors are highlighted in this document. The corrected sampling weights are also provided. Finally, the original stability limits provided formore » both schemes are corrected, and presented in a more precise form. It is recommended any future implementations of the two general higher order schemes provided in the Smith, et al. 2012 article should instead use the sampling weights and stability conditions listed in this document.« less

Bias-correction and Spatial Disaggregation for Climate Change Impact Assessments at a basin scale

NASA Astrophysics Data System (ADS)

Nyunt, Cho; Koike, Toshio; Yamamoto, Akio; Nemoto, Toshihoro; Kitsuregawa, Masaru

2013-04-01

Basin-scale climate change impact studies mainly rely on general circulation models (GCMs) comprising the related emission scenarios. Realistic and reliable data from GCM is crucial for national scale or basin scale impact and vulnerability assessments to build safety society under climate change. However, GCM fail to simulate regional climate features due to the imprecise parameterization schemes in atmospheric physics and coarse resolution scale. This study describes how to exclude some unsatisfactory GCMs with respect to focused basin, how to minimize the biases of GCM precipitation through statistical bias correction and how to cover spatial disaggregation scheme, a kind of downscaling, within in a basin. GCMs rejection is based on the regional climate features of seasonal evolution as a bench mark and mainly depends on spatial correlation and root mean square error of precipitation and atmospheric variables over the target region. Global Precipitation Climatology Project (GPCP) and Japanese 25-uear Reanalysis Project (JRA-25) are specified as references in figuring spatial pattern and error of GCM. Statistical bias-correction scheme comprises improvements of three main flaws of GCM precipitation such as low intensity drizzled rain days with no dry day, underestimation of heavy rainfall and inter-annual variability of local climate. Biases of heavy rainfall are conducted by generalized Pareto distribution (GPD) fitting over a peak over threshold series. Frequency of rain day error is fixed by rank order statistics and seasonal variation problem is solved by using a gamma distribution fitting in each month against insi-tu stations vs. corresponding GCM grids. By implementing the proposed bias-correction technique to all insi-tu stations and their respective GCM grid, an easy and effective downscaling process for impact studies at the basin scale is accomplished. The proposed method have been examined its applicability to some of the basins in various climate regions all over the world. The biases are controlled very well by using this scheme in all applied basins. After that, bias-corrected and downscaled GCM precipitation are ready to use for simulating the Water and Energy Budget based Distributed Hydrological Model (WEB-DHM) to analyse the stream flow change or water availability of a target basin under the climate change in near future. Furthermore, it can be investigated any inter-disciplinary studies such as drought, flood, food, health and so on.In summary, an effective and comprehensive statistical bias-correction method was established to fulfil the generative applicability of GCM scale to basin scale without difficulty. This gap filling also promotes the sound decision of river management in the basin with more reliable information to build the resilience society.

Solar Variability Controls on Rainfall in the Last Millennia: Evidence from a Highly Resolved Stalagmite Record from DeSoto Caverns (USA)

NASA Astrophysics Data System (ADS)

Aharon, P.; Lambert, W.; Hellstrom, J.

2009-12-01

Moisture transport from the Gulf of Mexico (GOM) inland has a considerable influence on both regional and continental rainfall patterns. Recent episodes of drought in the Southeastern USA exposed the vulnerability of the regional infrastructure to climate changes and gave rise to inter-state “water wars”. In order to better understand the cause of these periodic droughts and their controlling climate factors we have initiated a study of stalagmites from the DeSoto Caverns (Alabama, USA) that intersect the moisture flow from GOM. Combination of unusually high growth rates (up to 2 mm/decade), prominent dark and light seasonal layers, pristine aragonite mineralogy, precise U/Th dates acquired from mg-size samples and tight sampling (n=195) afforded generation of biannual (δ18O and δ13C of exceptional clarity spanning the last 700 yrs. The stalagmite (DSSG1) top yields isotope values (δ18O=-5.5 per-mill VPDB; δ13C=-10.1 per-mill VPDB) that are in good agreement with the predicted equilibrium isotope values. The oxygen and carbon isotope records exhibit a number of alternating negative and positive phase changes of

FIELD-SCALE LEACHING OF ARSENIC, CHROMIUM AND COPPER FROM WEATHERED TREATED WOOD

PubMed Central

Hasan, A. Rasem; Hu, Ligang; Solo-Gabriele, Helena M.; Fieber, Lynne; Cai, Yong; Townsend, Timothy G.

2010-01-01

Earlier studies documented the loss of wood preservatives from new wood. The objective of this study was to evaluate losses from weathered treated wood under field conditions by collecting rainfall leachate from 5 different wood types, all with a surface area of 0.21 m2. Wood samples included weathered chromate copper arsenate (CCA) treated wood at low (2.7 kg/m3), medium (4.8 kg/m3) and high (35.4 kg/m3) retention levels, new alkaline copper quat (ACQ) treated wood (1.1 kg/m3 as CuO) and new untreated wood. Arsenic was found to leach at a higher rate (100 mg in 1 year for low retention) than chromium and copper (<40 mg) in all CCA treated wood samples. Copper leached at the highest rate from the ACQ sample (670 mg). Overall results suggest that metals’ leaching is a continuous process driven by rainfall, and that the mechanism of release from the wood matrix changes as wood weathers. PMID:20053493

Soil characteristics of semidesert soils along a precipitation gradient in the Negev (Israel)

NASA Astrophysics Data System (ADS)

Steckenmesser, Daniel; Drahorad, Sylvie; Felix-Henningsen, Peter

2010-05-01

The sand dunes of the north-western Negev desert (Israel) show a unique precipitation gradient on a short distance. This area is build up by the same parent material and suited to investigate the influence of changes in rainfall on soil characteristics in semi-desert ecosystems. The study site is the western extension of the Sinai sand field, the sand dunes are stabilised by biological soil crusts and perennial vegetation like Retama raetam. Along this precipitation gradient the three investigation areas Nizzana South (90mm ^a-), Nizzana 84 (130mm ^a-1) and Nizzana 69 (170mm ^a-1) are situated. At every study site two soil profiles were investigated, each under the legume Retama raetam and in the bare interspace covered by biological soil crusts. The soil samples were taken at the interdune positions at every study site. The soil sampling included the biological soil crust, the topsoil and the subsoil up to 1,5 m. The narrow sampling of 20cm wide steps allow a mapping of the distribution of nutrients, carbonates and soluble salts of in order to show the impact of perennial plants and rainfall on soil properties. Soluble salts and nutrients were measured in a 1:5 water extraction, calcium carbonate was determined according to Scheibler. The data shows a strong influence of perennial shrubs on the deposition of dust and the redistribution of nutrients compared to the bare interspace. The distribution of highly and less soluble salts below the perennial shrub proofs a shallower water infiltration than in the comparable interspace area. The interspace between the plants is covered by a biological soil crust, which also strongly influences the matter fluxes by nutrient-fixation, creation of runoff and stabilization of the soil surface. These biological soil crusts show higher amounts of elements than the subsoils. The comparison of the three areas along the rainfall gradient shows higher inputs of soluble salts with increasing precipitation due to wet deposition, while carbonate contents are negatively correlated with decreasing precipitation. This is related to a higher dust input in the southern study site, which was generated in the lime stone Negev. Higher amounts of rainfall introduce higher element leaching. Perennial plants cover the surface and reduce infiltration. Inputs into the soils through dust have to be evaluated for every location to separate between effects of deposition and rainfall.

Impact of animal waste application on runoff water quality in field experimental plots.

PubMed

Hill, Dagne D; Owens, William E; Tchoounwou, Paul B

2005-08-01

Animal waste from dairy and poultry operations is an economical and commonly used fertilizer in the state of Louisiana. The application of animal waste to pasture lands not only is a source of fertilizer, but also allows for a convenient method of waste disposal. The disposal of animal wastes on land is a potential nonpoint source of water degradation. Water degradation and human health is a major concern when considering the disposal of large quantities of animal waste. The objective of this research was to determine the effect of animal waste application on biological (fecal coliform, Enterobacter spp. and Escherichia coli) and physical/chemical (temperature, pH, nitrate nitrogen, ammonia nitrogen, phosphate, copper, zinc, and sulfate) characteristics of runoff water in experimental plots. The effects of the application of animal waste have been evaluated by utilizing experimental plots and simulated rainfall events. Samples of runoff water were collected and analyzed for fecal coliforms. Fecal coliforms isolated from these samples were identified to the species level. Chemical analysis was performed following standard test protocols. An analysis of temperature, ammonia nitrogen, nitrate nitrogen, iron, copper, phosphate, potassium, sulfate, zinc and bacterial levels was performed following standard test protocols as presented in Standard Methods for the Examination of Water and Wastewater [1]. In the experimental plots, less time was required in the tilled broiler litter plots for the measured chemicals to decrease below the initial pre-treatment levels. A decrease of over 50% was noted between the first and second rainfall events for sulfate levels. This decrease was seen after only four simulated rainfall events in tilled broiler litter plots whereas broiler litter plots required eight simulated rainfall events to show this same type of reduction. A reverse trend was seen in the broiler litter plots and the tilled broiler plots for potassium. Bacteria numbers present after the simulated rainfall events were above 200/100 ml of sample water. It can be concluded that: 1) non-point source pollution has a significant effect on bacterial and nutrients levels in runoff water and in water resources; 2) land application of animal waste for soil fertilization makes a significant contribution to water pollution; 3) the use of tilling can significantly reduce the amount of nutrients available in runoff water.

Impact of Animal Waste Application on Runoff Water Quality in Field Experimental Plots

PubMed Central

Hill, Dagne D.; Owens, William E.; Tchounwou, Paul B.

2005-01-01

Animal waste from dairy and poultry operations is an economical and commonly used fertilizer in the state of Louisiana. The application of animal waste to pasture lands not only is a source of fertilizer, but also allows for a convenient method of waste disposal. The disposal of animal wastes on land is a potential nonpoint source of water degradation. Water degradation and human health is a major concern when considering the disposal of large quantities of animal waste. The objective of this research was to determine the effect of animal waste application on biological (fecal coliform, Enterobacter spp. and Escherichia coli) and physical/chemical (temperature, pH, nitrate nitrogen, ammonia nitrogen, phosphate, copper, zinc, and sulfate) characteristics of runoff water in experimental plots. The effects of the application of animal waste have been evaluated by utilizing experimental plots and simulated rainfall events. Samples of runoff water were collected and analyzed for fecal coliforms. Fecal coliforms isolated from these samples were identified to the species level. Chemical analysis was performed following standard test protocols. An analysis of temperature, ammonia nitrogen, nitrate nitrogen, iron, copper, phosphate, potassium, sulfate, zinc and bacterial levels was performed following standard test protocols as presented in Standard Methods for the Examination of Water and Wastewater [1]. In the experimental plots, less time was required in the tilled broiler litter plots for the measured chemicals to decrease below the initial pre-treatment levels. A decrease of over 50% was noted between the first and second rainfall events for sulfate levels. This decrease was seen after only four simulated rainfall events in tilled broiler litter plots whereas broiler litter plots required eight simulated rainfall events to show this same type of reduction. A reverse trend was seen in the broiler litter plots and the tilled broiler plots for potassium. Bacteria numbers present after the simulated rainfall events were above 200/100 ml of sample water. It can be concluded that: 1) non-point source pollution has a significant effect on bacterial and nutrients levels in runoff water and in water resources; 2) land application of animal waste for soil fertilization makes a significant contribution to water pollution; 3) the use of tilling can significantly reduce the amount of nutrients available in runoff water. PMID:16705834

Sampling for area estimation: A comparison of full-frame sampling with the sample segment approach. [Kansas

NASA Technical Reports Server (NTRS)

Hixson, M. M.; Bauer, M. E.; Davis, B. J.

1979-01-01

The effect of sampling on the accuracy (precision and bias) of crop area estimates made from classifications of LANDSAT MSS data was investigated. Full-frame classifications of wheat and non-wheat for eighty counties in Kansas were repetitively sampled to simulate alternative sampling plants. Four sampling schemes involving different numbers of samples and different size sampling units were evaluated. The precision of the wheat area estimates increased as the segment size decreased and the number of segments was increased. Although the average bias associated with the various sampling schemes was not significantly different, the maximum absolute bias was directly related to sampling unit size.

Monitoring forest areas from continental to territorial levels using a sample of medium spatial resolution satellite imagery

NASA Astrophysics Data System (ADS)

Eva, Hugh; Carboni, Silvia; Achard, Frédéric; Stach, Nicolas; Durieux, Laurent; Faure, Jean-François; Mollicone, Danilo

A global systematic sampling scheme has been developed by the UN FAO and the EC TREES project to estimate rates of deforestation at global or continental levels at intervals of 5 to 10 years. This global scheme can be intensified to produce results at the national level. In this paper, using surrogate observations, we compare the deforestation estimates derived from these two levels of sampling intensities (one, the global, for the Brazilian Amazon the other, national, for French Guiana) to estimates derived from the official inventories. We also report the precisions that are achieved due to sampling errors and, in the case of French Guiana, compare such precision with the official inventory precision. We extract nine sample data sets from the official wall-to-wall deforestation map derived from satellite interpretations produced for the Brazilian Amazon for the year 2002 to 2003. This global sampling scheme estimate gives 2.81 million ha of deforestation (mean from nine simulated replicates) with a standard error of 0.10 million ha. This compares with the full population estimate from the wall-to-wall interpretations of 2.73 million ha deforested, which is within one standard error of our sampling test estimate. The relative difference between the mean estimate from sampling approach and the full population estimate is 3.1%, and the standard error represents 4.0% of the full population estimate. This global sampling is then intensified to a territorial level with a case study over French Guiana to estimate deforestation between the years 1990 and 2006. For the historical reference period, 1990, Landsat-5 Thematic Mapper data were used. A coverage of SPOT-HRV imagery at 20 m × 20 m resolution acquired at the Cayenne receiving station in French Guiana was used for year 2006. Our estimates from the intensified global sampling scheme over French Guiana are compared with those produced by the national authority to report on deforestation rates under the Kyoto protocol rules for its overseas department. The latter estimates come from a sample of nearly 17,000 plots analyzed from same spatial imagery acquired between year 1990 and year 2006. This sampling scheme is derived from the traditional forest inventory methods carried out by IFN (Inventaire Forestier National). Our intensified global sampling scheme leads to an estimate of 96,650 ha deforested between 1990 and 2006, which is within the 95% confidence interval of the IFN sampling scheme, which gives an estimate of 91,722 ha, representing a relative difference from the IFN of 5.4%. These results demonstrate that the intensification of the global sampling scheme can provide forest area change estimates close to those achieved by official forest inventories (<6%), with precisions of between 4% and 7%, although we only estimate errors from sampling, not from the use of surrogate data. Such methods could be used by developing countries to demonstrate that they are fulfilling requirements for reducing emissions from deforestation in the framework of an REDD (Reducing Emissions from Deforestation in Developing Countries) mechanism under discussion within the United Nations Framework Convention on Climate Change (UNFCCC). Monitoring systems at national levels in tropical countries can also benefit from pan-tropical and regional observations, to ensure consistency between different national monitoring systems.

Influence of Environmental Factors and Human Activity on the Presence of Salmonella Serovars in a Marine Environment

PubMed Central

Martinez-Urtaza, Jaime; Saco, Montserrat; de Novoa, Jacobo; Perez-Piñeiro, Pelayo; Peiteado, Jesus; Lozano-Leon, Antonio; Garcia-Martin, Oscar

2004-01-01

The temporal and spatial distribution of Salmonella contamination in the coastal waters of Galicia (northwestern Spain) relative to contamination events with different environmental factors (temperature, wind, hours of sunlight, rainfall, and river flow) were investigated over a 4-year period. Salmonellae were isolated from 127 of 5,384 samples of molluscs and seawater (2.4%), and no significant differences (P < 0.05) between isolates obtained in different years were observed. The incidence of salmonellae was significantly higher in water column samples (2.9%) than in those taken from the marine benthos (0.7%). Of the 127 strains of Salmonella isolated, 20 different serovars were identified. Salmonella enterica serovar Senftenberg was the predominant serovar, being represented by 54 isolates (42.5%), followed by serovar Typhimurium (19 isolates [15%]) and serovar Agona (12 isolates [9.4%]). Serovar Senftenberg was detected at specific points on the coast and could not be related to any of the environmental parameters analyzed. All serovars except Salmonella serovar Senftenberg were found principally in the southern coastal areas close to the mouths of rivers, and their incidence was associated with high southwestern wind and rainfall. Using multiple logistic regression analysis models, the prevalence of salmonellae was best explained by environmental parameters on the day prior to sampling. Understanding this relationship may be useful for the control of molluscan shellfish harvests, with wind and rainfall serving as triggers for closure. PMID:15066800

Characteristics of the event mean concentration (EMC) from rainfall runoff on an urban highway.

PubMed

Lee, Ju Young; Kim, Hyoungjun; Kim, Youngjin; Han, Moo Young

2011-04-01

The purpose of this study was to investigate the characterization of the event mean concentration (EMC) of runoff during heavy precipitation events on highways. Highway runoff quality data were collected from the 7th highway, in South Korea during 2007-2009. The samples were analyzed for runoff quantity and quality parameters such as COD(cr), TSS, TPHs, TKN, NO₃, TP, PO₄ and six heavy metals, e.g., As, Cu, Cd, Ni, Pb and Zn. Analysis of resulting hydrographs and pollutant graphs indicates that the peak of the pollutant concentrations in runoff occurs 20 min after the first rainfall runoff occurrence. The first flush effect depends on the preceding dry period and the rainfall intensity. The results of this study can be used as a reference for water quality management of urban highways. Crown Copyright © 2010. Published by Elsevier Ltd. All rights reserved.

Exploring Sampling in the Detection of Multicategory EEG Signals

PubMed Central

Siuly, Siuly; Kabir, Enamul; Wang, Hua; Zhang, Yanchun

2015-01-01

The paper presents a structure based on samplings and machine leaning techniques for the detection of multicategory EEG signals where random sampling (RS) and optimal allocation sampling (OS) are explored. In the proposed framework, before using the RS and OS scheme, the entire EEG signals of each class are partitioned into several groups based on a particular time period. The RS and OS schemes are used in order to have representative observations from each group of each category of EEG data. Then all of the selected samples by the RS from the groups of each category are combined in a one set named RS set. In the similar way, for the OS scheme, an OS set is obtained. Then eleven statistical features are extracted from the RS and OS set, separately. Finally this study employs three well-known classifiers: k-nearest neighbor (k-NN), multinomial logistic regression with a ridge estimator (MLR), and support vector machine (SVM) to evaluate the performance for the RS and OS feature set. The experimental outcomes demonstrate that the RS scheme well represents the EEG signals and the k-NN with the RS is the optimum choice for detection of multicategory EEG signals. PMID:25977705

Efficient Simulation of Tropical Cyclone Pathways with Stochastic Perturbations

NASA Astrophysics Data System (ADS)

Webber, R.; Plotkin, D. A.; Abbot, D. S.; Weare, J.

2017-12-01

Global Climate Models (GCMs) are known to statistically underpredict intense tropical cyclones (TCs) because they fail to capture the rapid intensification and high wind speeds characteristic of the most destructive TCs. Stochastic parametrization schemes have the potential to improve the accuracy of GCMs. However, current analysis of these schemes through direct sampling is limited by the computational expense of simulating a rare weather event at fine spatial gridding. The present work introduces a stochastically perturbed parametrization tendency (SPPT) scheme to increase simulated intensity of TCs. We adapt the Weighted Ensemble algorithm to simulate the distribution of TCs at a fraction of the computational effort required in direct sampling. We illustrate the efficiency of the SPPT scheme by comparing simulations at different spatial resolutions and stochastic parameter regimes. Stochastic parametrization and rare event sampling strategies have great potential to improve TC prediction and aid understanding of tropical cyclogenesis. Since rising sea surface temperatures are postulated to increase the intensity of TCs, these strategies can also improve predictions about climate change-related weather patterns. The rare event sampling strategies used in the current work are not only a novel tool for studying TCs, but they may also be applied to sampling any range of extreme weather events.

Screening of sustainable groundwater sources for integration into a regional drought-prone water supply system

NASA Astrophysics Data System (ADS)

Stigter, T. Y.; Monteiro, J. P.; Nunes, L. M.; Vieira, J.; Cunha, M. C.; Ribeiro, L.; Nascimento, J.; Lucas, H.

2009-01-01

This paper reports on the qualitative and quantitative screening of groundwater sources for integration into the public water supply system of the Algarve, Portugal. The results are employed in a decision support system currently under development for an integrated water resources management scheme in the region. Such a scheme is crucial for several reasons, including the extreme seasonal and annual variations in rainfall, the effect of climate change on more frequent and long-lasting droughts, the continuously increasing water demand and the high risk of a single-source water supply policy. The latter was revealed during the severe drought of 2004 and 2005, when surface reservoirs were depleted and the regional water demand could not be met, despite the drilling of emergency wells. For screening and selection, quantitative criteria are based on aquifer properties and well yields, whereas qualitative criteria are defined by water quality indices. These reflect the well's degree of violation of drinking water standards for different sets of variables, including toxicity parameters, nitrate and chloride, iron and manganese and microbiological parameters. Results indicate the current availability of at least 1100 l s-1 of high quality groundwater (55% of the regional demand), requiring only disinfection (900 l s-1) or basic treatment, prior to human consumption. These groundwater withdrawals are sustainable when compared to mean annual recharge, considering that at least 40% is preserved for ecological demands. A more accurate and comprehensive analysis of sustainability is performed with the help of steady-state and transient groundwater flow simulations, which account for aquifer geometry, boundary conditions, recharge and discharge rates, pumping activity and seasonality. They permit an advanced analysis of present and future scenarios and show that increasing water demands and decreasing rainfall will make the water supply system extremely vulnerable, with a high risk of groundwater salinization and ecosystem degradation.

Screening of sustainable groundwater sources for integration into a regional drought-prone water supply system

NASA Astrophysics Data System (ADS)

Stigter, T. Y.; Monteiro, J. P.; Nunes, L. M.; Vieira, J.; Cunha, M. C.; Ribeiro, L.; Nascimento, J.; Lucas, H.

2009-07-01

This paper reports on the qualitative and quantitative screening of groundwater sources for integration into the public water supply system of the Algarve, Portugal. The results are employed in a decision support system currently under development for an integrated water resources management scheme in the region. Such a scheme is crucial for several reasons, including the extreme seasonal and annual variations in rainfall, the effect of climate change on more frequent and long-lasting droughts, the continuously increasing water demand and the high risk of a single-source water supply policy. The latter was revealed during the severe drought of 2004 and 2005, when surface reservoirs were depleted and the regional water demand could not be met, despite the drilling of emergency wells. For screening and selection, quantitative criteria are based on aquifer properties and well yields, whereas qualitative criteria are defined by water quality indices. These reflect the well's degree of violation of drinking water standards for different sets of variables, including toxicity parameters, nitrate and chloride, iron and manganese and microbiological parameters. Results indicate the current availability of at least 1100 l s-1 of high quality groundwater (55% of the regional demand), requiring only disinfection (900 l s-1) or basic treatment, prior to human consumption. These groundwater withdrawals are sustainable when compared to mean annual recharge, considering that at least 40% is preserved for ecological demands. A more accurate and comprehensive analysis of sustainability is performed with the help of steady-state and transient groundwater flow simulations, which account for aquifer geometry, boundary conditions, recharge and discharge rates, pumping activity and seasonality. They permit an advanced analysis of present and future scenarios and show that increasing water demands and decreasing rainfall will make the water supply system extremely vulnerable, with a high risk of groundwater salinization and ecosystem degradation.

Identifying the optimal spatially and temporally invariant root distribution for a semiarid environment

NASA Astrophysics Data System (ADS)

Sivandran, Gajan; Bras, Rafael L.

2012-12-01

In semiarid regions, the rooting strategies employed by vegetation can be critical to its survival. Arid regions are characterized by high variability in the arrival of rainfall, and species found in these areas have adapted mechanisms to ensure the capture of this scarce resource. Vegetation roots have strong control over this partitioning, and assuming a static root profile, predetermine the manner in which this partitioning is undertaken.A coupled, dynamic vegetation and hydrologic model, tRIBS + VEGGIE, was used to explore the role of vertical root distribution on hydrologic fluxes. Point-scale simulations were carried out using two spatially and temporally invariant rooting schemes: uniform: a one-parameter model and logistic: a two-parameter model. The simulations were forced with a stochastic climate generator calibrated to weather stations and rain gauges in the semiarid Walnut Gulch Experimental Watershed (WGEW) in Arizona. A series of simulations were undertaken exploring the parameter space of both rooting schemes and the optimal root distribution for the simulation, which was defined as the root distribution with the maximum mean transpiration over a 100-yr period, and this was identified. This optimal root profile was determined for five generic soil textures and two plant-functional types (PFTs) to illustrate the role of soil texture on the partitioning of moisture at the land surface. The simulation results illustrate the strong control soil texture has on the partitioning of rainfall and consequently the depth of the optimal rooting profile. High-conductivity soils resulted in the deepest optimal rooting profile with land surface moisture fluxes dominated by transpiration. As we move toward the lower conductivity end of the soil spectrum, a shallowing of the optimal rooting profile is observed and evaporation gradually becomes the dominate flux from the land surface. This study offers a methodology through which local plant, soil, and climate can be accounted for in the parameterization of rooting profiles in semiarid regions.

Influence of spatial resolution on precipitation simulations for the central Andes Mountains

NASA Astrophysics Data System (ADS)

Trachte, Katja; Bendix, Jörg

2013-04-01

The climate of South America is highly influenced by the north-south oriented Andes Mountains. Their complex structure causes modifications of large-scale atmospheric circulations resulting in various mesoscale phenomena as well as a high variability in the local conditions. Due to their height and length the terrain generates distinctly climate conditions between the western and the eastern slopes. While in the tropical regions along the western flanks the conditions are cold and arid, the eastern slopes are dominated by warm-moist and rainy air coming from the Amazon basin. Below 35° S the situation reverses with rather semiarid conditions in the eastern part and temperate rainy climate along southern Chile. Generally, global circulation models (GCMs) describe the state of the global climate and its changes, but are disabled to capture regional or even local features due to their coarse resolution. This is particularly true in heterogeneous regions such as the Andes Mountains, where local driving features, e. g. local circulation systems, highly varies on small scales and thus, lead to a high variability of rainfall distributions. An appropriate technique to overcome this problem and to gain regional and local scale rainfall information is the dynamical downscaling of the global data using a regional climate model (RCM). The poster presents results of the evaluation of the performance of the Weather Research and Forecasting (WRF) model over South America with special focus on the central Andes Mountains of Ecuador. A sensitivity study regarding the cumulus parametrization, microphysics, boundary layer processes and the radiation budget is conducted. With 17 simulations consisting of 16 parametrization scheme combinations and 1 default run a suitable model set-up for climate research in this region is supposed to be evaluated. The simulations were conducted in a two-way nested mode i) to examine the best physics scheme combination for the target and ii) to analyze the impact of spatial resolution and thus, the representation of the terrain on the result.

Ancestral inference from haplotypes and mutations.

PubMed

Griffiths, Robert C; Tavaré, Simon

2018-04-25

We consider inference about the history of a sample of DNA sequences, conditional upon the haplotype counts and the number of segregating sites observed at the present time. After deriving some theoretical results in the coalescent setting, we implement rejection sampling and importance sampling schemes to perform the inference. The importance sampling scheme addresses an extension of the Ewens Sampling Formula for a configuration of haplotypes and the number of segregating sites in the sample. The implementations include both constant and variable population size models. The methods are illustrated by two human Y chromosome datasets. Copyright © 2018. Published by Elsevier Inc.

Future projections of synoptic weather types over the Arabian Peninsula during the twenty-first century using an ensemble of CMIP5 models

NASA Astrophysics Data System (ADS)

El Kenawy, Ahmed M.; McCabe, Matthew F.

2017-10-01

An assessment of future change in synoptic conditions over the Arabian Peninsula throughout the twenty-first century was performed using 20 climate models from the Coupled Model Intercomparison Project Phase 5 (CMIP5) database. We employed the mean sea level pressure (SLP) data from model output together with NCEP/NCAR reanalysis data and compared the relevant circulation types produced by the Lamb classification scheme for the base period 1975-2000. Overall, model results illustrated good agreement with the reanalysis, albeit with a tendency to underestimate cyclonic (C) and southeasterly (SE) patterns and to overestimate anticyclones and directional flows. We also investigated future projections for each circulation-type during the rainy season (December-May) using three Representative Concentration Pathways (RCPs), comprising RCP2.6, RCP4.5, and RCP8.5. Overall, two scenarios (RCP4.5 and RCP 8.5) revealed a statistically significant increase in weather types favoring above normal rainfall in the region (e.g., C and E-types). In contrast, weather types associated with lower amounts of rainfall (e.g., anticyclones) are projected to decrease in winter but increase in spring. For all scenarios, there was consistent agreement on the sign of change (i.e., positive/negative) for the most frequent patterns (e.g., C, SE, E and A-types), whereas the sign was uncertain for less recurrent types (e.g., N, NW, SE, and W). The projected changes in weather type frequencies in the region can be viewed not only as indicators of change in rainfall response but may also be used to inform impact studies pertinent to water resource planning and management, extreme weather analysis, and agricultural production.