Shallow and Deep Latent Heating Modes Over Tropical Oceans Observed with TRMM PR Spectral Latent Heating Data

NASA Technical Reports Server (NTRS)

Takayabu, Yukari N.; Shige, Shoichi; Tao, Wei-Kuo; Hirota, Nagio

2010-01-01

The global hydrological cycle is central to the Earth's climate system, with rainfall and the physics of its formation acting as the key links in the cycle. Two-thirds of global rainfall occurs in the Tropics. Associated with this rainfall is a vast amount of heat, which is known as latent heat. It arises mainly due to the phase change of water vapor condensing into liquid droplets; three-fourths of the total heat energy available to the Earth's atmosphere comes from tropical rainfall. In addition, fresh water provided by tropical rainfall and its variability exerts a large impact upon the structure and motions of the upper ocean layer. Three-dimensional distributions of latent heating estimated from Tropical Rainfall Measuring Mission Precipitation Radar (TRMM PR)utilizing the Spectral Latent Heating (SLH) algorithm are analyzed. Mass-weighted and vertically integrated latent heating averaged over the tropical oceans is estimated as approx.72.6 J/s (approx.2.51 mm/day), and that over tropical land is approx.73.7 J/s (approx.2.55 mm/day), for 30degN-30degS. It is shown that non-drizzle precipitation over tropical and subtropical oceans consists of two dominant modes of rainfall systems, deep systems and congestus. A rough estimate of shallow mode contribution against the total heating is about 46.7 % for the average tropical oceans, which is substantially larger than 23.7 % over tropical land. While cumulus congestus heating linearly correlates with the SST, deep mode is dynamically bounded by large-scale subsidence. It is notable that substantial amount of rain, as large as 2.38 mm day-1 in average, is brought from congestus clouds under the large-scale subsiding circulation. It is also notable that even in the region with SST warmer than 28 oC, large-scale subsidence effectively suppresses the deep convection, remaining the heating by congestus clouds. Our results support that the entrainment of mid-to-lower-tropospheric dry air, which accompanies the large-scale subsidence is the major factor suppressing the deep convection. Therefore, representation of the realistic entrainment is very important for proper reproduction of precipitation distribution and resultant large-scale circulation.

Origins and interrelationship of Intraseasonal rainfall variations around the Maritime Continent during boreal winter

NASA Astrophysics Data System (ADS)

Cao, Xi; Wu, Renguang

2018-04-01

Large intraseasonal rainfall variations are identified over the southern South China Sea (SSCS), tropical southeastern Indian Ocean (SEIO), and east coast of the Philippines (EPHI) in boreal winter. The present study contrasts origins and propagations and investigates interrelations of intraseasonal rainfall variations on the 10-20- and 30-60-day time scales in these regions. Different origins are identified for intraseasonal rainfall anomalies over the SSCS, SEIO, and EPHI on both time scales. On the 10-20-day time scale, strong northerly or northeasterly wind anomalies related to the East Asian winter monsoon (EAWM) play a major role in intraseasonal rainfall variations over the SSCS and EPHI. On the 30-60-day time scale, both the intraseasonal signal from the tropical Indian Ocean and the EAWM-related wind anomalies contribute to intraseasonal rainfall variations over the SSCS, whereas the EAWM-related wind anomalies have a major contribution to the intraseasonal rainfall variations over the EPHI. No relation is detected between the intraseasonal rainfall variations over the SEIO and the EAWM on both the 10-20-day and 30-60-day time scales. The anomalies associated with intraseasonal rainfall variations over the SSCS and EPHI propagate northwestward and northeastward, respectively, on the 10-20- and 30-60-day time scales. The intraseasonal rainfall anomalies display northwestward and northward propagation over the Bay of Bengal, respectively, on the 10-20- and 30-60-day time scales.

Evaluation of different rainfall products over India for the summer monsoon

NASA Astrophysics Data System (ADS)

Prakash, Satya; Mitra, Ashis; Turner, Andrew; Collins, Mathew; AchutoRao, Krishna

2015-04-01

Summer rainfall over India forms an integral part of the Asian monsoon, which plays a key role in the global water cycle and climate system through coupled atmospheric and oceanic processes. Accurate prediction of Indian summer monsoon rainfall and its variability at various spatiotemporal scales are crucial for agriculture, water resources and hydroelectric-power sectors. Reliable rainfall observations are very important for verification of numerical model outputs and model development. However, high spatiotemporal variability of rainfall makes it difficult to measure adequately with ground-based instruments over a large region of various surface types from deserts to oceans. A number of multi-satellite rainfall products are available to users at different spatial and temporal scales. Each rainfall product has some advantages as well as limitations, hence it is essential to find a suitable region-specific data set among these rainfall products for a particular user application, such as water resources, agricultural modelling etc. In this study, we examine seasonal-mean and daily rainfall datasets for monsoon model validation. First, six multi-satellite and gauge-only rainfall products were evaluated over India at seasonal scale for 27 (JJAS 1979-2005) summer monsoon seasons against gridded 0.5-degree IMD gauge-based rainfall. Various skill metrics are computed to assess the potential of these data sets in representation of large-scale monsoon rainfall at all-India and sub-regional scales. Among the gauge-only data sets, APHRODITE and GPCC appear to outperform the others whereas GPCP is better than CMAP in the merged multi-satellite category. However, there are significant differences among these data sets indicating uncertainty in the observed rainfall over this region, with important implications for the evaluation of model simulations. At the daily scale, TRMM TMPA-3B42 is one of the best available products and is widely used for various hydro-meteorological applications. The existing version 6 (V6) products of TRMM underwent major changes and version 7 (V7) products were released in late 2012, and we compare these to the IMD daily gridded data over the 1998-2010 period. We show a clear improvement in V7 over V6 in the South Asian monsoon region using various skill metrics. Over typical monsoon rainfall zones, biases are improved by 5-10% in V7 over higher-rainfall regions. These results will help users to select appropriate rainfall product for their application. With the recent launch of the GPM Core Observatory, the release of a more advanced high-resolution multi-satellite rainfall product is expected soon.

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

NASA Astrophysics Data System (ADS)

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

2011-12-01

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

How spatial and temporal rainfall variability affect runoff across basin scales: insights from field observations in the (semi-)urbanised Charlotte watershed

NASA Astrophysics Data System (ADS)

Ten Veldhuis, M. C.; Smith, J. A.; Zhou, Z.

2017-12-01

Impacts of rainfall variability on runoff response are highly scale-dependent. Sensitivity analyses based on hydrological model simulations have shown that impacts are likely to depend on combinations of storm type, basin versus storm scale, temporal versus spatial rainfall variability. So far, few of these conclusions have been confirmed on observational grounds, since high quality datasets of spatially variable rainfall and runoff over prolonged periods are rare. Here we investigate relationships between rainfall variability and runoff response based on 30 years of radar-rainfall datasets and flow measurements for 16 hydrological basins ranging from 7 to 111 km2. Basins vary not only in scale, but also in their degree of urbanisation. We investigated temporal and spatial variability characteristics of rainfall fields across a range of spatial and temporal scales to identify main drivers for variability in runoff response. We identified 3 ranges of basin size with different temporal versus spatial rainfall variability characteristics. Total rainfall volume proved to be the dominant agent determining runoff response at all basin scales, independent of their degree of urbanisation. Peak rainfall intensity and storm core volume are of secondary importance. This applies to all runoff parameters, including runoff volume, runoff peak, volume-to-peak and lag time. Position and movement of the storm with respect to the basin have a negligible influence on runoff response, with the exception of lag times in some of the larger basins. This highlights the importance of accuracy in rainfall estimation: getting the position right but the volume wrong will inevitably lead to large errors in runoff prediction. Our study helps to identify conditions where rainfall variability matters for correct estimation of the rainfall volume as well as the associated runoff response.

Is the negative IOD during 2016 the reason for monsoon failure over southwest peninsular India?

NASA Astrophysics Data System (ADS)

Sreelekha, P. N.; Babu, C. A.

2018-01-01

The study investigates the mechanism responsible for the deficit rainfall over southwest peninsular India during the 2016 monsoon season. Analysis shows that the large-scale variation in circulation pattern due to the strong, negative Indian Ocean Dipole phenomenon was the reason for the deficit rainfall. Significant reduction in the number of northward-propagating monsoon-organized convections together with fast propagation over the southwest peninsular India resulted in reduction in rainfall. On the other hand, their persistence for longer time over the central part of India resulted in normal rainfall. It was found that the strong convection over the eastern equatorial Indian Ocean creates strong convergence over that region. The combined effect of the sinking due to the well-developed Walker circulation originated over the eastern equatorial Indian Ocean and the descending limb of the monsoon Hadley cell caused strong subsidence over the western equatorial Indian Ocean. The tail of this large-scale sinking extended up to the southern parts of India. This hinders formation of monsoon-organized convections leading to a large deficiency of rainfall during monsoon 2016 over the southwest peninsular India.

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.

A Monte-Carlo Bayesian framework for urban rainfall error modelling

NASA Astrophysics Data System (ADS)

Ochoa Rodriguez, Susana; Wang, Li-Pen; Willems, Patrick; Onof, Christian

2016-04-01

Rainfall estimates of the highest possible accuracy and resolution are required for urban hydrological applications, given the small size and fast response which characterise urban catchments. While significant progress has been made in recent years towards meeting rainfall input requirements for urban hydrology -including increasing use of high spatial resolution radar rainfall estimates in combination with point rain gauge records- rainfall estimates will never be perfect and the true rainfall field is, by definition, unknown [1]. Quantifying the residual errors in rainfall estimates is crucial in order to understand their reliability, as well as the impact that their uncertainty may have in subsequent runoff estimates. The quantification of errors in rainfall estimates has been an active topic of research for decades. However, existing rainfall error models have several shortcomings, including the fact that they are limited to describing errors associated to a single data source (i.e. errors associated to rain gauge measurements or radar QPEs alone) and to a single representative error source (e.g. radar-rain gauge differences, spatial temporal resolution). Moreover, rainfall error models have been mostly developed for and tested at large scales. Studies at urban scales are mostly limited to analyses of propagation of errors in rain gauge records-only through urban drainage models and to tests of model sensitivity to uncertainty arising from unmeasured rainfall variability. Only few radar rainfall error models -originally developed for large scales- have been tested at urban scales [2] and have been shown to fail to well capture small-scale storm dynamics, including storm peaks, which are of utmost important for urban runoff simulations. In this work a Monte-Carlo Bayesian framework for rainfall error modelling at urban scales is introduced, which explicitly accounts for relevant errors (arising from insufficient accuracy and/or resolution) in multiple data sources (in this case radar and rain gauge estimates typically available at present), while at the same time enabling dynamic combination of these data sources (thus not only quantifying uncertainty, but also reducing it). This model generates an ensemble of merged rainfall estimates, which can then be used as input to urban drainage models in order to examine how uncertainties in rainfall estimates propagate to urban runoff estimates. The proposed model is tested using as case study a detailed rainfall and flow dataset, and a carefully verified urban drainage model of a small (~9 km2) pilot catchment in North-East London. The model has shown to well characterise residual errors in rainfall data at urban scales (which remain after the merging), leading to improved runoff estimates. In fact, the majority of measured flow peaks are bounded within the uncertainty area produced by the runoff ensembles generated with the ensemble rainfall inputs. REFERENCES: [1] Ciach, G. J. & Krajewski, W. F. (1999). On the estimation of radar rainfall error variance. Advances in Water Resources, 22 (6), 585-595. [2] Rico-Ramirez, M. A., Liguori, S. & Schellart, A. N. A. (2015). Quantifying radar-rainfall uncertainties in urban drainage flow modelling. Journal of Hydrology, 528, 17-28.

Rainfall trends in the South Asian summer monsoon and its related large-scale dynamics with focus over Pakistan

NASA Astrophysics Data System (ADS)

Latif, M.; Syed, F. S.; Hannachi, A.

2017-06-01

The study of regional rainfall trends over South Asia is critically important for food security and economy, as both these factors largely depend on the availability of water. In this study, South Asian summer monsoon rainfall trends on seasonal and monthly (June-September) time scales have been investigated using three observational data sets. Our analysis identify a dipole-type structure in rainfall trends over the region north of the Indo-Pak subcontinent, with significant increasing trends over the core monsoon region of Pakistan and significant decreasing trends over the central-north India and adjacent areas. The dipole is also evident in monthly rainfall trend analyses, which is more prominent in July and August. We show, in particular, that the strengthening of northward moisture transport over the Arabian Sea is a likely reason for the significant positive trend of rainfall in the core monsoon region of Pakistan. In contrast, over the central-north India region, the rainfall trends are significantly decreasing due to the weakening of northward moisture transport over the Bay of Bengal. The leading empirical orthogonal functions clearly show the strengthening (weakening) patterns of vertically integrated moisture transport over the Arabian Sea (Bay of Bengal) in seasonal and monthly interannual time scales. The regression analysis between the principal components and rainfall confirm the dipole pattern over the region. Our results also suggest that the extra-tropical phenomena could influence the mean monsoon rainfall trends over Pakistan by enhancing the cross-equatorial flow of moisture into the Arabian Sea.

Downscaling of Global Climate Change Estimates to Regional Scales: An Application to Iberian Rainfall in Wintertime.

NASA Astrophysics Data System (ADS)

von Storch, Hans; Zorita, Eduardo; Cubasch, Ulrich

1993-06-01

A statistical strategy to deduct regional-scale features from climate general circulation model (GCM) simulations has been designed and tested. The main idea is to interrelate the characteristic patterns of observed simultaneous variations of regional climate parameters and of large-scale atmospheric flow using the canonical correlation technique.The large-scale North Atlantic sea level pressure (SLP) is related to the regional, variable, winter (DJF) mean Iberian Peninsula rainfall. The skill of the resulting statistical model is shown by reproducing, to a good approximation, the winter mean Iberian rainfall from 1900 to present from the observed North Atlantic mean SLP distributions. It is shown that this observed relationship between these two variables is not well reproduced in the output of a general circulation model (GCM).The implications for Iberian rainfall changes as the response to increasing atmospheric greenhouse-gas concentrations simulated by two GCM experiments are examined with the proposed statistical model. In an instantaneous `2 C02' doubling experiment, using the simulated change of the mean North Atlantic SLP field to predict Iberian rainfall yields, there is an insignificant increase of area-averaged rainfall of 1 mm/month, with maximum values of 4 mm/month in the northwest of the peninsula. In contrast, for the four GCM grid points representing the Iberian Peninsula, the change is 10 mm/month, with a minimum of 19 mm/month in the southwest. In the second experiment, with the IPCC scenario A ("business as usual") increase Of C02, the statistical-model results partially differ from the directly simulated rainfall changes: in the experimental range of 100 years, the area-averaged rainfall decreases by 7 mm/month (statistical model), and by 9 mm/month (GCM); at the same time the amplitude of the interdecadal variability is quite different.

Synchrony, compensatory dynamics, and the functional trait basis of phenological diversity in a tropical dry forest tree community: effects of rainfall seasonality

NASA Astrophysics Data System (ADS)

Lasky, Jesse R.; Uriarte, María; Muscarella, Robert

2016-11-01

Interspecific variation in phenology is a key axis of functional diversity, potentially mediating how communities respond to climate change. The diverse drivers of phenology act across multiple temporal scales. For example, abiotic constraints favor synchronous reproduction (positive covariance among species), while biotic interactions can favor synchrony or compensatory dynamics (negative covariance). We used wavelet analyses to examine phenology of community flower and seed production for 45 tree species across multiple temporal scales in a tropical dry forest in Puerto Rico with marked rainfall seasonality. We asked three questions: (1) do species exhibit synchronous or compensatory temporal dynamics in reproduction, (2) do interspecific differences in phenology reflect variable responses to rainfall, and (3) is interspecific variation in phenology and response to a major drought associated with functional traits that mediate responses to moisture? Community-level flowering was synchronized at seasonal scales (˜5-6 mo) and at short scales (˜1 mo, following rainfall). However, seed rain exhibited significant compensatory dynamics at intraseasonal scales (˜3 mo), suggesting interspecific variation in temporal niches. Species with large leaves (associated with sensitivity to water deficit) peaked in reproduction synchronously with the peak of seasonal rainfall (˜5 mo scale). By contrast, species with high wood specific gravity (associated with drought resistance) tended to flower in drier periods. Flowering of tall species and those with large leaves was most tightly linked to intraseasonal (˜2 mo scale) rainfall fluctuations. Although the 2015 drought dramatically reduced community-wide reproduction, functional traits were not associated with the magnitude of species-specific declines. Our results suggest opposing drivers of synchronous versus compensatory dynamics at different temporal scales. Phenology associations with functional traits indicated that distinct strategies for coping with seasonality underlie phenological diversity. Observed drought responses highlight the importance of non-linear community responses to climate. Community phenology exhibits scale-specific patterns highlighting the need for multi-scale approaches to community dynamics.

Influences of large-scale convection and moisture source on monthly precipitation isotope ratios observed in Thailand, Southeast Asia

NASA Astrophysics Data System (ADS)

Wei, Zhongwang; Lee, Xuhui; Liu, Zhongfang; Seeboonruang, Uma; Koike, Masahiro; Yoshimura, Kei

2018-04-01

Many paleoclimatic records in Southeast Asia rely on rainfall isotope ratios as proxies for past hydroclimatic variability. However, the physical processes controlling modern rainfall isotopic behaviors in the region is poorly constrained. Here, we combined isotopic measurements at six sites across Thailand with an isotope-incorporated atmospheric circulation model (IsoGSM) and the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model to investigate the factors that govern the variability of precipitation isotope ratios in this region. Results show that rainfall isotope ratios are both correlated with local rainfall amount and regional outgoing longwave radiation, suggesting that rainfall isotope ratios in this region are controlled not only by local rain amount (amount effect) but also by large-scale convection. As a transition zone between the Indian monsoon and the western North Pacific monsoon, the spatial difference of observed precipitation isotope among different sites are associated with moisture source. These results highlight the importance of regional processes in determining rainfall isotope ratios in the tropics and provide constraints on the interpretation of paleo-precipitation isotope records in the context of regional climate dynamics.

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

NASA Technical Reports Server (NTRS)

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

2006-01-01

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

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.

Meteorological impact assessment of possible large scale irrigation in Southwest Saudi Arabia

NASA Astrophysics Data System (ADS)

Ter Maat, H. W.; Hutjes, R. W. A.; Ohba, R.; Ueda, H.; Bisselink, B.; Bauer, T.

2006-11-01

On continental to regional scales feedbacks between landuse and landcover change and climate have been widely documented over the past 10-15 years. In the present study we explore the possibility that also vegetation changes over much smaller areas may affect local precipitation regimes. Large scale (˜ 10 5 ha) irrigated plantations in semi-arid environments under particular conditions may affect local circulations and induce additional rainfall. Capturing this rainfall 'surplus' could then reduce the need for external irrigation sources and eventually lead to self-sustained water cycling. This concept is studied in the coastal plains in South West Saudi Arabia where the mountains of the Asir region exhibit the highest rainfall of the peninsula due to orographic lifting and condensation of moisture imported with the Indian Ocean monsoon and with disturbances from the Mediterranean Sea. We use a regional atmospheric modeling system (RAMS) forced by ECMWF analysis data to resolve the effect of complex surface conditions in high resolution (Δ x = 4 km). After validation, these simulations are analysed with a focus on the role of local processes (sea breezes, orographic lifting and the formation of fog in the coastal mountains) in generating rainfall, and on how these will be affected by large scale irrigated plantations in the coastal desert. The validation showed that the model simulates the regional and local weather reasonably well. The simulations exhibit a slightly larger diurnal temperature range than those captured by the observations, but seem to capture daily sea-breeze phenomena well. Monthly rainfall is well reproduced at coarse resolutions, but appears more localized at high resolutions. The hypothetical irrigated plantation (3.25 10 5 ha) has significant effects on atmospheric moisture, but due to weakened sea breezes this leads to limited increases of rainfall. In terms of recycling of irrigation gifts the rainfall enhancement in this particular setting is rather insignificant.

The collaborative historical African rainfall model: description and evaluation

USGS Publications Warehouse

Funk, Christopher C.; Michaelsen, Joel C.; Verdin, James P.; Artan, Guleid A.; Husak, Gregory; Senay, Gabriel B.; Gadain, Hussein; Magadazire, Tamuka

2003-01-01

In Africa the variability of rainfall in space and time is high, and the general availability of historical gauge data is low. This makes many food security and hydrologic preparedness activities difficult. In order to help overcome this limitation, we have created the Collaborative Historical African Rainfall Model (CHARM). CHARM combines three sources of information: climatologically aided interpolated (CAI) rainfall grids (monthly/0.5° ), National Centers for Environmental Prediction reanalysis precipitation fields (daily/1.875° ) and orographic enhancement estimates (daily/0.1° ). The first set of weights scales the daily reanalysis precipitation fields to match the gridded CAI monthly rainfall time series. This produces data with a daily/0.5° resolution. A diagnostic model of orographic precipitation, VDELB—based on the dot-product of the surface wind V and terrain gradient (DEL) and atmospheric buoyancy B—is then used to estimate the precipitation enhancement produced by complex terrain. Although the data are produced on 0.1° grids to facilitate integration with satellite-based rainfall estimates, the ‘true’ resolution of the data will be less than this value, and varies with station density, topography, and precipitation dynamics. The CHARM is best suited, therefore, to applications that integrate rainfall or rainfall-driven model results over large regions. The CHARM time series is compared with three independent datasets: dekadal satellite-based rainfall estimates across the continent, dekadal interpolated gauge data in Mali, and daily interpolated gauge data in western Kenya. These comparisons suggest reasonable accuracies (standard errors of about half a standard deviation) when data are aggregated to regional scales, even at daily time steps. Thus constrained, numerical weather prediction precipitation fields do a reasonable job of representing large-scale diurnal variations.

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

PubMed Central

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

2012-01-01

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

Convective Systems Over the South China Sea: Cloud-Resolving Model Simulations

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Shie, C.-L.; Johnson, D.; Simpson, J.; Braun, S.; Johnson, R.; Ciesielski, P. E.; Starr, David OC. (Technical Monitor)

2002-01-01

The South China Sea Monsoon Experiment (SCSMEX) was conducted in May-June 1998. One of its major objectives is to better understand the key physical processes for the onset and evolution of the summer monsoon over Southeast Asia and southern China. Multiple observation platforms (e.g., upper-air soundings, Doppler radar, ships, wind profilers, radiometers, etc.) during SCSMEX provided a first attempt at investigating the detailed characteristics of convective storms and air pattern changes associated with monsoons over the South China Sea region. SCSMEX also provided rainfall estimates which allows for comparisons with those obtained from the Tropical Rainfall Measuring Mission (TRMM), a low earth orbit satellite designed to measure rainfall from space. The Goddard Cumulus Ensemble (GCE) model (with 1-km grid size) is used to understand and quantify the precipitation processes associated with the summer monsoon over the South China Sea. This is the first (loud-resolving model used to simulate precipitation processes in this particular region. The GCE-model results captured many of the observed precipitation characteristics because it used a fine grid size. For example, the temporal variation of the simulated rainfall compares quite well to the sounding-estimated rainfall variation. The time and domain-averaged temperature (heating/cooling) and water vapor (drying/ moistening) budgets are in good agreement with observations. The GCE-model-simulated rainfall amount also agrees well with TRMM rainfall data. The results show there is more evaporation from the ocean surface prior to the onset of the monsoon than after the on-et of monsoon when rainfall increases. Forcing due to net radiation (solar heating minus longwave cooling) is responsible for about 25% of the precipitation in SCSMEX The transfer of heat from the ocean into the atmosphere does not contribute significantly to the rainfall in SCSMEX. Model sensitivity tests indicated that total rain production is reduced 17-18% in runs neglecting the ice phase. The SCSMEX results are compared to other GCE-model-simulated weather systems that developed during other field campaigns (i.e., west Pacific warm pool region, eastern Atlantic region and central USA). Large-scale forcing vie temperature and water vapor tendency, is the major energy source for net condensation in the tropical cases. The effects of large-scale cooling exceed that of large-scale moistening in the west pacific warm pool region and eastern Atlantic region. For SCSMEX, however, the effects of large-scale moistening predominate. Net radiation and sensible and latent hc,it fluxes play a much more important role in the central USA.

The Tropical Rainfall Measuring (TRMM) - What Have We Learned and What Does the Future Hold?

NASA Technical Reports Server (NTRS)

Kummerow, C.; Hong, Y.; Olsen, W. S.

2000-01-01

Rainfall is important in the hydrological cycle and to the lives and welfare of humans. In addition to being a life-giving resource, rainfall processes also plays a crucial role in the dynamics of the global atmospheric circulation. Three-fourths of the energy that drives the atmospheric wind circulation comes from the latent heat released by tropical precipitation. It varies greatly in space and time. The rain-producing cloud systems may last several hours or days. Their dimensions range from 10 km to several hundred km. This makes it difficult to incorporate rainfall directly large-scale weather and climate models. Until the end of 1997, precipitation in the global tropics was not known to within a factor of two. Regarding "global warming", the various large-scale models differed among themselves in the predicted magnitude of the warming and in the expected regional effects of these temperature and moisture changes. The Tropical Rainfall Measuring Mission (TRMM) satellite has yielded important interim results related to rainfall observations, data assimilation and model forecast skills when rainfall data is assimilated. This talk will summarize where the TRMM science team is with regards to answering some of these important scientific challenges, as well as discuss the future Global Precipitation Mission which will provide 3 hourly rainfall coverage and offers some unique collaborative potential for NOAA and NASA.

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.

Climatological studies on precipitation features and large-scale atmospheric fields on the heavy rainfall days in the eastern part of Japan from the Baiu to midsummer season

NASA Astrophysics Data System (ADS)

Matsumoto, Kengo; Kato, Kuranoshin; Otani, Kazuo

2017-04-01

In East Asia the significant subtropical frontal zone called the Meiyu (in China) / Baiu (in Japan) appears in early summer (just before the midsummer) and the huge rainfall is brought due to the frequent appearance of the "heavy rainfall days" (referred to as HRDs hereafter) mainly in that western part. On the other hand, large-scale fields around the front in eastern Japan is rather different from that in western Japan but the total precipitation in the eastern Japan is still considerable compared to that in the other midlatitude regions. Thus, it is also interesting to examine how the rainfall characteristics and large-scale atmospheric fields on HRDs (with more than 50 mm/day) in the eastern Japan in the mature stage of the Baiu season (16 June 15 July), together with those in midsummer (1 31 August). Based on such scientific background, further analyses were performed in this study mainly with the daily and the hourly precipitation data and the NCEP/NCAR re-analysis date from 1971 to 2010, succeeding to our previous results (e.g., EGU2015). As reported at EGU2014 and 2015, about half of HRDs at Tokyo (eastern Japan) were related to the typhoon even in the Baiu season. Interestingly, half of HRDs were characterized by the large contribution of moderate rain less than 10 mm/h. While, the precipitation on HRDs at Tokyo in midsummer was mainly brought by the intense rainfall with more than 10 mm/h, in association with the typhoons. In the present study, we examined the composite meridional structure of the rainfall area along 140E. In the pattern only associated with a typhoons in the Baiu season (Pattern A), the heavy rainfall area (more than 50 mm/day) with large contribution of the intense rain (stronger than 10 mm/h) showed rather wide meridional extension. The area was characterized by the duration of the intermittent enhancement of the rainfall. In the pattern associated with a typhoon and a front (Pattern B), while the contribution ratio of the rainfall more than 10mm/h was large in the southern half of the heavy rainfall area, moderate rain with less than 10 mm/h contributed greatly to the total rainfall in the northern half. In Patter B, that heavy rainfall area was located just in the area with strong low-level warm advection around the Baiu front to the east of the typhoon. The warm advection near the heavy rainfall area was also found in Pattern A, the heavy rainfall occurred just on the southwest of the large advection. It is noted that, although the very warm humid air can intrude northward by the strong S-ly wind to the east of the typhoon in both Pattern A and B, the low-level baroclinicity around the eastern Japan was stronger in Pattern B. In midsummer, the similar situations to while the "Pattern B"-like situation was not seen. This might be greatly reflected by the seasonal change in the southern boundary of the Okhotsk air mass from the Baiu to midsummer and we will also examine that in the future.

Downscaling of global climate change estimates to regional scales: An application to Iberian rainfall in wintertime

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

von Storch, H.; Zorita, E.; Cubasch, U.

A statistical strategy to deduct regional-scale features from climate general circulation model (GCM) simulations has been designed and tested. The main idea is to interrelate the characteristic patterns of observed simultaneous variations of regional climate parameters and of large-scale atmospheric flow using the canonical correlation technique. The large-scale North Atlantic sea level pressure (SLP) is related to the regional, variable, winter (DJF) mean Iberian Peninsula rainfall. The skill of the resulting statistical model is shown by reproducing, to a good approximation, the winter mean Iberian rainfall from 1900 to present from the observed North Atlantic mean SLP distributions. It ismore » shown that this observed relationship between these two variables is not well reproduced in the output of a general circulation model (GCM). The implications for Iberian rainfall changes as the response to increasing atmospheric greenhouse-gas concentrations simulated by two GCM experiments are examined with the proposed statistical model. In an instantaneous [open quotes]2 CO[sub 2][close quotes] doubling experiment, using the simulated change of the mean North Atlantic SLP field to predict Iberian rainfall yields, there is an insignificant increase of area-averaged rainfall of I mm/month, with maximum values of 4 mm/month in the northwest of the peninsula. In contrast, for the four GCM grid points representing the lberian Peninsula, the change is - 10 mm/month, with a minimum of - 19 mm/month in the southwest. In the second experiment, with the IPCC scenario A ([open quotes]business as usual[close quotes]) increase of CO[sub 2], the statistical-model results partially differ from the directly simulated rainfall changes: in the experimental range of 100 years, the area-averaged rainfall decreases by 7 mm/month (statistical model), and by 9 mm/month (GCM); at the same time the amplitude of the interdecadal variability is quite different. 17 refs., 10 figs.« less

ENSO Precipitation Variations as Seen by GPM and TRMM Radar and Passive Microwave Observations

NASA Astrophysics Data System (ADS)

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

2017-12-01

Tropical precipitation variations related to ENSO are the largest-scale such variations both spatially and in magnitude and are also the main driver of surface temperature-surface rainfall relationships on the inter-annual scale. GPM (and TRMM before it) provide a unique capability to examine these relations with both the passive and active microwave approaches. Documenting the phase and magnitudes of these relationships are important to understand these large-scale processes and to validate climate models. However, as past research by the authors have shown, the results of these relations have been different for passive vs. radar retrievals. In this study we re-examine these relations with the new GPM Version 5 products, focusing on the 2015-2016 El Nino event. The recent El Nino peaked in Dec. 2015 through Feb. 2016 with the usual patterns of precipitation anomalies across the Tropics as evident in both the GPM GMI and the Near Surface (NS) DPR (single frequency) retrievals. Integrating both the rainfall anomalies and the SST anomalies over the entire tropical ocean area (25N-25S) and comparing how they vary as a function of time on a monthly scale during the GPM era (2014-2017), the radar-based results show contrasting results to those from the GMI-based (and GPCP) results. The passive microwave data (GMI and GPCP) indicates a slope of 17%/C for the precipitation variations, while the radar NS indicates about half that ( 8%/C). This NS slope is somewhat less than calculated before with GPM's V4 data, but is larger than obtained with TRMM PR data ( 0%/C) for an earlier period during the TRMM era. Very similar results as to the DPR NS calculations are also obtained for rainfall at 2km and 4km altitude and for the Combined (DPR + GMI) product. However, at 6km altitude, although the reflectivity and rainfall magnitudes are much less than at lower altitudes, the slope of the rainfall/SST relation is 17%/C, the same as calculated with the passive microwave data. The reasons for these differences are explored and lead to conclusions that the radar-based estimates of surface rainfall with GPM have limitations (and are negatively biased) in relatively intense rainfall and this leads to an underestimation of large-scale rainfall under El Nino conditions, where more oceanic rainfall, and more intense rainfall are prevalent.

Vegetation Response to Rainfall and Soil Moisture Variability in Botswana

DTIC Science & Technology

1991-01-01

Effects of Varying Soil Type on the NDVI /Rainfall and NDVI /Soil Moisture...examine the effects of different soil types on the vegetation growth/rainfall relationship. The goals are to determine whether differences in the water-use...34first step" in removing the soil effect (Huete et al., 1985). Indeed, no large-scale soil corrections have been attempted as yet on NDVI data.

Quantitative mapping of rainfall rates over the oceans utilizing Nimbus-5 ESMR data

NASA Technical Reports Server (NTRS)

Rao, M. S. V.; Abbott, W. V.

1976-01-01

The electrically scanning microwave radiometer (ESMR) data from the Nimbus 5 satellite was used to deduce estimates of precipitation amount over the oceans. An atlas of the global oceanic rainfall was prepared and the global rainfall maps analyzed and related to available ground truth information as well as to large scale processes in the atmosphere. It was concluded that the ESMR system provides the most reliable and direct approach yet known for the estimation of rainfall over sparsely documented, wide oceanic regions.

Effects of rainfall spatial variability and intermittency on shallow landslide triggering patterns at a catchment scale

NASA Astrophysics Data System (ADS)

von Ruette, J.; Lehmann, P.; Or, D.

2014-10-01

The occurrence of shallow landslides is often associated with intense and prolonged rainfall events, where infiltrating water reduces soil strength and may lead to abrupt mass release. Despite general understanding of the role of rainfall water in slope stability, the prediction of rainfall-induced landslides remains a challenge due to natural heterogeneity that affect hydrologic loading patterns and the largely unobservable internal progressive failures. An often overlooked and potentially important factor is the role of rainfall variability in space and time on landslide triggering that is often obscured by coarse information (e.g., hourly radar data at spatial resolution of a few kilometers). To quantify potential effects of rainfall variability on failure dynamics, spatial patterns, landslide numbers and volumes, we employed a physically based "Catchment-scale Hydromechanical Landslide Triggering" (CHLT) model for a study area where a summer storm in 2002 triggered 51 shallow landslides. In numerical experiments based on the CHLT model, we applied the measured rainfall amount of 53 mm in different artificial spatiotemporal rainfall patterns, resulting in between 30 and 100 landslides and total released soil volumes between 3000 and 60,000 m3 for the various scenarios. Results indicate that low intensity rainfall below soil's infiltration capacity resulted in the largest mechanical perturbation. This study illustrates how small-scale rainfall variability that is often overlooked by present operational rainfall data may play a key role in shaping landslide patterns.

Conceptual modelling of E. coli in urban stormwater drains, creeks and rivers

NASA Astrophysics Data System (ADS)

Jovanovic, Dusan; Hathaway, Jon; Coleman, Rhys; Deletic, Ana; McCarthy, David T.

2017-12-01

Accurate estimation of faecal microorganism levels in water systems, such as stormwater drains, creeks and rivers, is needed for appropriate assessment of impacts on receiving water bodies and the risks to human health. The underlying hypothesis for this work is that a single conceptual model (the MicroOrganism Prediction in Urban Stormwater model - i.e. MOPUS) can adequately simulate microbial dynamics over a variety of water systems and wide range of scales; something which has not been previously tested. Additionally, the application of radar precipitation data for improvement of the model performance at these scales via more accurate areal averaged rainfall intensities was tested. Six comprehensive Escherichia coli (E. coli) datasets collected from five catchments in south-eastern Australia and one catchment in Raleigh, USA, were used to calibrate the model. The MOPUS rainfall-runoff model performed well at all scales (Nash-Sutcliffe E for instantaneous flow rates between 0.70 and 0.93). Sensitivity analysis showed that wet weather urban stormwater flows can be modelled with only three of the five rainfall runoff model parameters: routing coefficient (K), effective imperviousness (IMP) and time of concentration (TOC). The model's performance for representing instantaneous E. coli fluctuations ranged from 0.17 to 0.45 in catchments drained via pipe or open creek, and was the highest for a large riverine catchment (0.64); performing similarly, if not better, than other microbial models in literature. The model could also capture the variability in event mean concentrations (E = 0.17-0.57) and event loads (E = 0.32-0.97) at all scales. Application of weather radar-derived rainfall inputs caused lower overall performance compared to using gauged rainfall inputs in representing both flow and E. coli levels in urban drain catchments, with the performance improving with increasing catchment size and being comparable to the models that use gauged rainfall inputs at the large riverine catchment. These results demonstrate the potential of the MOPUS model and its ability to be applied to a wide range of catchment scales, including large riverine systems.

Small scale rainfall simulators: Challenges for a future use in soil erosion research

NASA Astrophysics Data System (ADS)

Ries, Johannes B.; Iserloh, Thomas; Seeger, Manuel

2013-04-01

Rainfall simulation on micro-plot scale is a method used worldwide to assess the generation of overland flow, soil erosion, infiltration and interrelated processes such as soil sealing, crusting, splash and redistribution of solids and solutes. The produced data are of great significance not only for the analysis of the simulated processes, but also as a source of input-data for soil erosion modelling. The reliability of the data is therefore of paramount importance, and quality management of rainfall simulation procedure a general responsibility of the rainfall simulation community. This was an accepted outcome at the "International Rainfall Simulator Workshop 2011" at Trier University. The challenges of the present and near future use of small scale rainfall simulations concern the comparability of results and scales, the quality of the data for soil erosion modelling, and further technical developments to overcome physical limitations and constraints. Regarding the high number of research questions, different fields of application, and due to the great technical creativity of researchers, a large number of different types of rainfall simulators is available. But each of the devices produces a different rainfall, leading to different kinetic energy values influencing soil surface and erosion processes. Plot sizes are also variable, as well as the experimental simulation procedures. As a consequence, differing runoff and erosion results are produced. The presentation summarises the three important aspects of rainfall simulations, following a processual order: 1. Input-factor "rain" and its calibration 2. Surface-factor "plot" and its documentation 3. Output-factors "runoff" and "sediment concentration" Finally, general considerations about the limitations and challenges for further developments and applications of rainfall simulation data are presented.

Uncertainties in TRMM-Era multisatellite-based tropical rainfall estimates over the Maritime Continent

NASA Astrophysics Data System (ADS)

Rauniyar, S. P.; Protat, A.; Kanamori, H.

2017-05-01

This study investigates the regional and seasonal rainfall rate retrieval uncertainties within nine state-of-the-art satellite-based rainfall products over the Maritime Continent (MC) region. The results show consistently larger differences in mean daily rainfall among products over land, especially over mountains and along coasts, compared to over ocean, by about 20% for low to medium rain rates and 5% for heavy rain rates. However, rainfall differences among the products do not exhibit any seasonal dependency over both surface types (land and ocean) of the MC region. The differences between products largely depends on the rain rate itself, with a factor 2 difference for light rain and 30% for intermediate and high rain rates over ocean. The rain-rate products dominated by microwave measurements showed less spread among themselves over ocean compared to the products dominated by infrared measurements. Conversely, over land, the rain gauge-adjusted post-real-time products dominated by microwave measurements produced the largest spreads, due to the usage of different gauge analyses for the bias corrections. Intercomparisons of rainfall characteristics of these products revealed large discrepancies in detecting the frequency and intensity of rainfall. These satellite products are finally evaluated at subdaily, daily, monthly, intraseasonal, and seasonal temporal scales against high-quality gridded rainfall observations in the Sarawak (Malaysia) region for the 4 year period 2000-2003. No single satellite-based rainfall product clearly outperforms the other products at all temporal scales. General guidelines are provided for selecting a product that could be best suited for a particular application and/or temporal resolution.

Short-term rainfall: its scaling properties over Portugal

NASA Astrophysics Data System (ADS)

de Lima, M. Isabel P.

2010-05-01

The characterization of rainfall at a variety of space- and time-scales demands usually that data from different origins and resolution are explored. Different tools and methodologies can be used for this purpose. In regions where the spatial variation of rain is marked, the study of the scaling structure of rainfall can lead to a better understanding of the type of events affecting that specific area, which is essential for many engineering applications. The relevant factors affecting rain variability, in time and space, can lead to contrasting statistics which should be carefully taken into account in design procedures and decision making processes. One such region is Mainland Portugal; the territory is located in the transitional region between the sub-tropical anticyclone and the subpolar depression zones and is characterized by strong north-south and east-west rainfall gradients. The spatial distribution and seasonal variability of rain are particularly influenced by the characteristics of the global circulation. One specific feature is the Atlantic origin of many synoptic disturbances in the context of the regional geography (e.g. latitude, orography, oceanic and continental influences). Thus, aiming at investigating the statistical signature of rain events of different origins, resulting from the large number of mechanisms and factors affecting the rainfall climate over Portugal, scale-invariant analyses of the temporal structure of rain from several locations in mainland Portugal were conducted. The study used short-term rainfall time series. Relevant scaling ranges were identified and characterized that help clarifying the small-scale behaviour and statistics of this process.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

Rainfall Downscaling Conditional on Upper-air Atmospheric Predictors: Improved Assessment of Rainfall Statistics in a Changing Climate

NASA Astrophysics Data System (ADS)

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

2015-04-01

To improve the level skill of Global Climate Models (GCMs) and Regional Climate Models (RCMs) in reproducing the statistics of rainfall at a basin level and at hydrologically relevant temporal scales (e.g. daily), two types of statistical approaches have been suggested. One is the statistical correction of climate model rainfall outputs using historical series of precipitation. The other is the use of stochastic models of rainfall to conditionally simulate precipitation series, based on large-scale atmospheric predictors produced by climate models (e.g. geopotential height, relative vorticity, divergence, mean sea level pressure). The latter approach, usually referred to as statistical rainfall downscaling, aims at reproducing the statistical character of rainfall, while accounting for the effects of large-scale atmospheric circulation (and, therefore, climate forcing) on rainfall statistics. While promising, statistical rainfall downscaling has not attracted much attention in recent years, since the suggested approaches involved complex (i.e. subjective or computationally intense) identification procedures of the local weather, in addition to demonstrating limited success in reproducing several statistical features of rainfall, such as seasonal variations, the distributions of dry and wet spell lengths, the distribution of the mean rainfall intensity inside wet periods, and the distribution of rainfall extremes. In an effort to remedy those shortcomings, Langousis and Kaleris (2014) developed a statistical framework for simulation of daily rainfall intensities conditional on upper air variables, which accurately reproduces the statistical character of rainfall at multiple time-scales. Here, we study the relative performance of: a) quantile-quantile (Q-Q) correction of climate model rainfall products, and b) the statistical downscaling scheme of Langousis and Kaleris (2014), in reproducing the statistical structure of rainfall, as well as rainfall extremes, at a regional level. This is done for an intermediate-sized catchment in Italy, i.e. the Flumendosa catchment, using climate model rainfall and atmospheric data from the ENSEMBLES project (http://ensembleseu.metoffice.com). In doing so, we split the historical rainfall record of mean areal precipitation (MAP) in 15-year calibration and 45-year validation periods, and compare the historical rainfall statistics to those obtained from: a) Q-Q corrected climate model rainfall products, and b) synthetic rainfall series generated by the suggested downscaling scheme. To our knowledge, this is the first time that climate model rainfall and statistically downscaled precipitation are compared to catchment-averaged MAP at a daily resolution. The obtained results are promising, since the proposed downscaling scheme is more accurate and robust in reproducing a number of historical rainfall statistics, independent of the climate model used and the length of the calibration period. This is particularly the case for the yearly rainfall maxima, where direct statistical correction of climate model rainfall outputs shows increased sensitivity to the length of the calibration period and the climate model used. The robustness of the suggested downscaling scheme in modeling rainfall extremes at a daily resolution, is a notable feature that can effectively be used to assess hydrologic risk at a regional level under changing climatic conditions. Acknowledgments The research project is implemented within the framework of the Action «Supporting Postdoctoral Researchers» of the Operational Program "Education and Lifelong Learning" (Action's Beneficiary: General Secretariat for Research and Technology), and is co-financed by the European Social Fund (ESF) and the Greek State. CRS4 highly acknowledges the contribution of the Sardinian regional authorities.

Spatial Scaling of Global Rainfall and Flood Extremes

NASA Astrophysics Data System (ADS)

Devineni, Naresh; Lall, Upmanu; Xi, Chen; Ward, Philip

2014-05-01

Floods associated with severe storms are a significant source of risk for property, life and supply chains. These property losses tend to be determined as much by the duration and spatial extent of flooding as by the depth and velocity of inundation. High duration floods are typically induced by persistent rainfall (up to 30 day duration) as seen recently in Thailand, Pakistan, the Ohio and the Mississippi Rivers, France, and Germany. Events related to persistent and recurrent rainfall appear to correspond to the persistence of specific global climate patterns that may be identifiable from global, historical data fields, and also from climate models that project future conditions. In this paper, we investigate the statistical properties of the spatial manifestation of the rainfall exceedances and floods. We present the first ever results on a global analysis of the scaling characteristics of extreme rainfall and flood event duration, volumes and contiguous flooded areas as a result of large scale organization of long duration rainfall events. Results are organized by latitude and with reference to the phases of ENSO, and reveal surprising invariance across latitude. Speculation as to the potential relation to the dynamical factors is presented

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.

Uncertainty based modeling of rainfall-runoff: Combined differential evolution adaptive Metropolis (DREAM) and K-means clustering

NASA Astrophysics Data System (ADS)

Zahmatkesh, Zahra; Karamouz, Mohammad; Nazif, Sara

2015-09-01

Simulation of rainfall-runoff process in urban areas is of great importance considering the consequences and damages of extreme runoff events and floods. The first issue in flood hazard analysis is rainfall simulation. Large scale climate signals have been proved to be effective in rainfall simulation and prediction. In this study, an integrated scheme is developed for rainfall-runoff modeling considering different sources of uncertainty. This scheme includes three main steps of rainfall forecasting, rainfall-runoff simulation and future runoff prediction. In the first step, data driven models are developed and used to forecast rainfall using large scale climate signals as rainfall predictors. Due to high effect of different sources of uncertainty on the output of hydrologic models, in the second step uncertainty associated with input data, model parameters and model structure is incorporated in rainfall-runoff modeling and simulation. Three rainfall-runoff simulation models are developed for consideration of model conceptual (structural) uncertainty in real time runoff forecasting. To analyze the uncertainty of the model structure, streamflows generated by alternative rainfall-runoff models are combined, through developing a weighting method based on K-means clustering. Model parameters and input uncertainty are investigated using an adaptive Markov Chain Monte Carlo method. Finally, calibrated rainfall-runoff models are driven using the forecasted rainfall to predict future runoff for the watershed. The proposed scheme is employed in the case study of the Bronx River watershed, New York City. Results of uncertainty analysis of rainfall-runoff modeling reveal that simultaneous estimation of model parameters and input uncertainty significantly changes the probability distribution of the model parameters. It is also observed that by combining the outputs of the hydrological models using the proposed clustering scheme, the accuracy of runoff simulation in the watershed is remarkably improved up to 50% in comparison to the simulations by the individual models. Results indicate that the developed methodology not only provides reliable tools for rainfall and runoff modeling, but also adequate time for incorporating required mitigation measures in dealing with potentially extreme runoff events and flood hazard. Results of this study can be used in identification of the main factors affecting flood hazard analysis.

Water yield issues in the jarrah forest of south-western Australia

NASA Astrophysics Data System (ADS)

Ruprecht, J. K.; Stoneman, G. L.

1993-10-01

The jarrah forest of south-western Australia produces little streamflow from moderate rainfall. Water yield from water supply catchments for Perth, Western Australia, are low, averaging 71 mm (7% of annual rainfall). The low water yields are attributed to the large soil water storage available for continuous use by the forest vegetation. A number of water yield studies in south-western Australia have examined the impact on water yield of land use practices including clearing for agricultural development, forest harvesting and regeneration, forest thinning and bauxite mining. A permanent reduction in forest cover by clearing for agriculture led to permanent increases of water yield of approximately 28% of annual rainfall in a high rainfall catchment. Thinning of a high rainfall catchment led to an increase in water yield of 20% of annual rainfall. However, it is not clear for how long the increased water yield will persist. Forest harvesting and regeneration have led to water yield increases of 16% of annual rainfall. The subsequent recovery of vegetation cover has led to water yields returning to pre-disturbance levels after an estimated 12-15 years. Bauxite mining of a high rainfall catchment led to a water yield increase of 8% of annual rainfall, followed by a return to pre-disturbance water yield after 12 years. The magnitude of specific streamflow generation mechanisms in small catchments subject to forest disturbance vary considerably, typically in a number of distinct stages. The presence of a permanent groundwater discharge area was shown to be instrumental in determining the magnitude of the streamflow response after forest disturbance. The long-term prognosis for water yield from areas subject to forest thinning, harvesting and regeneration, and bauxite mining are uncertain, owing to the complex interrelationship between vegetation cover, tree height and age, and catchment evapotranspiration. Management of the forest for water yield needs to acknowledge this complexity and evaluate forest management strategies both at the large catchment scale and at long time-scales. The extensive network of small catchment experiments, regional studies, process studies and catchment modelling at both the small and large scale, which are carried out in the jarrah forest, are all considered as integral components of the research to develop these management strategies to optimise water yield from the jarrah forest, without forfeiting other forest values.

Detecting Trends in Tropical Rainfall Characteristics, 1979-2003

NASA Technical Reports Server (NTRS)

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

2006-01-01

From analyses of blended space-based and ground-based global rainfall data, we found increasing trends in the occurrence of extreme heavy and light rain events, coupled to a decreasing trend in moderate rain events in the tropics during 1979-2003. The trends are consistent with a shift in the large-scale circulation associated with a) a relatively uniform increase in warm rain over the tropical oceans, b) enhanced ice-phase rain over the near-equatorial oceans, and c) reduced mixed-phase rain over the tropical ocean and land regions. Due to the large compensation among different rain categories, the total tropical rainfall trend remained undetectable.

A Canonical Response in Rainfall Characteristics to Global Warming: Projections by IPCC CMIP5 Models

NASA Technical Reports Server (NTRS)

Lau, William K. M.; Wu, H. T.; Kim, K. M.

2012-01-01

Changes in rainfall characteristics induced by global warming are examined based on probability distribution function (PDF) analysis, from outputs of 14 IPCC (Intergovernmental Panel on Climate Change), CMIP (5th Coupled Model Intercomparison Project) models under various scenarios of increased CO2 emissions. Results show that collectively CMIP5 models project a robust and consistent global and regional rainfall response to CO2 warming. Globally, the models show a 1-3% increase in rainfall per degree rise in temperature, with a canonical response featuring large increase (100-250 %) in frequency of occurrence of very heavy rain, a reduction (5-10%) of moderate rain, and an increase (10-15%) of light rain events. Regionally, even though details vary among models, a majority of the models (>10 out of 14) project a consistent large scale response with more heavy rain events in climatologically wet regions, most pronounced in the Pacific ITCZ and the Asian monsoon. Moderate rain events are found to decrease over extensive regions of the subtropical and extratropical oceans, but increases over the extratropical land regions, and the Southern Oceans. The spatial distribution of light rain resembles that of moderate rain, but mostly with opposite polarity. The majority of the models also show increase in the number of dry events (absence or only trace amount of rain) over subtropical and tropical land regions in both hemispheres. These results suggest that rainfall characteristics are changing and that increased extreme rainfall events and droughts occurrences are connected, as a consequent of a global adjustment of the large scale circulation to global warming.

Improving Assimilated Global Climate Data Using TRMM and SSM/I Rainfall and Moisture Data

NASA Technical Reports Server (NTRS)

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

1999-01-01

Current global analyses contain significant errors in primary hydrological fields such as precipitation, evaporation, and related cloud and moisture in the tropics. Work has been underway at NASA's Data Assimilation Office to explore the use of TRMM and SSM/I-derived rainfall and total precipitable water (TPW) data in global data assimilation to directly constrain these hydrological parameters. We found that assimilating these data types improves not only the precipitation and moisture estimates but also key climate parameters directly linked to convection such as the outgoing longwave radiation, clouds, and the large-scale circulation in the tropics. We will present results showing that assimilating TRMM and SSM/I 6-hour averaged rain rates and TPW estimates significantly reduces the state-dependent systematic errors in assimilated products. Specifically, rainfall assimilation improves cloud and latent heating distributions, which, in turn, improves the cloudy-sky radiation and the large-scale circulation, while TPW assimilation reduces moisture biases to improve radiation in clear-sky regions. Rainfall and TPW assimilation also improves tropical forecasts beyond 1 day.

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

NASA Astrophysics Data System (ADS)

Saatchi, S.; Asefi, S.

2012-04-01

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

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

NASA Astrophysics Data System (ADS)

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

2011-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

Interannual rainfall variability and SOM-based circulation classification

NASA Astrophysics Data System (ADS)

Wolski, Piotr; Jack, Christopher; Tadross, Mark; van Aardenne, Lisa; Lennard, Christopher

2018-01-01

Self-Organizing Maps (SOM) based classifications of synoptic circulation patterns are increasingly being used to interpret large-scale drivers of local climate variability, and as part of statistical downscaling methodologies. These applications rely on a basic premise of synoptic climatology, i.e. that local weather is conditioned by the large-scale circulation. While it is clear that this relationship holds in principle, the implications of its implementation through SOM-based classification, particularly at interannual and longer time scales, are not well recognized. Here we use a SOM to understand the interannual synoptic drivers of climate variability at two locations in the winter and summer rainfall regimes of South Africa. We quantify the portion of variance in seasonal rainfall totals that is explained by year to year differences in the synoptic circulation, as schematized by a SOM. We furthermore test how different spatial domain sizes and synoptic variables affect the ability of the SOM to capture the dominant synoptic drivers of interannual rainfall variability. Additionally, we identify systematic synoptic forcing that is not captured by the SOM classification. The results indicate that the frequency of synoptic states, as schematized by a relatively disaggregated SOM (7 × 9) of prognostic atmospheric variables, including specific humidity, air temperature and geostrophic winds, captures only 20-45% of interannual local rainfall variability, and that the residual variance contains a strong systematic component. Utilising a multivariate linear regression framework demonstrates that this residual variance can largely be explained using synoptic variables over a particular location; even though they are used in the development of the SOM their influence, however, diminishes with the size of the SOM spatial domain. The influence of the SOM domain size, the choice of SOM atmospheric variables and grid-point explanatory variables on the levels of explained variance, is consistent with the general understanding of the dominant processes and atmospheric variables that affect rainfall variability at a particular location.

Large rainfall changes consistently projected over substantial areas of tropical land

NASA Astrophysics Data System (ADS)

Chadwick, Robin; Good, Peter; Martin, Gill; Rowell, David P.

2016-02-01

Many tropical countries are exceptionally vulnerable to changes in rainfall patterns, with floods or droughts often severely affecting human life and health, food and water supplies, ecosystems and infrastructure. There is widespread disagreement among climate model projections of how and where rainfall will change over tropical land at the regional scales relevant to impacts, with different models predicting the position of current tropical wet and dry regions to shift in different ways. Here we show that despite uncertainty in the location of future rainfall shifts, climate models consistently project that large rainfall changes will occur for a considerable proportion of tropical land over the twenty-first century. The area of semi-arid land affected by large changes under a higher emissions scenario is likely to be greater than during even the most extreme regional wet or dry periods of the twentieth century, such as the Sahel drought of the late 1960s to 1990s. Substantial changes are projected to occur by mid-century--earlier than previously expected--and to intensify in line with global temperature rise. Therefore, current climate projections contain quantitative, decision-relevant information on future regional rainfall changes, particularly with regard to climate change mitigation policy.

Space based observations: A state of the art solution for spatial monitoring tropical forested watershed productivity at regional scale in developing countries

NASA Astrophysics Data System (ADS)

Mahmud, M. R.

2014-02-01

This paper presents the simplified and operational approach of mapping the water yield in tropical watershed using space-based multi sensor remote sensing data. Two main critical hydrological rainfall variables namely rainfall and evapotranspiration are being estimated by satellite measurement and reinforce the famous Thornthwaite & Mather water balance model. The satellite rainfall and ET estimates were able to represent the actual value on the ground with accuracy under considerable conditions. The satellite derived water yield had good agreement and relation with actual streamflow. A high bias measurement may result due to; i) influence of satellite rainfall estimates during heavy storm, and ii) large uncertainties and standard deviation of MODIS temperature data product. The output of this study managed to improve the regional scale of hydrology assessment in Peninsular Malaysia.

Power-law scaling in daily rainfall patterns and consequences in urban stream discharges

NASA Astrophysics Data System (ADS)

Park, Jeryang; Krueger, Elisabeth H.; Kim, Dongkyun; Rao, Suresh C.

2016-04-01

Poissonian rainfall has been frequently used for modelling stream discharge in a catchment at the daily scale. Generally, it is assumed that the daily rainfall depth is described by memoryless exponential distribution which is transformed to stream discharge, resulting in an analytical pdf for discharge [Gamma distribution]. While it is true that catchment hydrological filtering processes (censored by constant rate ET losses, and first-order recession) increases "memory", reflected in 1/f noise in discharge time series. Here, we show that for urban watersheds in South Korea: (1) the observation of daily rainfall depths follow power-law pdfs, and spectral slopes range between 0.2 ~ 0.4; and (2) the stream discharge pdfs have power-law tails. These observation results suggest that multiple hydro-climatic factors (e.g., non-stationarity of rainfall patterns) and hydrologic filtering (increasing impervious area; more complex urban drainage networks) influence the catchment hydrologic responses. We test the role of such factors using a parsimonious model, using different types of daily rainfall patterns (e.g., power-law distributed rainfall depth with Poisson distribution in its frequency) and urban settings to reproduce patterns similar to those observed in empirical records. Our results indicate that fractality in temporally up-scaled rainfall, and the consequences of large extreme events are preserved as high discharge events in urbanizing catchments. Implications of these results to modeling urban hydrologic responses and impacts on receiving waters are discussed.

Feasibility Study on the Satellite Rainfall Data for Prediction of Sediment- Related Disaster by the Japanese Prediction Methodology

NASA Astrophysics Data System (ADS)

Shimizu, Y.; Ishizuka, T.; Osanai, N.; Okazumi, T.

2014-12-01

In this study, the sediment-related disaster prediction method which based ground gauged rainfall-data, currently practiced in Japan was coupled with satellite rainfall data and applied to domestic large-scale sediment-related disasters. The study confirmed the feasibility of this integrated method. In Asia, large-scale sediment-related disasters which can sweep away an entire settlement occur frequently. Leyte Island suffered from a huge landslide in 2004, and Typhoon Molakot in 2009 caused huge landslides in Taiwan. In the event of these sediment-related disasters, immediate responses by central and local governments are crucial in crisis management. In general, there are not enough rainfall gauge stations in developing countries. Therefore national and local governments have little information to determine the risk level of water induced disasters in their service areas. In the Japanese methodology, a criterion is set by combining two indices: the short-term rainfall index and long-term rainfall index. The short-term rainfall index is defined as the 60-minute total rainfall; the long-term rainfall index as the soil-water index, which is an estimation of the retention status of fallen rainfall in soil. In July 2009, a high-density sediment related disaster, or a debris flow, occurred in Hofu City of Yamaguchi Prefecture, in the western region of Japan. This event was calculated by the Japanese standard methodology, and then analyzed for its feasibility. Hourly satellite based rainfall has underestimates compared with ground based rainfall data. Long-term index correlates with each other. Therefore, this study confirmed that it is possible to deliver information on the risk level of sediment-related disasters such as shallow landslides and debris flows. The prediction method tested in this study is expected to assist for timely emergency responses to rainfall-induced natural disasters in sparsely gauged areas. As the Global Precipitation Measurement (GPM) Plan progresses, spatial resolution, time resolution and accuracy of rainfall data should be further improved and will be more effective in practical use.

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

NASA Astrophysics Data System (ADS)

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

2017-08-01

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

Changes in Intense Precipitation Events in West Africa and the central U.S. under Global Warming

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

Cook, Kerry H.; Vizy, Edward

The purpose of the proposed project is to improve our understanding of the physical processes and large-scale connectivity of changes in intense precipitation events (high rainfall rates) under global warming in West Africa and the central U.S., including relationships with low-frequency modes of variability. This is in response to the requested subject area #2 “simulation of climate extremes under a changing climate … to better quantify the frequency, duration, and intensity of extreme events under climate change and elucidate the role of low frequency climate variability in modulating extremes.” We will use a regional climate model and emphasize an understandingmore » of the physical processes that lead to an intensification of rainfall. The project objectives are as follows: 1. Understand the processes responsible for simulated changes in warm-season rainfall intensity and frequency over West Africa and the Central U.S. associated with greenhouse gas-induced global warming 2. Understand the relationship between changes in warm-season rainfall intensity and frequency, which generally occur on regional space scales, and the larger-scale global warming signal by considering modifications of low-frequency modes of variability. 3. Relate changes simulated on regional space scales to global-scale theories of how and why atmospheric moisture levels and rainfall should change as climate warms.« less

Diagnostics of Rainfall Anomalies in the Nordeste During the Global Weather Experiment

NASA Technical Reports Server (NTRS)

Sikdar, D. M.

1984-01-01

The relationship of the daily variability of large-scale pressure, cloudiness and upper level wind patterns over the Brazil-Atlantic sector during March/April 1979 to rainfall anomalies in northern Nordeste was investigated. The experiment divides the rainy season (March/April) of 1979 into wet and dry days, then composites bright cloudiness, sea level pressure, and upper level wind fields with respect to persistent rainfall episodes. Wet and dry anomalies are analyzed along with seasonal mean conditions.

Singularity-sensitive gauge-based radar rainfall adjustment methods for urban hydrological applications

NASA Astrophysics Data System (ADS)

Wang, L.-P.; Ochoa-Rodríguez, S.; Onof, C.; Willems, P.

2015-09-01

Gauge-based radar rainfall adjustment techniques have been widely used to improve the applicability of radar rainfall estimates to large-scale hydrological modelling. However, their use for urban hydrological applications is limited as they were mostly developed based upon Gaussian approximations and therefore tend to smooth off so-called "singularities" (features of a non-Gaussian field) that can be observed in the fine-scale rainfall structure. Overlooking the singularities could be critical, given that their distribution is highly consistent with that of local extreme magnitudes. This deficiency may cause large errors in the subsequent urban hydrological modelling. To address this limitation and improve the applicability of adjustment techniques at urban scales, a method is proposed herein which incorporates a local singularity analysis into existing adjustment techniques and allows the preservation of the singularity structures throughout the adjustment process. In this paper the proposed singularity analysis is incorporated into the Bayesian merging technique and the performance of the resulting singularity-sensitive method is compared with that of the original Bayesian (non singularity-sensitive) technique and the commonly used mean field bias adjustment. This test is conducted using as case study four storm events observed in the Portobello catchment (53 km2) (Edinburgh, UK) during 2011 and for which radar estimates, dense rain gauge and sewer flow records, as well as a recently calibrated urban drainage model were available. The results suggest that, in general, the proposed singularity-sensitive method can effectively preserve the non-normality in local rainfall structure, while retaining the ability of the original adjustment techniques to generate nearly unbiased estimates. Moreover, the ability of the singularity-sensitive technique to preserve the non-normality in rainfall estimates often leads to better reproduction of the urban drainage system's dynamics, particularly of peak runoff flows.

Estimation of sediment yield from subsequent expanded landslides after heavy rainfalls : a case study in central Hokkaido, Japan

NASA Astrophysics Data System (ADS)

Koshimizu, K.; Uchida, T.

2015-12-01

Initial large-scale sediment yield caused by heavy rainfall or major storms have made a strong impression on us. Previous studies focusing on landslide management investigated the initial sediment movement and its mechanism. However, integrated management of catchment-scale sediment movements requires estimating the sediment yield, which is produced by the subsequent expanded landslides due to rainfall, in addition to the initial landslide movement. This study presents a quantitative analysis of expanded landslides by surveying the Shukushubetsu River basin, at the foot of the Hidaka mountain range in central Hokkaido, Japan. This area recorded heavy rainfall in 2003, reaching a maximum daily precipitation of 388 mm. We extracted the expanded landslides from 2003 to 2008 using aerial photographs taken over the river area. In particular, we calculated the probability of expansion for each landslide, the ratio of the landslide area in 2008 as compared with that in 2003, and the amount of the expanded landslide area corresponding to the initial landslide area. As a result, it is estimated 24% about probability of expansion for each landslide. In addition, each expanded landslide area is smaller than the initial landslide area. Furthermore, the amount of each expanded landslide area in 2008 is approximately 7% of their landslide area in 2003. Therefore, the sediment yield from subsequent expanded landslides is equal to or slightly greater than the sediment yield in a typical base flow. Thus, we concluded that the amount of sediment yield from subsequent expanded landslides is lower than that of initial large-scale sediment yield caused by a heavy rainfall in terms of effect on management of catchment-scale sediment movement.

Generalizing a nonlinear geophysical flood theory to medium-sized river networks

USGS Publications Warehouse

Gupta, Vijay K.; Mantilla, Ricardo; Troutman, Brent M.; Dawdy, David; Krajewski, Witold F.

2010-01-01

The central hypothesis of a nonlinear geophysical flood theory postulates that, given space-time rainfall intensity for a rainfall-runoff event, solutions of coupled mass and momentum conservation differential equations governing runoff generation and transport in a self-similar river network produce spatial scaling, or a power law, relation between peak discharge and drainage area in the limit of large area. The excellent fit of a power law for the destructive flood event of June 2008 in the 32,400-km2 Iowa River basin over four orders of magnitude variation in drainage areas supports the central hypothesis. The challenge of predicting observed scaling exponent and intercept from physical processes is explained. We show scaling in mean annual peak discharges, and briefly discuss that it is physically connected with scaling in multiple rainfall-runoff events. Scaling in peak discharges would hold in a non-stationary climate due to global warming but its slope and intercept would change.

The development of a capability for aerodynamic testing of large-scale wing sections in a simulated natural rain environment

NASA Technical Reports Server (NTRS)

Bezos, Gaudy M.; Cambell, Bryan A.; Melson, W. Edward

1989-01-01

A research technique to obtain large-scale aerodynamic data in a simulated natural rain environment has been developed. A 10-ft chord NACA 64-210 wing section wing section equipped with leading-edge and trailing-edge high-lift devices was tested as part of a program to determine the effect of highly-concentrated, short-duration rainfall on airplane performance. Preliminary dry aerodynamic data are presented for the high-lift configuration at a velocity of 100 knots and an angle of attack of 18 deg. Also, data are presented on rainfield uniformity and rainfall concentration intensity levels obtained during the calibration of the rain simulation system.

Darfur: rainfall and conflict

NASA Astrophysics Data System (ADS)

Kevane, Michael; Gray, Leslie

2008-07-01

Data on rainfall patterns only weakly corroborate the claim that climate change explains the Darfur conflict that began in 2003 and has claimed more than 200 000 lives and displaced more than two million persons. Rainfall in Darfur did not decline significantly in the years prior to the eruption of major conflict in 2003; rainfall exhibited a flat trend in the thirty years preceding the conflict (1972 2002). The rainfall evidence suggests instead a break around 1971. Rainfall is basically stationary over the pre- and post-1971 sub-periods. The break is larger for the more northerly rainfall stations, and is less noticeable for En Nahud. Rainfall in Darfur did indeed decline, but the decline happened over 30 years before the conflict erupted. Preliminary analysis suggests little merit to the proposition that a structural break several decades earlier is a reasonable predictor of the outbreak of large-scale civil conflict in Africa.

Accounting for Rainfall Spatial Variability in Prediction of Flash Floods

NASA Astrophysics Data System (ADS)

Saharia, M.; Kirstetter, P. E.; Gourley, J. J.; Hong, Y.; Vergara, H. J.

2016-12-01

Flash floods are a particularly damaging natural hazard worldwide in terms of both fatalities and property damage. In the United States, the lack of a comprehensive database that catalogues information related to flash flood timing, location, causative rainfall, and basin geomorphology has hindered broad characterization studies. First a representative and long archive of more than 20,000 flooding events during 2002-2011 is used to analyze the spatial and temporal variability of flash floods. We also derive large number of spatially distributed geomorphological and climatological parameters such as basin area, mean annual precipitation, basin slope etc. to identify static basin characteristics that influence flood response. For the same period, the National Severe Storms Laboratory (NSSL) has produced a decadal archive of Multi-Radar/Multi-Sensor (MRMS) radar-only precipitation rates at 1-km spatial resolution with 5-min temporal resolution. This provides an unprecedented opportunity to analyze the impact of event-level precipitation variability on flooding using a big data approach. To analyze the impact of sub-basin scale rainfall spatial variability on flooding, certain indices such as the first and second scaled moment of rainfall, horizontal gap, vertical gap etc. are computed from the MRMS dataset. Finally, flooding characteristics such as rise time, lag time, and peak discharge are linked to derived geomorphologic, climatologic, and rainfall indices to identify basin characteristics that drive flash floods. Next the model is used to predict flash flooding characteristics all over the continental U.S., specifically over regions poorly covered by hydrological observations. So far studies involving rainfall variability indices have only been performed on a case study basis, and a large scale approach is expected to provide a deeper insight into how sub-basin scale precipitation variability affects flooding. Finally, these findings are validated using the National Weather Service storm reports and a historical flood fatalities database. This analysis framework will serve as a baseline for evaluating distributed hydrologic model simulations such as the Flooded Locations And Simulated Hydrographs Project (FLASH) (http://flash.ou.edu).

Accounting for rainfall spatial variability in the prediction of flash floods

NASA Astrophysics Data System (ADS)

Saharia, Manabendra; Kirstetter, Pierre-Emmanuel; Gourley, Jonathan J.; Hong, Yang; Vergara, Humberto; Flamig, Zachary L.

2017-04-01

Flash floods are a particularly damaging natural hazard worldwide in terms of both fatalities and property damage. In the United States, the lack of a comprehensive database that catalogues information related to flash flood timing, location, causative rainfall, and basin geomorphology has hindered broad characterization studies. First a representative and long archive of more than 15,000 flooding events during 2002-2011 is used to analyze the spatial and temporal variability of flash floods. We also derive large number of spatially distributed geomorphological and climatological parameters such as basin area, mean annual precipitation, basin slope etc. to identify static basin characteristics that influence flood response. For the same period, the National Severe Storms Laboratory (NSSL) has produced a decadal archive of Multi-Radar/Multi-Sensor (MRMS) radar-only precipitation rates at 1-km spatial resolution with 5-min temporal resolution. This provides an unprecedented opportunity to analyze the impact of event-level precipitation variability on flooding using a big data approach. To analyze the impact of sub-basin scale rainfall spatial variability on flooding, certain indices such as the first and second scaled moment of rainfall, horizontal gap, vertical gap etc. are computed from the MRMS dataset. Finally, flooding characteristics such as rise time, lag time, and peak discharge are linked to derived geomorphologic, climatologic, and rainfall indices to identify basin characteristics that drive flash floods. The database has been subjected to rigorous quality control by accounting for radar beam height and percentage snow in basins. So far studies involving rainfall variability indices have only been performed on a case study basis, and a large scale approach is expected to provide a deeper insight into how sub-basin scale precipitation variability affects flooding. Finally, these findings are validated using the National Weather Service storm reports and a historical flood fatalities database. This analysis framework will serve as a baseline for evaluating distributed hydrologic model simulations such as the Flooded Locations And Simulated Hydrographs Project (FLASH) (http://flash.ou.edu).

Annual Rainfall Maxima: Theoretical Estimation of the GEV Shape Parameter k Using Multifractal Models

NASA Astrophysics Data System (ADS)

Veneziano, D.; Langousis, A.; Lepore, C.

2009-12-01

The annual maximum of the average rainfall intensity in a period of duration d, Iyear(d), is typically assumed to have generalized extreme value (GEV) distribution. The shape parameter k of that distribution is especially difficult to estimate from either at-site or regional data, making it important to constraint k using theoretical arguments. In the context of multifractal representations of rainfall, we observe that standard theoretical estimates of k from extreme value (EV) and extreme excess (EE) theories do not apply, while estimates from large deviation (LD) theory hold only for very small d. We then propose a new theoretical estimator based on fitting GEV models to the numerically calculated distribution of Iyear(d). A standard result from EV and EE theories is that k depends on the tail behavior of the average rainfall in d, I(d). This result holds if Iyear(d) is the maximum of a sufficiently large number n of variables, all distributed like I(d); therefore its applicability hinges on whether n = 1yr/d is large enough and the tail of I(d) is sufficiently well known. One typically assumes that at least for small d the former condition is met, but poor knowledge of the upper tail of I(d) remains an obstacle for all d. In fact, in the case of multifractal rainfall, also the first condition is not met because, irrespective of d, 1yr/d is too small (Veneziano et al., 2009, WRR, in press). Applying large deviation (LD) theory to this multifractal case, we find that, as d → 0, Iyear(d) approaches a GEV distribution whose shape parameter kLD depends on a region of the distribution of I(d) well below the upper tail, is always positive (in the EV2 range), is much larger than the value predicted by EV and EE theories, and can be readily found from the scaling properties of I(d). The scaling properties of rainfall can be inferred also from short records, but the limitation remains that the result holds under d → 0 not for finite d. Therefore, for different reasons, none of the above asymptotic theories applies to Iyear(d). In practice, one is interested in the distribution of Iyear(d) over a finite range of averaging durations d and return periods T. Using multifractal representations of rainfall, we have numerically calculated the distribution of Iyear(d) and found that, although not GEV, the distribution can be accurately approximated by a GEV model. The best-fitting parameter k depends on d, but is insensitive to the scaling properties of rainfall and the range of return periods T used for fitting. We have obtained a default expression for k(d) and compared it with estimates from historical rainfall records. The theoretical function tracks well the empirical dependence on d, although it generally overestimates the empirical k values, possibly due to deviations of rainfall from perfect scaling. This issue is under investigation.

Use of Fuzzy rainfall-runoff predictions for claypan watersheds with conservation buffers in Northeast Missouri

NASA Astrophysics Data System (ADS)

Anomaa Senaviratne, G. M. M. M.; Udawatta, Ranjith P.; Anderson, Stephen H.; Baffaut, Claire; Thompson, Allen

2014-09-01

Fuzzy rainfall-runoff models are often used to forecast flood or water supply in large catchments and applications at small/field scale agricultural watersheds are limited. The study objectives were to develop, calibrate, and validate a fuzzy rainfall-runoff model using long-term data of three adjacent field scale row crop watersheds (1.65-4.44 ha) with intermittent discharge in the claypan soils of Northeast Missouri. The watersheds were monitored for a six-year calibration period starting 1991 (pre-buffer period). Thereafter, two of them were treated with upland contour grass and agroforestry (tree + grass) buffers (4.5 m wide, 36.5 m apart) to study water quality benefits. The fuzzy system was based on Mamdani method using MATLAB 7.10.0. The model predicted event-based runoff with model performance coefficients of r2 and Nash-Sutcliffe Coefficient (NSC) values greater than 0.65 for calibration and validation. The pre-buffer fuzzy system predicted event-based runoff for 30-50 times larger corn/soybean watersheds with r2 values of 0.82 and 0.68 and NSC values of 0.77 and 0.53, respectively. The runoff predicted by the fuzzy system closely agreed with values predicted by physically-based Agricultural Policy Environmental eXtender model (APEX) for the pre-buffer watersheds. The fuzzy rainfall-runoff model has the potential for runoff predictions at field-scale watersheds with minimum input. It also could up-scale the predictions for large-scale watersheds to evaluate the benefits of conservation practices.

Role of monsoon intraseasonal oscillation and its interannual variability in simulation of seasonal mean in CFSv2

NASA Astrophysics Data System (ADS)

Pillai, Prasanth A.; Aher, Vaishali R.

2018-01-01

Intraseasonal oscillation (ISO), which appears as "active" and "break" spells of rainfall, is an important component of Indian summer monsoon (ISM). The present study investigates the potential of new National Centre for Environmental Prediction (NCEP) climate forecast system version 2 (CFSv2) in simulating the ISO with emphasis to its interannual variability (IAV) and its possible role in the seasonal mean rainfall. The present analysis shows that the spatial distribution of CFSv2 rainfall has noticeable differences with observations in both ISO and IAV time scales. Active-break cycle of CFSv2 has similar evolution during both strong and weak years. Regardless of a reasonable El Niño Southern Oscillation (ENSO)-monsoon teleconnection in the model, the overestimated Arabian Sea (AS) sea surface temperature (SST)-convection relationship hinters the large-scale influence of ENSO over the ISM region and adjacent oceans. The ISO scale convections over AS and Bay of Bengal (BoB) have noteworthy contribution to the seasonal mean rainfall, opposing the influence of boundary forcing in these areas. At the same time, overwhelming contribution of ISO component over AS towards the seasonal mean modifies the effect of slow varying boundary forcing to large-scale summer monsoon. The results here underline that, along with the correct simulation of monsoon ISO, its IAV and relationship with the boundary forcing also need to be well captured in coupled models for the accurate simulation of seasonal mean anomalies of the monsoon and its teleconnections.

Lower Boundary Forcing related to the Occurrence of Rain in the Tropical Western Pacific

NASA Astrophysics Data System (ADS)

Li, Y.; Carbone, R. E.

2013-12-01

Global weather and climate models have a long and somewhat tortured history with respect to simulation and prediction of tropical rainfall in the relative absence of balanced flow in the geostrophic sense. An important correlate with tropical rainfall is sea surface temperature (SST). The introduction of SST information to convective rainfall parameterization in global models has improved model climatologies of tropical oceanic rainfall. Nevertheless, large systematic errors have persisted, several of which are common to most atmospheric models. Models have evolved to the point where increased spatial resolution demands representation of the SST field at compatible temporal and spatial scales, leading to common usage of monthly SST fields at scales of 10-100 km. While large systematic errors persist, significant skill has been realized from various atmospheric and coupled ocean models, including assimilation of weekly or even daily SST fields, as tested by the European Center for Medium Range Weather Forecasting. A few investigators have explored the role of SST gradients in relation to the occurrence of precipitation. Some of this research has focused on large scale gradients, mainly associated with surface ocean-atmosphere climatology. These studies conclude that lower boundary atmospheric convergence, under some conditions, could be substantially enhanced over SST gradients, destabilizing the atmosphere, and thereby enabling moist convection. While the concept has a firm theoretical foundation, it has not gained a sizeable following far beyond the realm of western boundary currents. Li and Carbone 2012 examined the role of transient mesoscale (~ 100 km) SST gradients in the western Pacific warm pool by means of GHRSST and CMORPH rainfall data. They found that excitation of deep moist convection was strongly associated with the Laplacian of SST (LSST). Specifically, -LSST is associated with rainfall onset in 75% of 10,000 events over 4 years, whereas the background ocean is symmetric about zero Laplacian. This finding is fully consistent with theory for gradients of order ~1degC in low mean wind conditions, capable of inducing atmospheric convergence of N x 10-5s-1. We will present new findings resulting from the application of a Madden-Julian oscillation (MJO) passband filter to GHRSST/CMORPH data. It shows that the -LSST field organizes at scales of 1000-2000 km and can persist for periods of two weeks to 3 months. Such -LSST anomalies are in quadrature with MJO rainfall, tracking and leading the wet phase of the MJO by 10-14 days, from the Indian Ocean to the dateline. More generally, an evaluation of SST structure in rainfall production will be presented, which represents a decidedly alternative view to conventional wisdom. Li, Yanping, and R.E. Carbone, 2012: Excitation of Rainfall over the Tropical Western Pacific, J. Atmos. Sci., 69, 2983-2994.

Simulating Daily and Sub-daily Water Flow in Large, Semi-arid Watershed Using SWAT: A Case Study of Nueces River Basin, Texas

NASA Astrophysics Data System (ADS)

Bassam, S.; Ren, J.

2015-12-01

Runoff generated during heavy rainfall imposes quick, but often intense, changes in the flow of streams, which increase the chance of flash floods in the vicinity of the streams. Understanding the temporal response of streams to heavy rainfall requires a hydrological model that considers meteorological, hydrological, and geological components of the streams and their watersheds. SWAT is a physically-based, semi-distributed model that is capable of simulating water flow within watersheds with both long-term, i.e. annually and monthly, and short-term (daily and sub-daily) time scales. However, the capability of SWAT in sub-daily water flow modeling within large watersheds has not been studied much, compare to long-term and daily time scales. In this study we are investigating the water flow in a large, semi-arid watershed, Nueces River Basin (NRB) with the drainage area of 16950 mi2 located in South Texas, with daily and sub-daily time scales. The objectives of this study are: (1) simulating the response of streams to heavy, and often quick, rainfall, (2) evaluating SWAT performance in sub-daily modeling of water flow within a large watershed, and (3) examining means for model performance improvement during model calibration and verification based on results of sensitivity and uncertainty analysis. The results of this study can provide important information for water resources planning during flood seasons.

Global Distribution of Extreme Precipitation and High-Impact Landslides in 2010 Relative to Previous Years

NASA Technical Reports Server (NTRS)

Kirschbaum, Dalia; Adler, Robert; Adler, David; Peters-Lidard, Christa; Huffman, George

2012-01-01

It is well known that extreme or prolonged rainfall is the dominant trigger of landslides worldwide. While research has evaluated the spatiotemporal distribution of extreme rainfall and landslides at local or regional scales using in situ data, few studies have mapped rainfall-triggered landslide distribution globally due to the dearth of landslide data and consistent precipitation information. This study uses a newly developed Global Landslide Catalog (GLC) and a 13-year satellite-based precipitation record from TRMM data. For the first time, these two unique products provide the foundation to quantitatively evaluate the co-occurrence of precipitation and landslides globally. Evaluation of the GLC indicates that 2010 had a large number of high-impact landslide events relative to previous years. This study considers how variations in extreme and prolonged satellite-based rainfall are related to the distribution of landslides over the same time scales for three active landslide areas: Central America, the Himalayan Arc, and central-eastern China. Several test statistics confirm that TRMM rainfall generally scales with the observed increase in landslide reports and fatal events for 2010 and previous years over each region. These findings suggest that the co-occurrence of satellite precipitation and landslide reports may serve as a valuable indicator for characterizing the spatiotemporal distribution of landslide-prone areas in order to establish a global rainfall-triggered landslide climatology. This study characterizes the variability of satellite precipitation data and reported landslide activity at the globally scale in order to improve landslide cataloging, forecasting and quantify potential triggering sources at daily, monthly and yearly time scales.

The Microphysical Structure of Extreme Precipitation as Inferred from Ground-Based Raindrop Spectra.

NASA Astrophysics Data System (ADS)

Uijlenhoet, Remko; Smith, James A.; Steiner, Matthias

2003-05-01

The controls on the variability of raindrop size distributions in extreme rainfall and the associated radar reflectivity-rain rate relationships are studied using a scaling-law formalism for the description of raindrop size distributions and their properties. This scaling-law formalism enables a separation of the effects of changes in the scale of the raindrop size distribution from those in its shape. Parameters controlling the scale and shape of the scaled raindrop size distribution may be related to the microphysical processes generating extreme rainfall. A global scaling analysis of raindrop size distributions corresponding to rain rates exceeding 100 mm h1, collected during the 1950s with the Illinois State Water Survey raindrop camera in Miami, Florida, reveals that extreme rain rates tend to be associated with conditions in which the variability of the raindrop size distribution is strongly number controlled (i.e., characteristic drop sizes are roughly constant). This means that changes in properties of raindrop size distributions in extreme rainfall are largely produced by varying raindrop concentrations. As a result, rainfall integral variables (such as radar reflectivity and rain rate) are roughly proportional to each other, which is consistent with the concept of the so-called equilibrium raindrop size distribution and has profound implications for radar measurement of extreme rainfall. A time series analysis for two contrasting extreme rainfall events supports the hypothesis that the variability of raindrop size distributions for extreme rain rates is strongly number controlled. However, this analysis also reveals that the actual shapes of the (measured and scaled) spectra may differ significantly from storm to storm. This implies that the exponents of power-law radar reflectivity-rain rate relationships may be similar, and close to unity, for different extreme rainfall events, but their prefactors may differ substantially. Consequently, there is no unique radar reflectivity-rain rate relationship for extreme rain rates, but the variability is essentially reduced to one free parameter (i.e., the prefactor). It is suggested that this free parameter may be estimated on the basis of differential reflectivity measurements in extreme rainfall.

Spatial and temporal variability in the R-5 infiltration data set: Déjà vu and rainfall-runoff simulations

NASA Astrophysics Data System (ADS)

Loague, Keith; Kyriakidis, Phaedon C.

1997-12-01

This paper is a continuation of the event-based rainfall-runoff model evaluation study reported by Loague and Freeze [1985[. Here we reevaluate the performance of a quasi-physically based rainfall-runoff model for three large events from the well-known R-5 catchment. Five different statistical criteria are used to quantitatively judge model performance. Temporal variability in the large R-5 infiltration data set [Loague and Gander, 1990] is filtered by working in terms of permeability. The transformed data set is reanalyzed via geostatistical methods to model the spatial distribution of permeability across the R-5 catchment. We present new estimates of the spatial distribution of infiltration that are in turn used in our rainfall-runoff simulations with the Horton rainfall-runoff model. The new rainfall-runoff simulations, complicated by reinfiltration impacts at the smaller scales of characterization, indicate that the near-surface hydrologic response of the R-5 catchment is most probably dominated by a combination of the Horton and Dunne overland flow mechanisms.

Influence of large-scale climate modes on dynamical complexity patterns of Indian Summer Monsoon rainfall

NASA Astrophysics Data System (ADS)

Papadimitriou, Constantinos; Donner, Reik V.; Stolbova, Veronika; Balasis, Georgios; Kurths, Jürgen

2015-04-01

Indian Summer monsoon is one of the most anticipated and important weather events with vast environmental, economical and social effects. Predictability of the Indian Summer Monsoon strength is crucial question for life and prosperity of the Indian population. In this study, we are attempting to uncover the relationship between the spatial complexity of Indian Summer Monsoon rainfall patterns, and the monsoon strength, in an effort to qualitatively determine how spatial organization of the rainfall patterns differs between strong and weak instances of the Indian Summer Monsoon. Here, we use observational satellite data from 1998 to 2012 from the Tropical Rainfall Measuring Mission (TRMM 3B42V7) and reanalysis gridded daily rainfall data for a time period of 57 years (1951-2007) (Asian Precipitation Highly Resolved Observational Data Integration Towards the Evaluation of Water Resources, APHRODITE). In order to capture different aspects of the system's dynamics, first, we convert rainfall time series to binary symbolic sequences, exploring various thresholding criteria. Second, we apply the Shannon entropy formulation (in a block-entropy sense) using different measures of normalization of the resulting entropy values. Finally, we examine the effect of various large-scale climate modes such as El-Niño-Southern Oscillation, North Atlantic Oscillation, and Indian Ocean Dipole, on the emerging complexity patterns, and discuss the possibility for the utilization of such pattern maps in the forecasting of the spatial variability and strength of the Indian Summer Monsoon.

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.

Relationships between Tropical Rainfall Events and Regional Annual Rainfall Anomalies

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

The assessment of Global Precipitation Measurement estimates over the Indian subcontinent

NASA Astrophysics Data System (ADS)

Murali Krishna, U. V.; Das, Subrata Kumar; Deshpande, Sachin M.; Doiphode, S. L.; Pandithurai, G.

2017-08-01

Accurate and real-time precipitation estimation is a challenging task for current and future spaceborne measurements, which is essential to understand the global hydrological cycle. Recently, the Global Precipitation Measurement (GPM) satellites were launched as a next-generation rainfall mission for observing the global precipitation characteristics. The purpose of the GPM is to enhance the spatiotemporal resolution of global precipitation. The main objective of the present study is to assess the rainfall products from the GPM, especially the Integrated Multi-satellitE Retrievals for the GPM (IMERG) data by comparing with the ground-based observations. The multitemporal scale evaluations of rainfall involving subdaily, diurnal, monthly, and seasonal scales were performed over the Indian subcontinent. The comparison shows that the IMERG performed better than the Tropical Rainfall Measuring Mission (TRMM)-3B42, although both rainfall products underestimated the observed rainfall compared to the ground-based measurements. The analyses also reveal that the TRMM-3B42 and IMERG data sets are able to represent the large-scale monsoon rainfall spatial features but are having region-specific biases. The IMERG shows significant improvement in low rainfall estimates compared to the TRMM-3B42 for selected regions. In the spatial distribution, the IMERG shows higher rain rates compared to the TRMM-3B42, due to its enhanced spatial and temporal resolutions. Apart from this, the characteristics of raindrop size distribution (DSD) obtained from the GPM mission dual-frequency precipitation radar is assessed over the complex mountain terrain site in the Western Ghats, India, using the DSD measured by a Joss-Waldvogel disdrometer.

Use of High-Resolution Satellite Observations to Evaluate Cloud and Precipitation Statistics from Cloud-Resolving Model Simulations

NASA Astrophysics Data System (ADS)

Zhou, Y.; Tao, W.; Hou, A. Y.; Zeng, X.; Shie, C.

2007-12-01

The cloud and precipitation statistics simulated by 3D Goddard Cumulus Ensemble (GCE) model for different environmental conditions, i.e., the South China Sea Monsoon Experiment (SCSMEX), CRYSTAL-FACE, and KAWJEX are compared with Tropical Rainfall Measuring Mission (TRMM) TMI and PR rainfall measurements and as well as cloud observations from the Earth's Radiant Energy System (CERES) and the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments. It is found that GCE is capable of simulating major convective system development and reproducing total surface rainfall amount as compared with rainfall estimated from the soundings. The model presents large discrepancies in rain spectrum and vertical hydrometer profiles. The discrepancy in the precipitation field is also consistent with the cloud and radiation observations. The study will focus on the effects of large scale forcing and microphysics to the simulated model- observation discrepancies.

Diagnosing the Atmospheric/Oceanic Phenomena Associated with the Onset, Demise and Mid-Summer Drought of the Rainy Season in Mesoamerica

NASA Astrophysics Data System (ADS)

Groenen, D.; Bourassa, M. A.

2017-12-01

The rainfall in Mesoamerica (Mexico and Central America) has influences from two bodies of water, interesting topography, and complex wind patterns, which complicates weather forecasting. Knowing the approximate onset and demise of the rainy season is critical for the optimal growth and development of key crops in this region such as coffee, bananas, rice, and maize. This study compares three methods to calculate the onset/demise dates of the individual years' rainy season, using area-averaged rainfall data (7-28 °N/77-109 °W) from two datasets. After these onset/demise dates are obtained using rainfall data, the atmospheric and oceanic phenomena associated with the timing is analyzed using MERRA-2 reanalysis data. The objective is to link the large-scale phenomena to the individual years' onset/demise dates, as well as link the weather phenomena to the interannual variability of the onset/demise dates. In addition, the broad scale rainy season will be connected with regional onset/demise dates on the scale of 400km. Linking the broad scale rainfall regimes to the regional regimes will allow a more cohesive view of the dynamics related to rainfall variability in the Mesoamerican region. A smoothing method will be used to analyze the timing and intensity of the mid-summer drought (MSD), a minimum in rainfall typically occurring during July and August. The goal of this research is to link the physical and dynamical mechanisms that cause the Mesoamerican rainy season and mid-summer drought (MSD) in order to better understand the predictability of Mesoamerican rainfall and ensure the health and safety of key crops.

Variability in rainfall over tropical Australia during summer and relationships with the Bilybara High

NASA Astrophysics Data System (ADS)

Reason, C. J. C.

2018-04-01

Variability in summer rainfall over tropical Australia, defined here as that part of the continent north of 25° S, and its linkages with regional circulation are examined. In particular, relationships with the mid-level anticyclone (termed the Bilybara High) that exists over the northwestern Australia/Timor Sea region between August and April are considered. This High forms to the southwest of the upper-level anticyclone via a balance between the upper-level divergence over the region of tropical precipitation maximum and planetary vorticity advection and moves south and strengthens during the spring and summer. It is shown that variations in the strength and position of the Bilybara High are related to anomalies in precipitation and temperature over large parts of tropical Australia as well as some areas in the south and southeast of the landmass. Some of the interannual variations in the High are related to ENSO, but there are also a number of neutral years with large anomalies in the High and hence in rainfall. On decadal time scales, a strong relationship exists between the leading mode of tropical Australian rainfall and the Bilybara High. On both interannual and decadal scales, the relationships between the High and the regional rainfall involve changes in the monsoonal northwesterlies blowing towards northern Australia, and further south, in the easterly trade winds over the region.

Goddard Cumulus Ensemble (GCE) Model: Application for Understanding Preciptation Processes

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Einaudi, Franco (Technical Monitor)

2000-01-01

The global hydrological cycle is central to climate system interactions and the key to understanding their behavior. Rainfall and its associated precipitation processes are a key link in the hydrologic cycle. Fresh water provided by tropical rainfall and its variability can exert a large impact upon the structure of the upper ocean layer. In addition, approximately two-thirds of the global rain falls in the Tropics, while the associated latent heat release accounts for about three-fourths of the total heat energy for the Earth's atmosphere. Precipitation from convective cloud systems comprises a large portion of tropical heating and rainfall. Furthermore, the vertical distribution of convective latent-heat releases modulates large-scale tropical circulations (e.g., the 30-60-day intraseasonal oscillation), which, in turn, impacts midlatitude weather through teleconnection patterns such as those associated with El Nino. Shifts in these global circulations can result in prolonged periods of droughts and floods, thereby exerting a tremendous impact upon the biosphere and human habitation. And yet, monthly rainfall over the tropical oceans is still not known within a factor of two over large (5 degrees latitude by 5 degrees longitude) areas. Hence, the Tropical Rainfall Measuring Mission (TRMM), a joint U.S./Japan space project, can provide a more accurate measurement of rainfall as well as estimate the four-dimensional structure of diabatic heating over the global tropics. The distributions of rainfall and inferred heating can be used to advance our understanding of the global energy and water cycle. In addition, this information can be used for global circulation and climate models for testing and improving their parameterizations.

Tree-Ring Reconstruction of Wet Season Rainfall Totals in the Amazon

NASA Astrophysics Data System (ADS)

Stahle, D. W.; Lopez, L.; Granato-Souza, D.; Barbosa, A. C. M. C.; Torbenson, M.; Villalba, R.; Pereira, G. D. A.; Feng, S.; Schongart, J.; Cook, E. R.

2017-12-01

The Amazon Basin is a globally important center of deep atmospheric convection, energy balance, and biodiversity, but only a handful of weather stations in this vast Basin have recorded rainfall measurements for at least 50 years. The available rainfall and river level observations suggest that the hydrologic cycle in the Amazon may have become amplified in the last 40-years, with more extreme rainfall and streamflow seasonality, deeper droughts, and more severe flooding. These changes in the largest hydrological system on earth may be early evidence of the expected consequences of anthropogenic climate change and deforestation in the coming century. Placing these observed and simulated changes in the context of natural climate variability during the late Holocene is a significant challenge for high-resolution paleoclimatology. We have developed exactly dated and well-replicated annual tree-ring chronologies from two native Amazonian tree species (Cedrela sp and Centrolobium microchaete). These moisture sensitive chronologies have been used to compute two reconstructions of wet season rainfall totals, one in the southern Amazon based on Centrolobium and another in the eastern equatorial Amazon using Cedrela. Both reconstructions are over 200-years long and extend the available instrumental observations in each region by over 150-years. These reconstructions are well correlated with the same regional and large-scale climate dynamics that govern the inter-annual variability of the instrumental wet season rainfall totals. Increased multi-decadal variability is reconstructed after 1950 with the Centrolobium chronologies in the southern Amazon. The Cedrela reconstruction from the eastern Amazon exhibits changes in the spatial pattern of correlation with regional rainfall stations and the large-scale sea surface temperature field after 1990 that may be consistent with recent changes in the mean position of the Inter-Tropical Convergence Zone in March over the western Atlantic and South American sector.

Convective Systems over the South China Sea: Cloud-Resolving Model Simulations.

NASA Astrophysics Data System (ADS)

Tao, W.-K.; Shie, C.-L.; Simpson, J.; Braun, S.; Johnson, R. H.; Ciesielski, P. E.

2003-12-01

The two-dimensional version of the Goddard Cumulus Ensemble (GCE) model is used to simulate two South China Sea Monsoon Experiment (SCSMEX) convective periods [18 26 May (prior to and during the monsoon onset) and 2 11 June (after the onset of the monsoon) 1998]. Observed large-scale advective tendencies for potential temperature, water vapor mixing ratio, and horizontal momentum are used as the main forcing in governing the GCE model in a semiprognostic manner. The June SCSMEX case has stronger forcing in both temperature and water vapor, stronger low-level vertical shear of the horizontal wind, and larger convective available potential energy (CAPE).The temporal variation of the model-simulated rainfall, time- and domain-averaged heating, and moisture budgets compares well to those diagnostically determined from soundings. However, the model results have a higher temporal variability. The model underestimates the rainfall by 17% to 20% compared to that based on soundings. The GCE model-simulated rainfall for June is in very good agreement with the Tropical Rainfall Measuring Mission (TRMM), precipitation radar (PR), and the Global Precipitation Climatology Project (GPCP). Overall, the model agrees better with observations for the June case rather than the May case.The model-simulated energy budgets indicate that the two largest terms for both cases are net condensation (heating/drying) and imposed large-scale forcing (cooling/moistening). These two terms are opposite in sign, however. The model results also show that there are more latent heat fluxes for the May case. However, more rainfall is simulated for the June case. Net radiation (solar heating and longwave cooling) are about 34% and 25%, respectively, of the net condensation (condensation minus evaporation) for the May and June cases. Sensible heat fluxes do not contribute to rainfall in either of the SCSMEX cases. Two types of organized convective systems, unicell (May case) and multicell (June case), are simulated by the model. They are determined by the observed mean U wind shear (unidirectional versus reverse shear profiles above midlevels).Several sensitivity tests are performed to examine the impact of the radiation, microphysics, and large-scale mean horizontal wind on the organization and intensity of the SCSMEX convective systems.

Vegetation-rainfall feedbacks across the Sahel: a combined observational and modeling study

NASA Astrophysics Data System (ADS)

Yu, Y.; Notaro, M.; Wang, F.; Mao, J.; Shi, X.; Wei, Y.

2016-12-01

The Sahel rainfall is characterized by large interannual variability. Past modeling studies have concluded that the Sahel rainfall variability is primarily driven by oceanic forcings and amplified by land-atmosphere interactions. However, the relative importance of oceanic versus terrestrial drivers has never been assessed from observations. The current understanding of vegetation's impacts on climate, i.e. positive vegetation-rainfall feedback through the albedo, moisture, and momentum mechanisms, comes from untested models. Neither the positive vegetation-rainfall feedback, nor the underlying mechanisms, has been fully resolved in observations. The current study fills the knowledge gap about the observed vegetation-rainfall feedbacks, through the application of the multivariate statistical method Generalized Equilibrium Feedback Assessment (GEFA) to observational data. According to GEFA, the observed oceanic impacts dominate over terrestrial impacts on Sahel rainfall, except in the post-monsoon period. Positive leaf area index (LAI) anomalies favor an extended, wetter monsoon across the Sahel, largely due to moisture recycling. The albedo mechanism is not responsible for this positive vegetation feedback on the seasonal-interannual time scale, which is too short for a grass-desert transition. A low-level stabilization and subsidence is observed in response to increased LAI - potentially responsible for a negative vegetation-rainfall feedback. However, the positive moisture feedback overwhelms the negative momentum feedback, resulting in an observed positive vegetation-rainfall feedback. We further applied GEFA to a fully-coupled Community Earth System Model (CESM) control run, as an example of evaluating climate models against the GEFA-based observational benchmark. In contrast to the observed positive vegetation-rainfall feedbacks, CESM simulates a negative vegetation-rainfall feedback across Sahel, peaking in the pre-monsoon season. The simulated negative feedback is largely due to the low-level stabilization caused by increased LAI. Positive moisture feedback is present in the CESM simulation, but an order weaker than the observed and weaker than the negative momentum feedback, thereby leading to the simulated negative vegetation-rainfall feedbacks.

Rainfall recharge estimation on a nation-wide scale using satellite information in New Zealand

NASA Astrophysics Data System (ADS)

Westerhoff, Rogier; White, Paul; Moore, Catherine

2015-04-01

Models of rainfall recharge to groundwater are challenged by the need to combine uncertain estimates of rainfall, evapotranspiration, terrain slope, and unsaturated zone parameters (e.g., soil drainage and hydraulic conductivity of the subsurface). Therefore, rainfall recharge is easiest to estimate on a local scale in well-drained plains, where it is known that rainfall directly recharges groundwater. In New Zealand, this simplified approach works in the policy framework of regional councils, who manage water allocation at the aquifer and sub-catchment scales. However, a consistent overview of rainfall recharge is difficult to obtain at catchment and national scale: in addition to data uncertainties, data formats are inconsistent between catchments; the density of ground observations, where these exist, differs across regions; each region typically uses different local models for estimating recharge components; and different methods and ground observations are used for calibration and validation of these models. The research described in this paper therefore presents a nation-wide approach to estimate rainfall recharge in New Zealand. The method used is a soil water balance approach, with input data from national rainfall and soil and geology databases. Satellite data (i.e., evapotranspiration, soil moisture, and terrain) aid in the improved calculation of rainfall recharge, especially in data-sparse areas. A first version of the model has been implemented on a 1 km x 1 km and monthly scale between 2000 and 2013. A further version will include a quantification of recharge estimate uncertainty: with both "top down" input error propagation methods and catchment-wide "bottom up" assessments of integrated uncertainty being adopted. Using one nation-wide methodology opens up new possibilities: it can, for example, help in more consistent estimation of water budgets, groundwater fluxes, or other hydrological parameters. Since recharge is estimated for the entire land surface, and not only the known aquifers, the model also identifies other zones that could potentially recharge aquifers, including large areas (e.g., mountains) that are currently regarded as impervious. The resulting rainfall recharge data have also been downscaled in a 200 m x 200 m calculation of a national monthly water table. This will lead to better estimation of hydraulic conductivity, which holds considerable potential for further research in unconfined aquifers in New Zealand.

Effects of ocean-atmosphere coupling on rainfall over the Indian Ocean and northwestern Pacific Ocean during boreal summer

NASA Astrophysics Data System (ADS)

Zhou, Z. Q.; Xie, S. P.; Zhou, W.

2016-12-01

Atmosphere general circulation model (AGCM), forced with specified SST, has been widely used in climate studies. On one hand, AGCM is much faster to run compared to coupled general circulation model (CGCM). Also, the identical SST forcing allows a clean evaluation of the atmospheric component of CGCM. On the other hand, the coupling between atmosphere and ocean is missed in such atmosphere-only simulations. It is not clear how such simplification could affect the simulate of the atmosphere. In this study, the impact of ocean-atmosphere coupling is studied by comparing a CGCM simulation with an AGCM simulation which is forced with monthly SSTs specified from the CGCM simulation. Particularly, we focus on the climatology and interannual variability of rainfall over the IONWP during boreal summer. The IONWP is a unique region with a strong negative correlation between sea surface temperature (SST) and rainfall during boreal summer on the interannual time scale. The lead/lag correlation analysis suggests a negative feedback of rainfall on SST, which is only reasonably captured by CGCMs. We find that the lack of the negative feedback in AGCM not only enhances the climatology and interannual variability of rainfall but also increases the internal variability of rainfall over the IONWP. A simple mechanism is proposed to explain such enhancement. In addition, AGCM is able to capture the large-scale rainfall pattern over the IONWP during boreal summer, this is because that rainfall here is caused by remote ENSO effect on the interannual time scale. Our results herein suggest that people should be more careful when using an AGCM for climate change studies.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Radar-rain-gauge rainfall estimation for hydrological applications in small catchments

NASA Astrophysics Data System (ADS)

Gabriele, Salvatore; Chiaravalloti, Francesco; Procopio, Antonio

2017-07-01

The accurate evaluation of the precipitation's time-spatial structure is a critical step for rainfall-runoff modelling. Particularly for small catchments, the variability of rainfall can lead to mismatched results. Large errors in flow evaluation may occur during convective storms, responsible for most of the flash floods in small catchments in the Mediterranean area. During such events, we may expect large spatial and temporal variability. Therefore, using rain-gauge measurements only can be insufficient in order to adequately depict extreme rainfall events. In this work, a double-level information approach, based on rain gauges and weather radar measurements, is used to improve areal rainfall estimations for hydrological applications. In order to highlight the effect that precipitation fields with different level of spatial details have on hydrological modelling, two kinds of spatial rainfall fields were computed for precipitation data collected during 2015, considering both rain gauges only and their merging with radar information. The differences produced by these two precipitation fields in the computation of the areal mean rainfall accumulation were evaluated considering 999 basins of the region Calabria, southern Italy. Moreover, both of the two precipitation fields were used to carry out rainfall-runoff simulations at catchment scale for main precipitation events that occurred during 2015 and the differences between the scenarios obtained in the two cases were analysed. A representative case study is presented in detail.

Large-scale rainfall diversity for ACTS

NASA Technical Reports Server (NTRS)

Lin, H. P.; Vogel, Wolfhard J.

1993-01-01

From the NOAA 15 minute precipitation file for the US, data were selected for a set of 23 stations spanning a 5 year period. The selection covers the spot beam locations for ACTS and the propagation experiment sites. There is a 2 percent probability of having any simultaneous rain at 3 or more stations, but this reduces to less than 0.001 percent at a rainfall rate of 40 mm/hr.

Dependence of winter precipitation over Portugal on NAO and baroclinic wave activity

NASA Astrophysics Data System (ADS)

Ulbrich, U.; Christoph, M.; Pinto, J. G.; Corte-Real, J.

1999-03-01

The relationship between winter (DJF) rainfall over Portugal and the variable large scale circulation is addressed. It is shown that the poles of the sea level pressure (SLP) field variability associated with rainfall variability are shifted about 15° northward with respect to those used in standard definitions of the North Atlantic Oscillation (NAO). It is suggested that the influence of NAO on rainfall dominantly arises from the associated advection of humidity from the Atlantic Ocean. Rainfall is also related to different aspects of baroclinic wave activity, the variability of the latter quantity in turn being largely dependent on the NAO.A negative NAO index (leading to increased westerly surface geostrophic winds into Portugal) is associated with an increased number of deep (ps<980 hPa) surface lows over the central North Atlantic and of intermediate (980

Radar-based Quantitative Precipitation Forecasting using Spatial-scale Decomposition Method for Urban Flood Management

NASA Astrophysics Data System (ADS)

Yoon, S.; Lee, B.; Nakakita, E.; Lee, G.

2016-12-01

Recent climate changes and abnormal weather phenomena have resulted in increased occurrences of localized torrential rainfall. Urban areas in Korea have suffered from localized heavy rainfall, including the notable Seoul flood disaster in 2010 and 2011. The urban hydrological environment has changed in relation to precipitation, such as reduced concentration time, a decreased storage rate, and increased peak discharge. These changes have altered and accelerated the severity of damage to urban areas. In order to prevent such urban flash flood damages, we have to secure the lead time for evacuation through the improvement of radar-based quantitative precipitation forecasting (QPF). The purpose of this research is to improve the QPF products using spatial-scale decomposition method for considering the life time of storm and to assess the accuracy between traditional QPF method and proposed method in terms of urban flood management. The layout of this research is as below. First, this research applies the image filtering to separate the spatial-scale of rainfall field. Second, the separated small and large-scale rainfall fields are extrapolated by each different forecasting method. Third, forecasted rainfall fields are combined at each lead time. Finally, results of this method are evaluated and compared with the results of uniform advection model for urban flood modeling. It is expected that urban flood information using improved QPF will help to reduce casualties and property damage caused by urban flooding through this research.

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

NASA Astrophysics Data System (ADS)

Peng, Yu; Wang, Qinghui; Fan, Min

2017-11-01

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

Changing circulation structure and precipitation characteristics in Asian monsoon regions: greenhouse warming vs. aerosol effects

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

Lau, William K. M.; Kim, Kyu-Myong; Ruby Leung, L.

Using model outputs from CMIP5 historical integrations, we have investigated the relative roles of anthropogenic emissions of greenhouse gases (GHG) and aerosols in changing the characteristics of the large-scale circulation and rainfall in Asian summer monsoon (ASM) regions. Under GHG warming, a strong positive trend in low-level moist static energy (MSE) is found over ASM regions, associated with increasing large-scale land–sea thermal contrast from 1870s to present. During the same period, a mid-tropospheric convective barrier (MCB) due to widespread reduction in relative humidity in the mid- and lower troposphere is strengthening over the ASM regions, in conjunction with expanding areasmore » of anomalous subsidence associated with the Deep Tropical Squeeze (Lau and Kim in Proc Natl Acad Sci 12:3630–3635, 2015). The opposing effects of MSE and MCB lead to enhanced total ASM rainfall, but only a partial strengthening of the southern portion of the monsoon meridional circulation, coupled to anomalous multi-cellular overturning motions over ASM land. Including anthropogenic aerosol emissions strongly masks MSE but enhances MCB via increased stability in the lower troposphere, resulting in an overall weakened ASM circulation with suppressed rainfall. Analyses of rainfall characteristics indicate that under GHG, overall precipitation efficiency over the ASM region is reduced, manifesting in less moderate but more extreme heavy rain events. Under combined effects of GHG and aerosols, precipitation efficiency is unchanged, with more moderate, but less extreme rainfall.« less

Changing circulation structure and precipitation characteristics in Asian monsoon regions: greenhouse warming vs. aerosol effects

NASA Astrophysics Data System (ADS)

Lau, William K. M.; Kim, Kyu-Myong; Ruby Leung, L.

2017-12-01

Using model outputs from CMIP5 historical integrations, we have investigated the relative roles of anthropogenic emissions of greenhouse gases (GHG) and aerosols in changing the characteristics of the large-scale circulation and rainfall in Asian summer monsoon (ASM) regions. Under GHG warming, a strong positive trend in low-level moist static energy (MSE) is found over ASM regions, associated with increasing large-scale land-sea thermal contrast from 1870s to present. During the same period, a mid-tropospheric convective barrier (MCB) due to widespread reduction in relative humidity in the mid- and lower troposphere is strengthening over the ASM regions, in conjunction with expanding areas of anomalous subsidence associated with the Deep Tropical Squeeze (Lau and Kim in Proc Natl Acad Sci 12:3630-3635, 2015). The opposing effects of MSE and MCB lead to enhanced total ASM rainfall, but only a partial strengthening of the southern portion of the monsoon meridional circulation, coupled to anomalous multi-cellular overturning motions over ASM land. Including anthropogenic aerosol emissions strongly masks MSE but enhances MCB via increased stability in the lower troposphere, resulting in an overall weakened ASM circulation with suppressed rainfall. Analyses of rainfall characteristics indicate that under GHG, overall precipitation efficiency over the ASM region is reduced, manifesting in less moderate but more extreme heavy rain events. Under combined effects of GHG and aerosols, precipitation efficiency is unchanged, with more moderate, but less extreme rainfall.

Scale-dependency of effective hydraulic conductivity on fire-affected hillslopes

NASA Astrophysics Data System (ADS)

Langhans, Christoph; Lane, Patrick N. J.; Nyman, Petter; Noske, Philip J.; Cawson, Jane G.; Oono, Akiko; Sheridan, Gary J.

2016-07-01

Effective hydraulic conductivity (Ke) for Hortonian overland flow modeling has been defined as a function of rainfall intensity and runon infiltration assuming a distribution of saturated hydraulic conductivities (Ks). But surface boundary condition during infiltration and its interactions with the distribution of Ks are not well represented in models. As a result, the mean value of the Ks distribution (KS¯), which is the central parameter for Ke, varies between scales. Here we quantify this discrepancy with a large infiltration data set comprising four different methods and scales from fire-affected hillslopes in SE Australia using a relatively simple yet widely used conceptual model of Ke. Ponded disk (0.002 m2) and ring infiltrometers (0.07 m2) were used at the small scales and rainfall simulations (3 m2) and small catchments (ca 3000 m2) at the larger scales. We compared KS¯ between methods measured at the same time and place. Disk and ring infiltrometer measurements had on average 4.8 times higher values of KS¯ than rainfall simulations and catchment-scale estimates. Furthermore, the distribution of Ks was not clearly log-normal and scale-independent, as supposed in the conceptual model. In our interpretation, water repellency and preferential flow paths increase the variance of the measured distribution of Ks and bias ponding toward areas of very low Ks during rainfall simulations and small catchment runoff events while areas with high preferential flow capacity remain water supply-limited more than the conceptual model of Ke predicts. The study highlights problems in the current theory of scaling runoff generation.

Stable isotope and noble gas constraints on the source and residence time of spring water from the Table Mountain Group Aquifer, Paarl, South Africa and implications for large scale abstraction

NASA Astrophysics Data System (ADS)

Miller, J. A.; Dunford, A. J.; Swana, K. A.; Palcsu, L.; Butler, M.; Clarke, C. E.

2017-08-01

Large scale groundwater abstraction is increasingly being used to support large urban centres especially in areas of low rainfall but presents particular challenges in the management and sustainability of the groundwater system. The Table Mountain Group (TMG) Aquifer is one of the largest and most important aquifer systems in South Africa and is currently being considered as an alternative source of potable water for the City of Cape Town, a metropolis of over four million people. The TMG aquifer is a fractured rock aquifer hosted primarily in super mature sandstones, quartzites and quartz arenites. The groundwater naturally emanates from numerous springs throughout the cape region. One set of springs were examined to assess the source and residence time of the spring water. Oxygen and hydrogen isotopes indicate that the spring water has not been subject to evaporation and in combination with Na/Cl ratios implies that recharge to the spring systems is via coastal precipitation. Although rainfall in the Cape is usually modelled on orographic rainfall, δ18O and δ2H values of some rainfall samples are strongly positive indicating a stratiform component as well. Comparing the spring water δ18O and δ2H values with that of local rainfall, indicates that the springs are likely derived from continuous bulk recharge over the immediate hinterland to the springs and not through large and/or heavy downpours. Noble gas concentrations, combined with tritium and radiocarbon activities indicate that the residence time of the TMG groundwater in this area is decadal in age with a probable maximum upper limit of ∼40 years. This residence time is probably a reflection of the slow flow rate through the fractured rock aquifer and hence indicates that the interconnectedness of the fractures is the most important factor controlling groundwater flow. The short residence time of the groundwater suggest that recharge to the springs and the Table Mountain Group Aquifer as a whole is vulnerable to climate change and reductions in regional precipitation. Any plans for large scale abstraction to supplement the City of Cape Town water supply would need to factor this into models of maximum sustainable yield.

Impact of landslides induced by 2014 northeast monsoon extreme rain in Malaysia

NASA Astrophysics Data System (ADS)

Fukuoka, Hiroshi; Koay, Swee Peng; Sakai, Naoki; Lateh, Habibah

2016-04-01

In December 2014, northeast monsoon brought extreme rainfalls to Malaysia, mainly in the eastern coast of Peninsular Malaysia and coastal area in Sabah and Sarawak. In this month, many of the rain gauge records in this area exceeded 1,000 mm, which is about 1/3 of average annual rainfall precipitation (2,850mm/year) in Malaysia. This unexpected heavy rainfall induced landslides and floods which brought about large-scale losses in Malaysia equivalent to several hundred million USD as thousands of residents had evacuated from hometown for months, and factories, schools and business activities were shut down for weeks. Among the major infrastructure of the nation, East-west Highway was subjected to damages by 21 landslides. Two large-scale landslides cut off the highway for a week. Authors had installed landslide monitoring instruments at reactivated landslide sites along the highway at N05° 36.042' E101° 35.546'. Records by in-situ inclinometers showed clear deformation from 17th December to 26th December, associated with certain change in piezometeres record for groundwater level monitoring. Several cracks occurred in the slope.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Analyzing energy-water exchange dynamics in the Thar desert

NASA Astrophysics Data System (ADS)

Raja, P.; Singh, Nilendu; Srinivas, C. V.; Singhal, Mohit; Chauhan, Pankaj; Singh, Maharaj; Sinha, N. K.

2017-07-01

Regions of strong land-atmosphere coupling will be more susceptible to the hydrological impacts in the intensifying hydrological cycle. In this study, micrometeorological experiments were performed to examine the land-atmosphere coupling strength over a heat low region (Thar desert, NW India), known to influence the Indian summer monsoon (ISM). Within the vortex of Thar desert heat low, energy-water exchange and coupling behavior were studied for 4 consecutive years (2011-2014) based on sub-hourly measurements of radiative-convective flux, state parameters and sub-surface thermal profiles using lead-lag analysis between various E-W balance components. Results indicated a strong (0.11-0.35) but variable monsoon season (July-September) land-atmosphere coupling events. Coupling strength declined with time, becomes negative beyond 10-day lag. Evapotranspiration (LE) influences rainfall at the monthly time-scale (20-40 days). Highly correlated monthly rainfall and LE anomalies (r = 0.55, P < 0.001) suggested a large precipitation memory linked to the local land surface state. Sensible heating (SH) during March and April are more strongly (r = 0.6-0.7) correlated to ISM rainfall than heating during May or June (r = 0.16-0.36). Analyses show strong and weak couplings among net radiation (Rn)-vapour pressure deficit (VPD), LE-VPD and Rn-LE switching between energy-limited to water-limited conditions. Consistently, +ve and -ve residual energy [(dE) = (Rn - G) - (SH + LE)] were associated with regional wet and dry spells respectively with a lead of 10-40 days. Dew deposition (18.8-37.9 mm) was found an important component in the annual surface water balance. Strong association of variation of LE and rainfall was found during monsoon at local-scale and with regional-scale LE (MERRA 2D) but with a lag which was more prominent at local-scale than at regional-scale. Higher pre-monsoon LE at local-scale as compared to low and monotonous variation in regional-scale LE led to hypothesize that excess energy and water vapour brought through advection caused by pre-monsoon rainfall might have been recycled through rainfall to compensate for early part of monsoon rainfall at local-scale. However, long-term measurements and isotope analysis would be able to strengthen this hypothesis. This study would fill the key gaps in the global flux studies and improve understanding on local E-W exchange pathways, responses and feedbacks.

HYDROSCAPE: A SCAlable and ParallelizablE Rainfall Runoff Model for Hydrological Applications

NASA Astrophysics Data System (ADS)

Piccolroaz, S.; Di Lazzaro, M.; Zarlenga, A.; Majone, B.; Bellin, A.; Fiori, A.

2015-12-01

In this work we present HYDROSCAPE, an innovative streamflow routing method based on the travel time approach, and modeled through a fine-scale geomorphological description of hydrological flow paths. The model is designed aimed at being easily coupled with weather forecast or climate models providing the hydrological forcing, and at the same time preserving the geomorphological dispersion of the river network, which is kept unchanged independently on the grid size of rainfall input. This makes HYDROSCAPE particularly suitable for multi-scale applications, ranging from medium size catchments up to the continental scale, and to investigate the effects of extreme rainfall events that require an accurate description of basin response timing. Key feature of the model is its computational efficiency, which allows performing a large number of simulations for sensitivity/uncertainty analyses in a Monte Carlo framework. Further, the model is highly parsimonious, involving the calibration of only three parameters: one defining the residence time of hillslope response, one for channel velocity, and a multiplicative factor accounting for uncertainties in the identification of the potential maximum soil moisture retention in the SCS-CN method. HYDROSCAPE is designed with a simple and flexible modular structure, which makes it particularly prone to massive parallelization, customization according to the specific user needs and preferences (e.g., rainfall-runoff model), and continuous development and improvement. Finally, the possibility to specify the desired computational time step and evaluate streamflow at any location in the domain, makes HYDROSCAPE an attractive tool for many hydrological applications, and a valuable alternative to more complex and highly parametrized large scale hydrological models. Together with model development and features, we present an application to the Upper Tiber River basin (Italy), providing a practical example of model performance and characteristics.

A Global-Scale Examination of Monsoon-Related Precipitation.

NASA Astrophysics Data System (ADS)

Janowiak, John E.; Xie, Pingping

2003-12-01

A pentad version of the Global Precipitation Climatology Project global precipitation dataset is used to document the annual and interannual variations in precipitation over monsoon regions around the globe. An algorithm is described that determines objectively wet season onset and withdrawal for individual years, and this tool is used to examine the behavior of various characteristics of the major monsoon systems. The definition of onset and withdrawal are determined by examining the ramp-up and diminution of rainfall within the context of the climatological rainfall at each location. Also examined are interannual variations in onset and withdrawal and their relationship to rainy season precipitation accumulations. Changes in the distribution of “heavy” and “light” precipitation events are examined for years in which “abundant” and “poor” wet seasons are observed, and associations with variations in large-scale atmospheric general circulation features are also examined. In particular, some regions of the world have strong associations between wet season rainfall and global-scale patterns of 200-hPa streamfunction anomalies.

Disparity in rainfall trend and patterns among different regions: analysis of 158 years' time series of rainfall dataset across India

NASA Astrophysics Data System (ADS)

Saha, Saurav; Chakraborty, Debasish; Paul, Ranjit Kumar; Samanta, Sandipan; Singh, S. B.

2017-10-01

Rainfall anomaly during crop-growing season can have large impact on the agricultural output of a country, especially like India, where two-thirds of the crop land is rain-fed. In such situation, decreased agricultural production not only challenges food security of the country but directly and immediately hits the livelihood of its farming community. In a vast country like India, rainfall or its anomalies hardly follow a specific pattern, rather it is having high variability in spatial domain. This study focused on the trends of national and regional rainfall anomalies (wetness/dryness) along with their interrelationship using time series data of past 158 years. The significant reducing wetness trend (p < 0.05) over north mountainous India was prominent with an increasing trend over southern peninsular India (p < 0.10). However, long-term annual wetness was increasing over entire peninsular India. The results of change point tests indicate that major abrupt changes occurred between early to mid-twentieth century having regional variations. The regional interrelationship was studied using principal component, hierarchical clustering, and pair-wise difference test, which clearly indicated a significantly different pattern in rainfall anomalies for north east India (p = 0.022), north central India (p = 0.022), and north mountainous India (p = 0.011) from that of the all India. Result of this study affirmed high spatial variability in rainfall anomaly and most importantly established the unalike pattern in trends of regional rainfall vis-à-vis national level, ushering towards paradigm shift in rainfall forecast from country scale to regional scale for pragmatic planning.

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

PubMed Central

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

2016-01-01

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

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

PubMed

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

2016-01-01

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

Spatial connections in regional climate model rainfall outputs at different temporal scales: Application of network theory

NASA Astrophysics Data System (ADS)

Naufan, Ihsan; Sivakumar, Bellie; Woldemeskel, Fitsum M.; Raghavan, Srivatsan V.; Vu, Minh Tue; Liong, Shie-Yui

2018-01-01

Understanding the spatial and temporal variability of rainfall has always been a great challenge, and the impacts of climate change further complicate this issue. The present study employs the concepts of complex networks to study the spatial connections in rainfall, with emphasis on climate change and rainfall scaling. Rainfall outputs (during 1961-1990) from a regional climate model (i.e. Weather Research and Forecasting (WRF) model that downscaled the European Centre for Medium-range Weather Forecasts, ECMWF ERA-40 reanalyses) over Southeast Asia are studied, and data corresponding to eight different temporal scales (6-hr, 12-hr, daily, 2-day, 4-day, weekly, biweekly, and monthly) are analyzed. Two network-based methods are applied to examine the connections in rainfall: clustering coefficient (a measure of the network's local density) and degree distribution (a measure of the network's spread). The influence of rainfall correlation threshold (T) on spatial connections is also investigated by considering seven different threshold levels (ranging from 0.5 to 0.8). The results indicate that: (1) rainfall networks corresponding to much coarser temporal scales exhibit properties similar to that of small-world networks, regardless of the threshold; (2) rainfall networks corresponding to much finer temporal scales may be classified as either small-world networks or scale-free networks, depending upon the threshold; and (3) rainfall spatial connections exhibit a transition phase at intermediate temporal scales, especially at high thresholds. These results suggest that the most appropriate model for studying spatial connections may often be different at different temporal scales, and that a combination of small-world and scale-free network models might be more appropriate for rainfall upscaling/downscaling across all scales, in the strict sense of scale-invariance. The results also suggest that spatial connections in the studied rainfall networks in Southeast Asia are weak, especially when more stringent conditions are imposed (i.e. when T is very high), except at the monthly scale.

The effects of acid rainfall and heavy metal particulates on a boreal forest ecosystem near the Sudbury smelting region of Canada

Treesearch

T. C. Hutchinson

1976-01-01

Sulphur dioxide emissions have occurred on a gigantic scale at Sudbury from nickel-copper smelters. Soil erosion has followed the destruction of large areas of forest. Rainfall has been found highly acidic, frequently less than pH 3.0 in 1971. Metal accumulation in the soils (to distances of 50 km) have occurred for nickel and copper. The combination of heavy metal...

Spatial and temporal patterns of Amazon rainfall. Consequences for the planning of agricultural occupation and the protection of primary forests.

PubMed

Sombroek, W

2001-11-01

The spatial and temporal pattern of annual rainfall and the strength of the dry season within the Amazon region are poorly known. Existing rainfall maps are based on the data from full-scale, long-term meteorological stations, operated by national organizations linked to the World Meteorological Organisation, such as INMET in Brazil. Stations with 30 or more years of uninterrupted and reliable recordings are very few, considering the size of the region, and most of them are located along the major rivers. It has been suggested that rainfall conditions away from these rivers are substantially different. An analysis has been made of the records of a network of simple pluviometric sites in the Brazilian part of the region as maintained by the National Agency for Electric Energy (ANEEL) since 1970. The latter data sets were used to draw more detailed maps on annual rainfall, and on the strength of the dry season in particular; average number of consecutive months with less than 100 mm, 50 mm, and 10 mm, respectively. Also, some data were obtained on the spatial expression of El Niño events within the region. Subregional differences are large, and it is argued that they are important for the success or failure of agricultural settlements; for the hazard of large-scale fire damage of the still existing primary forest vegetation; for the functioning of this land cover as stock and sink of CO2, and for the likelihood that secondary forests on abandoned agricultural lands will have less biomass. The effects of past El Niño rainfall anomalies on the biodiversity of the natural savannahs within the forest region are discussed.

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.

Rainy Day: A Remote Sensing-Driven Extreme Rainfall Simulation Approach for Hazard Assessment

NASA Astrophysics Data System (ADS)

Wright, Daniel; Yatheendradas, Soni; Peters-Lidard, Christa; Kirschbaum, Dalia; Ayalew, Tibebu; Mantilla, Ricardo; Krajewski, Witold

2015-04-01

Progress on the assessment of rainfall-driven hazards such as floods and landslides has been hampered by the challenge of characterizing the frequency, intensity, and structure of extreme rainfall at the watershed or hillslope scale. Conventional approaches rely on simplifying assumptions and are strongly dependent on the location, the availability of long-term rain gage measurements, and the subjectivity of the analyst. Regional and global-scale rainfall remote sensing products provide an alternative, but are limited by relatively short (~15-year) observational records. To overcome this, we have coupled these remote sensing products with a space-time resampling framework known as stochastic storm transposition (SST). SST "lengthens" the rainfall record by resampling from a catalog of observed storms from a user-defined region, effectively recreating the regional extreme rainfall hydroclimate. This coupling has been codified in Rainy Day, a Python-based platform for quickly generating large numbers of probabilistic extreme rainfall "scenarios" at any point on the globe. Rainy Day is readily compatible with any gridded rainfall dataset. The user can optionally incorporate regional rain gage or weather radar measurements for bias correction using the Precipitation Uncertainties for Satellite Hydrology (PUSH) framework. Results from Rainy Day using the CMORPH satellite precipitation product are compared with local observations in two examples. The first example is peak discharge estimation in a medium-sized (~4000 square km) watershed in the central United States performed using CUENCAS, a parsimonious physically-based distributed hydrologic model. The second example is rainfall frequency analysis for Saint Lucia, a small volcanic island in the eastern Caribbean that is prone to landslides and flash floods. The distinct rainfall hydroclimates of the two example sites illustrate the flexibility of the approach and its usefulness for hazard analysis in data-poor regions.

Critical scales to explain urban hydrological response: an application in Cranbrook, London

NASA Astrophysics Data System (ADS)

Cristiano, Elena; ten Veldhuis, Marie-Claire; Gaitan, Santiago; Ochoa Rodriguez, Susana; van de Giesen, Nick

2018-04-01

Rainfall variability in space and time, in relation to catchment characteristics and model complexity, plays an important role in explaining the sensitivity of hydrological response in urban areas. In this work we present a new approach to classify rainfall variability in space and time and we use this classification to investigate rainfall aggregation effects on urban hydrological response. Nine rainfall events, measured with a dual polarimetric X-Band radar instrument at the CAESAR site (Cabauw Experimental Site for Atmospheric Research, NL), were aggregated in time and space in order to obtain different resolution combinations. The aim of this work was to investigate the influence that rainfall and catchment scales have on hydrological response in urban areas. Three dimensionless scaling factors were introduced to investigate the interactions between rainfall and catchment scale and rainfall input resolution in relation to the performance of the model. Results showed that (1) rainfall classification based on cluster identification well represents the storm core, (2) aggregation effects are stronger for rainfall than flow, (3) model complexity does not have a strong influence compared to catchment and rainfall scales for this case study, and (4) scaling factors allow the adequate rainfall resolution to be selected to obtain a given level of accuracy in the calculation of hydrological response.

The impact of mesoscale convective systems on global precipitation: A modeling study

NASA Astrophysics Data System (ADS)

Tao, Wei-Kuo

2017-04-01

The importance of precipitating mesoscale convective systems (MCSs) has been quantified from TRMM precipitation radar and microwave imager retrievals. MCSs generate more than 50% of the rainfall in most tropical regions. Typical MCSs have horizontal scales of a few hundred kilometers (km); therefore, a large domain and high resolution are required for realistic simulations of MCSs in cloud-resolving models (CRMs). Almost all traditional global and climate models do not have adequate parameterizations to represent MCSs. Typical multi-scale modeling frameworks (MMFs) with 32 CRM grid points and 4 km grid spacing also might not have sufficient resolution and domain size for realistically simulating MCSs. In this study, the impact of MCSs on precipitation processes is examined by conducting numerical model simulations using the Goddard Cumulus Ensemble model (GCE) and Goddard MMF (GMMF). The results indicate that both models can realistically simulate MCSs with more grid points (i.e., 128 and 256) and higher resolutions (1 or 2 km) compared to those simulations with less grid points (i.e., 32 and 64) and low resolution (4 km). The modeling results also show that the strengths of the Hadley circulations, mean zonal and regional vertical velocities, surface evaporation, and amount of surface rainfall are either weaker or reduced in the GMMF when using more CRM grid points and higher CRM resolution. In addition, the results indicate that large-scale surface evaporation and wind feed back are key processes for determining the surface rainfall amount in the GMMF. A sensitivity test with reduced sea surface temperatures (SSTs) is conducted and results in both reduced surface rainfall and evaporation.

The Impact of Simulated Mesoscale Convective Systems on Global Precipitation: A Multiscale Modeling Study

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Chern, Jiun-Dar

2017-01-01

The importance of precipitating mesoscale convective systems (MCSs) has been quantified from TRMM precipitation radar and microwave imager retrievals. MCSs generate more than 50% of the rainfall in most tropical regions. MCSs usually have horizontal scales of a few hundred kilometers (km); therefore, a large domain with several hundred km is required for realistic simulations of MCSs in cloud-resolving models (CRMs). Almost all traditional global and climate models do not have adequate parameterizations to represent MCSs. Typical multi-scale modeling frameworks (MMFs) may also lack the resolution (4 km grid spacing) and domain size (128 km) to realistically simulate MCSs. In this study, the impact of MCSs on precipitation is examined by conducting model simulations using the Goddard Cumulus Ensemble (GCE) model and Goddard MMF (GMMF). The results indicate that both models can realistically simulate MCSs with more grid points (i.e., 128 and 256) and higher resolutions (1 or 2 km) compared to those simulations with fewer grid points (i.e., 32 and 64) and low resolution (4 km). The modeling results also show the strengths of the Hadley circulations, mean zonal and regional vertical velocities, surface evaporation, and amount of surface rainfall are weaker or reduced in the GMMF when using more CRM grid points and higher CRM resolution. In addition, the results indicate that large-scale surface evaporation and wind feed back are key processes for determining the surface rainfall amount in the GMMF. A sensitivity test with reduced sea surface temperatures shows both reduced surface rainfall and evaporation.

Rain Characteristics and Large-Scale Environments of Precipitation Objects with Extreme Rain Volumes from TRMM Observations

NASA Technical Reports Server (NTRS)

Zhou, Yaping; Lau, William K M.; Liu, Chuntao

2013-01-01

This study adopts a "precipitation object" approach by using 14 years of Tropical Rainfall Measuring Mission (TRMM) Precipitation Feature (PF) and National Centers for Environmental Prediction (NCEP) reanalysis data to study rainfall structure and environmental factors associated with extreme heavy rain events. Characteristics of instantaneous extreme volumetric PFs are examined and compared to those of intermediate and small systems. It is found that instantaneous PFs exhibit a much wider scale range compared to the daily gridded precipitation accumulation range. The top 1% of the rainiest PFs contribute over 55% of total rainfall and have 2 orders of rain volume magnitude greater than those of the median PFs. We find a threshold near the top 10% beyond which the PFs grow exponentially into larger, deeper, and colder rain systems. NCEP reanalyses show that midlevel relative humidity and total precipitable water increase steadily with increasingly larger PFs, along with a rapid increase of 500 hPa upward vertical velocity beyond the top 10%. This provides the necessary moisture convergence to amplify and sustain the extreme events. The rapid increase in vertical motion is associated with the release of convective available potential energy (CAPE) in mature systems, as is evident in the increase in CAPE of PFs up to 10% and the subsequent dropoff. The study illustrates distinct stages in the development of an extreme rainfall event including: (1) a systematic buildup in large-scale temperature and moisture, (2) a rapid change in rain structure, (3) explosive growth of the PF size, and (4) a release of CAPE before the demise of the event.

Convective Cloud and Rainfall Processes Over the Maritime Continent: Simulation and Analysis of the Diurnal Cycle

NASA Astrophysics Data System (ADS)

Gianotti, Rebecca L.

The Maritime Continent experiences strong moist convection, which produces significant rainfall and drives large fluxes of heat and moisture to the upper troposphere. Despite the importance of these processes to global circulations, current predictions of climate change over this region are still highly uncertain, largely due to inadequate representation of the diurnally-varying processes related to convection. In this work, a coupled numerical model of the land-atmosphere system (RegCM3-IBIS) is used to investigate how more physically-realistic representations of these processes can be incorporated into large-scale climate models. In particular, this work improves simulations of convective-radiative feedbacks and the role of cumulus clouds in mediating the diurnal cycle of rainfall. Three key contributions are made to the development of RegCM3-IBIS. Two pieces of work relate directly to the formation and dissipation of convective clouds: a new representation of convective cloud cover, and a new parameterization of convective rainfall production. These formulations only contain parameters that can be directly quantified from observational data, are independent of model user choices such as domain size or resolution, and explicitly account for subgrid variability in cloud water content and nonlinearities in rainfall production. The third key piece of work introduces a new method for representation of cloud formation within the boundary layer. A comprehensive evaluation of the improved model was undertaken using a range of satellite-derived and ground-based datasets, including a new dataset from Singapore's Changi airport that documents diurnal variation of the local boundary layer height. The performance of RegCM3-IBIS with the new formulations is greatly improved across all evaluation metrics, including cloud cover, cloud liquid water, radiative fluxes and rainfall, indicating consistent improvement in physical realism throughout the simulation. This work demonstrates that: (1) moist convection strongly influences the near surface environment by mediating the incoming solar radiation and net radiation at the surface; (2) dissipation of convective cloud via rainfall plays an equally important role in the convectiveradiative feedback as the formation of that cloud; and (3) over parts of the Maritime Continent, rainfall is a product of diurnally-varying convective processes that operate at small spatial scales, on the order of 1 km. (Copies available exclusively from MIT Libraries, libraries.mit.edu/docs - docs@mit.edu)

Difference infiltrometer: a method to measure temporally variable infiltration rates during rainstorms

USGS Publications Warehouse

Moody, John A.; Ebel, Brian A.

2012-01-01

We developed a difference infiltrometer to measure time series of non-steady infiltration rates during rainstorms at the point scale. The infiltrometer uses two, tipping bucket rain gages. One gage measures rainfall onto, and the other measures runoff from, a small circular plot about 0.5-m in diameter. The small size allows the infiltration rate to be computed as the difference of the cumulative rainfall and cumulative runoff without having to route water through a large plot. Difference infiltrometers were deployed in an area burned by the 2010 Fourmile Canyon Fire near Boulder, Colorado, USA, and data were collected during the summer of 2011. The difference infiltrometer demonstrated the capability to capture different magnitudes of infiltration rates and temporal variability associated with convective (high intensity, short duration) and cyclonic (low intensity, long duration) rainstorms. Data from the difference infiltrometer were used to estimate saturated hydraulic conductivity of soil affected by the heat from a wildfire. The difference infiltrometer is portable and can be deployed in rugged, steep terrain and does not require the transport of water, as many rainfall simulators require, because it uses natural rainfall. It can be used to assess infiltration models, determine runoff coefficients, identify rainfall depth or rainfall intensity thresholds to initiate runoff, estimate parameters for infiltration models, and compare remediation treatments on disturbed landscapes. The difference infiltrometer can be linked with other types of soil monitoring equipment in long-term studies for detecting temporal and spatial variability at multiple time scales and in nested designs where it can be linked to hillslope and basin-scale runoff responses.

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

NASA Technical Reports Server (NTRS)

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

2005-01-01

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

Soil moisture and biogeochemical factors influence the distribution of annual Bromus species

Treesearch

Jayne Belnap; John M. Stark; Benjamin M. Rau; Edith B. Allen; Susan Phillips

2016-01-01

Abiotic factors have a strong influence on where annual Bromus species are found. At the large regional scale, temperature and precipitation extremes determine the boundaries of Bromus occurrence. At the more local scale, soil characteristics and climate influence distribution, cover, and performance. In hot, dry, summer-rainfall-dominated deserts (Sonoran, Chihuahuan...

Prediction of rainfall anomalies during the dry to wet transition season over the Southern Amazonia using machine learning tools

NASA Astrophysics Data System (ADS)

Shan, X.; Zhang, K.; Zhuang, Y.; Fu, R.; Hong, Y.

2017-12-01

Seasonal prediction of rainfall during the dry-to-wet transition season in austral spring (September-November) over southern Amazonia is central for improving planting crops and fire mitigation in that region. Previous studies have identified the key large-scale atmospheric dynamic and thermodynamics pre-conditions during the dry season (June-August) that influence the rainfall anomalies during the dry to wet transition season over Southern Amazonia. Based on these key pre-conditions during dry season, we have evaluated several statistical models and developed a Neural Network based statistical prediction system to predict rainfall during the dry to wet transition for Southern Amazonia (5-15°S, 50-70°W). Multivariate Empirical Orthogonal Function (EOF) Analysis is applied to the following four fields during JJA from the ECMWF Reanalysis (ERA-Interim) spanning from year 1979 to 2015: geopotential height at 200 hPa, surface relative humidity, convective inhibition energy (CIN) index and convective available potential energy (CAPE), to filter out noise and highlight the most coherent spatial and temporal variations. The first 10 EOF modes are retained for inputs to the statistical models, accounting for at least 70% of the total variance in the predictor fields. We have tested several linear and non-linear statistical methods. While the regularized Ridge Regression and Lasso Regression can generally capture the spatial pattern and magnitude of rainfall anomalies, we found that that Neural Network performs best with an accuracy greater than 80%, as expected from the non-linear dependence of the rainfall on the large-scale atmospheric thermodynamic conditions and circulation. Further tests of various prediction skill metrics and hindcasts also suggest this Neural Network prediction approach can significantly improve seasonal prediction skill than the dynamic predictions and regression based statistical predictions. Thus, this statistical prediction system could have shown potential to improve real-time seasonal rainfall predictions in the future.

Temporal sequencing of throughfall drop generation as revealed by use of a large-scale rainfall simulator

NASA Astrophysics Data System (ADS)

Nanko, K.; Levia, D. F., Jr.; Iida, S.; SUN, X.; Shinohara, Y.; Sakai, N.

2017-12-01

Scientists have been interested in throughfall drop size and its distribution because of its importance to soil erosion and the forest water balance. An indoor experiment was employed to deepen our understanding of throughfall drop generation processes to promote better management of forested ecosystems. The indoor experiment provides a unique opportunity to examine an array of constant rainfall intensities that are ideal conditions to pick up the effect of changing intensities and not found in the fields. Throughfall drop generation was examined for three species- Cryptomeria japonica D. Don (Japanese cedar), Chamaecyparis obtusa (Siebold & Zucc.) Endl. (Japanese cypress), and Zelkova serrata Thunb. (Japanese zelkova)- under both leafed and leafless conditions in the large-scale rainfall simulator in the National Research Institute for Earth Science and Disaster Resilience (Tsukuba, Japan) at varying rainfall intensities ranging from15 to 100 mm h-1. Drop size distributions of the applied rainfall and throughfall were measured simultaneously by 20 laser disdrometers. Utilizing the drop size dataset, throughfall was separated into three components: free throughfall, canopy drip, and splash throughfall. The temporal sequencing of the throughfall components were analyzed on a 1-min interval during each experimental run. The throughfall component percentage and drop size of canopy drip differed among tree species and rainfall intensities and by elapsed time from the beginning of the rainfall event. Preliminary analysis revealed that the time differences to produce branch drip as compared to leaf (or needle) drip was partly due to differential canopy wet-up processes and the disappearance of branch drips due to canopy saturation, leading to dissimilar throughfall drop size distributions beneath the various tree species examined. This research was supported by JSPS Invitation Fellowship for Research in Japan (Grant No.: S16088) and JSPS KAKENHI (Grant No.: JP15H05626).

Observed Land Impacts on Clouds, Water Vapor, and Rainfall at Continental Scales

NASA Technical Reports Server (NTRS)

Jin, Menglin; King, Michael D.

2005-01-01

How do the continents affect large-scale hydrological cycles? How important can one continent be to the climate system? To address these questions, 4-years of National Aeronautics and Space Administration (NASA) Terra Moderate Resolution Imaging Spectroradiometer (MODIS) observations, Tropical Rainfall Measuring Mission (TRMM) observations, and the Global Precipitation Climatology Project (GPCP) global precipitation analysis, were used to assess the land impacts on clouds, rainfall, and water vapor at continental scales. At these scales, the observations illustrate that continents are integrated regions that enhance the seasonality of atmospheric and surface hydrological parameters. Specifically, the continents of Eurasia and North America enhance the seasonality of cloud optical thickness, cirrus fraction, rainfall, and water vapor. Over land, both liquid water and ice cloud effective radii are smaller than over oceans primarily because land has more aerosol particles. In addition, different continents have similar impacts on hydrological variables in terms of seasonality, but differ in magnitude. For example, in winter, North America and Eurasia increase cloud optical thickness to 17.5 and 16, respectively, while in summer, Eurasia has much smaller cloud optical thicknesses than North America. Such different land impacts are determined by each continent s geographical condition, land cover, and land use. These new understandings help further address the land-ocean contrasts on global climate, help validate global climate model simulated land-atmosphere interactions, and help interpret climate change over land.

Systematic errors in the simulation of the Asian summer monsoon: the role of rainfall variability on a range of time and space scales

NASA Astrophysics Data System (ADS)

Martin, Gill; Levine, Richard; Klingaman, Nicholas; Bush, Stephanie; Turner, Andrew; Woolnough, Steven

2015-04-01

Despite considerable efforts worldwide to improve model simulations of the Asian summer monsoon, significant biases still remain in climatological seasonal mean rainfall distribution, timing of the onset, and northward and eastward extent of the monsoon domain (Sperber et al., 2013). Many modelling studies have shown sensitivity to convection and boundary layer parameterization, cloud microphysics and land surface properties, as well as model resolution. Here we examine the problems in representing short-timescale rainfall variability (related to convection parameterization), problems in representing synoptic-scale systems such as monsoon depressions (related to model resolution), and the relationship of each of these with longer-term systematic biases. Analysis of the spatial distribution of rainfall intensity on a range of timescales ranging from ~30 minutes to daily, in the MetUM and in observations (where available), highlights how rainfall biases in the South Asian monsoon region on different timescales in different regions can be achieved in models through a combination of the incorrect frequency and/or intensity of rainfall. Over the Indian land area, the typical dry bias is related to sub-daily rainfall events being too infrequent, despite being too intense when they occur. In contrast, the wet bias regions over the equatorial Indian Ocean are mainly related to too frequent occurrence of lower-than-observed 3-hourly rainfall accumulations which result in too frequent occurrence of higher-than-observed daily rainfall accumulations. This analysis sheds light on the model deficiencies behind the climatological seasonal mean rainfall biases that many models exhibit in this region. Changing physical parameterizations alters this behaviour, with associated adjustments in the climatological rainfall distribution, although the latter is not always improved (Bush et al., 2014). This suggests a more complex interaction between the diabatic heating and the large-scale circulation than is indicated by the intensity and frequency of rainfall alone. Monsoon depressions and low pressure systems are important contributors to monsoon rainfall over central and northern India, areas where MetUM climate simulations typically show deficient monsoon rainfall. Analysis of MetUM climate simulations at resolutions ranging from N96 (~135km) to N512 (~25km) suggests that at lower resolution the numbers and intensities of monsoon depressions and low pressure systems and their associated rainfall are very low compared with re-analyses/observations. We show that there are substantial increases with horizontal resolution, but resolution is not the only factor. Idealised simulations, either using nudged atmospheric winds or initialised coupled hindcasts, which improve (strengthen) the mean state monsoon and cyclonic circulation over the Indian peninsula, also result in a substantial increase in monsoon depressions and associated rainfall. This suggests that a more realistic representation of monsoon depressions is possible even at lower resolution if the larger-scale systematic error pattern in the monsoon is improved.

Downscaling of a global climate model for estimation of runoff, sediment yield and dam storage: A case study of Pirapama basin, Brazil

NASA Astrophysics Data System (ADS)

Braga, Ana Cláudia F. Medeiros; Silva, Richarde Marques da; Santos, Celso Augusto Guimarães; Galvão, Carlos de Oliveira; Nobre, Paulo

2013-08-01

The coastal zone of northeastern Brazil is characterized by intense human activities and by large settlements and also experiences high soil losses that can contribute to environmental damage. Therefore, it is necessary to build an integrated modeling-forecasting system for rainfall-runoff erosion that assesses plans for water availability and sediment yield that can be conceived and implemented. In this work, we present an evaluation of an integrated modeling system for a basin located in this region with a relatively low predictability of seasonal rainfall and a small area (600 km2). The National Center for Environmental Predictions - NCEP’s Regional Spectral Model (RSM) nested within the Center for Weather Forecasting and Climate Studies - CPTEC’s Atmospheric General Circulation Model (AGCM) were investigated in this study, and both are addressed in the simulation work. The rainfall analysis shows that: (1) the dynamic downscaling carried out by the regional RSM model approximates the frequency distribution of the daily observed data set although errors were detected in the magnitude and timing (anticipation of peaks, for example) at the daily scale, (2) an unbiased precipitation forecast seemed to be essential for use of the results in hydrological models, and (3) the information directly extracted from the global model may also be useful. The simulated runoff and reservoir-stored volumes are strongly linked to rainfall, and their estimation accuracy was significantly improved at the monthly scale, thus rendering the results useful for management purposes. The runoff-erosion forecasting displayed a large sediment yield that was consistent with the predicted rainfall.

Spatial and temporal synchrony in reptile population dynamics in variable environments.

PubMed

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

2016-10-01

Resources are seldom distributed equally across space, but many species exhibit spatially synchronous population dynamics. Such synchrony suggests the operation of large-scale external drivers, such as rainfall or wildfire, or the influence of oasis sites that provide water, shelter, or other resources. However, testing the generality of these factors is not easy, especially in variable environments. Using a long-term dataset (13-22 years) from a large (8000 km(2)) study region in arid Central Australia, we tested firstly for regional synchrony in annual rainfall and the dynamics of six reptile species across nine widely separated sites. For species that showed synchronous spatial dynamics, we then used multivariate follow a multivariate auto-regressive state-space (MARSS) models to predict that regional rainfall would be positively associated with their populations. For asynchronous species, we used MARSS models to explore four other possible population structures: (1) populations were asynchronous, (2) differed between oasis and non-oasis sites, (3) differed between burnt and unburnt sites, or (4) differed between three sub-regions with different rainfall gradients. Only one species showed evidence of spatial population synchrony and our results provide little evidence that rainfall synchronizes reptile populations. The oasis or the wildfire hypotheses were the best-fitting models for the other five species. Thus, our six study species appear generally to be structured in space into one or two populations across the study region. Our findings suggest that for arid-dwelling reptile populations, spatial and temporal dynamics are structured by abiotic events, but individual responses to covariates at smaller spatial scales are complex and poorly understood.

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

NASA Astrophysics Data System (ADS)

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

2015-04-01

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

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

NASA Astrophysics Data System (ADS)

Misra, Vasubandhu

2007-06-01

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

Seasonal Evolution and Variability Associated with the West African Monsoon System

NASA Technical Reports Server (NTRS)

Gu, Guojun; Adler, Robert F.

2003-01-01

In this study, we investigate the seasonal variations in surface rainfall and associated large-scale processes in the tropical eastern Atlantic and West African region. The 5-yr (1998-2002) high-quality TRMM rainfall, sea surface temperature (SST), water vapor and cloud liquid water observations are applied along with the NCEP/NCAR reanalysis wind components and a 3-yr (2000-2002) Quickscat satellite-observed surface wind product. Major mean rainfall over West Africa tends to be concentrated in two regions and is observed in two different seasons, manifesting an abrupt shift of the mean rainfall zone during June-July. (i) Near the Gulf of Guinea (about 5 degN), intense convection and rainfall are seen during April-June and roughly follow the seasonality of SST in the tropical eastern Atlantic. (ii) Along the latitudes of about 10 deg. N over the interior West African continent, a second intense rain belt begins to develop from July and remains there during the later summer season. This belt co-exists with a northwardmoved African Easterly Jet (AEJ) and its accompanying horizonal and vertical shear zones, the appearance and intensification of an upper tropospheric Tropical Easterly Jet (TEJ), and a strong low-level westerly flow. Westward-propagating wave signals [ i e . , African easterly waves (AEWs)] dominate the synoptic-scale variability during July-September, in contrast to the evident eastward-propagating wave signals during May- June. The abrupt shift of mean rainfall zone thus turns out to be a combination of two different physical processes: (i) Evident seasonal cycles in the tropical eastern Atlantic ocean which modulate convection and rainfall in the Gulf of Guinea by means of SST thermal forcing and SST-related meridional gradient; (ii) The interaction among the AEJ, TEJ, low-level westerly flow, moist convection and AEWs during July-September which modulates rainfall variability in the interior West Africa, primarily within the ITCZ rain band. Evident seasonality in synoptic-scale wave signals is shown to be a good evidence for this seasonal evolution.

An assessment of the feasibility of the use of satellite-only rainfall estimates for the hydrological monitoring in central Italy

NASA Astrophysics Data System (ADS)

Campo, Lorenzo; Caparrini, Francesca

2013-04-01

The need for accurate distributed hydrological modelling has constantly increased in last years for several purposes: agricultural applications, water resources management, hydrological balance at watershed scale, floods forecast. The main input for the hydrological numerical models is rainfall data that present, at the same time, a large availability of measures (in gauged regions, with respect to other micro-meteorological variables) and the most complex spatial patterns. While also in presence of densely gauged watersheds the spatial interpolation of the rainfall is a non-trivial problem, due to the spatial intermittence of the variable (especially at finer temporal scales), ungauged regions need an alternative source of rainfall data in order to perform the hydrological modelling. Such source can be constituted by the satellite-estimated rainfall fields, with reference to both geostationary and polar-orbit platforms. In this work the rainfall product obtained by the Aqua-AIRS sensor were used in order to assess the feasibility of the use of satellite-based rainfall as input for distributed hydrological modelling. The MOBIDIC (MOdello di BIlancio Distribuito e Continuo) model, developed at the Department of civil and Environmental Engineering of the University of Florence and operationally used by Tuscany Region and Umbria Region for flood prediction and management, was used for the experiments. In particular three experiments were carried on: a) hydrological simulation with the use of rain-gauges data, b) simulation with the use of satellite-only rainfall estimates, c) simulation with the combined use of the two sources of data in order to obtain an optimal estimate of the actual rainfall fields. The domain of the study was the central Italy. Several critical events occurred in the area were analyzed. A discussion of the results is provided.

High resolution land surface response of inland moving Indian monsoon depressions over Bay of Bengal

NASA Astrophysics Data System (ADS)

Rajesh, P. V.; Pattnaik, S.

2016-05-01

During Indian summer monsoon (ISM) season, nearly about half of the monsoonal rainfall is brought inland by the low pressure systems called as Monsoon Depressions (MDs). These systems bear large amount of rainfall and frequently give copious amount of rainfall over land regions, therefore accurate forecast of these synoptic scale systems at short time scale can help in disaster management, flood relief, food safety. The goal of this study is to investigate, whether an accurate moisture-rainfall feedback from land surface can improve the prediction of inland moving MDs. High Resolution Land Data Assimilation System (HRLDAS) is used to generate improved land state .i.e. soil moisture and soil temperature profiles by means of NOAH-MP land-surface model. Validation of the model simulated basic atmospheric parameters at surface layer and troposphere reveals that the incursion of high resolution land state yields least Root Mean Squared Error (RMSE) with a higher correlation coefficient and facilitates accurate depiction of MDs. Rainfall verification shows that HRLDAS simulations are spatially and quantitatively in more agreement with the observations and the improved surface characteristics could result in the realistic reproduction of the storm spatial structure, movement as well as intensity. These results signify the necessity of investigating more into the land surface-rainfall feedbacks through modifications in moisture flux convergence within the storm.

Trends in autumn rain of West China from 1961 to 2014

NASA Astrophysics Data System (ADS)

Zhang, Chi; Wang, Zunya; Zhou, Botao; Li, Yonghua; Tang, Hongyu; Xiang, Bo

2018-02-01

Autumn rain of West China is a typical climate phenomenon, which is characterized by continuous rainy days and large rainfall amounts and exerts profound impacts on the economic society. Based on daily precipitation data from 524 observation stations for the period of 1961-2014, this article comprehensively examined secular changes in autumn rain of West China, including its amount, frequency, intensity, and associated extremes. The results generally show a significant reduction of rainfall amount and rainy days and a significant enhancement of mean rainfall intensity for the average of West China during autumn (September-October) since 1961. Meanwhile, decreasing trends are consistently observed in the maximum daily rainfall, the longest consecutive rainy days, the greatest consecutive rainfall amount, and the frequencies of the extreme daily rainfall, consecutive rainfall, and consecutive rainfall process. Further analysis indicates that the decreases of autumn rainfall and related extremes in West China are associated with the decreases in both water vapor content and atmospheric unstable stratification during the past decades. On the regional scale, some differences exist in the changes of autumn rainfall between the eastern and western parts of West China. Besides, it is found that the autumn rainy season tends to start later and terminate earlier particularly in eastern West China.

Downscaling large-scale circulation to local winter climate using neural network techniques

NASA Astrophysics Data System (ADS)

Cavazos Perez, Maria Tereza

1998-12-01

The severe impacts of climate variability on society reveal the increasing need for improving regional-scale climate diagnosis. A new downscaling approach for climate diagnosis is developed here. It is based on neural network techniques that derive transfer functions from the large-scale atmospheric controls to the local winter climate in northeastern Mexico and southeastern Texas during the 1985-93 period. A first neural network (NN) model employs time-lagged component scores from a rotated principal component analysis of SLP, 500-hPa heights, and 1000-500 hPa thickness as predictors of daily precipitation. The model is able to reproduce the phase and, to some decree, the amplitude of large rainfall events, reflecting the influence of the large-scale circulation. Large errors are found over the Sierra Madre, over the Gulf of Mexico, and during El Nino events, suggesting an increase in the importance of meso-scale rainfall processes. However, errors are also due to the lack of randomization of the input data and the absence of local atmospheric predictors such as moisture. Thus, a second NN model uses time-lagged specific humidity at the Earth's surface and at the 700 hPa level, SLP tendency, and 700-500 hPa thickness as input to a self-organizing map (SOM) that pre-classifies the atmospheric fields into different patterns. The results from the SOM classification document that negative (positive) anomalies of winter precipitation over the region are associated with: (1) weaker (stronger) Aleutian low; (2) stronger (weaker) North Pacific high; (3) negative (positive) phase of the Pacific North American pattern; and (4) La Nina (El Nino) events. The SOM atmospheric patterns are then used as input to a feed-forward NN that captures over 60% of the daily rainfall variance and 94% of the daily minimum temperature variance over the region. This demonstrates the ability of artificial neural network models to simulate realistic relationships on daily time scales. The results of this research also reveal that the SOM pre-classification of days with similar atmospheric conditions succeeded in emphasizing the differences of the atmospheric variance conducive to extreme events. This resulted in a downscaling NN model that is highly sensitive to local-scale weather anomalies associated with El Nino and extreme cold events.

How effective is the new generation of GPM satellite precipitation in characterizing the rainfall variability over Malaysia?

NASA Astrophysics Data System (ADS)

Mahmud, Mohd Rizaludin; Hashim, Mazlan; Reba, Mohd Nadzri Mohd

2017-08-01

We investigated the potential of the new generation of satellite precipitation product from the Global Precipitation Mission (GPM) to characterize the rainfall in Malaysia. Most satellite precipitation products have limited ability to precisely characterize the high dynamic rainfall variation that occurred at both time and scale in this humid tropical region due to the coarse grid size to meet the physical condition of the smaller land size, sub-continent and islands. Prior to the status quo, an improved satellite precipitation was required to accurately measure the rainfall and its distribution. Subsequently, the newly released of GPM precipitation product at half-hourly and 0.1° resolution served an opportunity to anticipate the aforementioned conflict. Nevertheless, related evidence was not found and therefore, this study made an initiative to fill the gap. A total of 843 rain gauges over east (Borneo) and west Malaysia (Peninsular) were used to evaluate the rainfall the GPM rainfall data. The assessment covered all critical rainy seasons which associated with Asian Monsoon including northeast (Nov. - Feb.), southwest (May - Aug.) and their subsequent inter-monsoon period (Mar. - Apr. & Sep. - Oct.). The ability of GPM to provide quantitative rainfall estimates and qualitative spatial rainfall patterns were analysed. Our results showed that the GPM had good capacity to depict the spatial rainfall patterns in less heterogeneous rainfall patterns (Spearman's correlation, 0.591 to 0.891) compared to the clustered one (r = 0.368 to 0.721). Rainfall intensity and spatial heterogeneity that is largely driven by seasonal monsoon has significant influence on GPM ability to resolve local rainfall patterns. In quantitative rainfall estimation, large errors can be primarily associated with the rainfall intensity increment. 77% of the error variation can be explained through rainfall intensity particularly the high intensity (> 35 mm d-1). A strong relationship between GPM rainfall and error was found from heavy ( 35 mm d-1) to violent rain (160 mm d-1). The output of this study provides reference regarding the performance of GPM data for respective hydrology studies in this region.

Sensitivity of peak flow to the change of rainfall temporal pattern due to warmer climate

NASA Astrophysics Data System (ADS)

Fadhel, Sherien; Rico-Ramirez, Miguel Angel; Han, Dawei

2018-05-01

The widely used design storms in urban drainage networks has different drawbacks. One of them is that the shape of the rainfall temporal pattern is fixed regardless of climate change. However, previous studies have shown that the temporal pattern may scale with temperature due to climate change, which consequently affects peak flow. Thus, in addition to the scaling of the rainfall volume, the scaling relationship for the rainfall temporal pattern with temperature needs to be investigated by deriving the scaling values for each fraction within storm events, which is lacking in many parts of the world including the UK. Therefore, this study analysed rainfall data from 28 gauges close to the study area with a 15-min resolution as well as the daily temperature data. It was found that, at warmer temperatures, the rainfall temporal pattern becomes less uniform, with more intensive peak rainfall during higher intensive times and weaker rainfall during less intensive times. This is the case for storms with and without seasonal separations. In addition, the scaling values for both the rainfall volume and the rainfall fractions (i.e. each segment of rainfall temporal pattern) for the summer season were found to be higher than the corresponding results for the winter season. Applying the derived scaling values for the temporal pattern of the summer season in a hydrodynamic sewer network model produced high percentage change of peak flow between the current and future climate. This study on the scaling of rainfall fractions is the first in the UK, and its findings are of importance to modellers and designers of sewer systems because it can provide more robust scenarios for flooding mitigation in urban areas.

Record Balkan floods of 2014 linked to planetary wave resonance.

PubMed

Stadtherr, Lisa; Coumou, Dim; Petoukhov, Vladimir; Petri, Stefan; Rahmstorf, Stefan

2016-04-01

In May 2014, the Balkans were hit by a Vb-type cyclone that brought disastrous flooding and severe damage to Bosnia and Herzegovina, Serbia, and Croatia. Vb cyclones migrate from the Mediterranean, where they absorb warm and moist air, to the north, often causing flooding in central/eastern Europe. Extreme rainfall events are increasing on a global scale, and both thermodynamic and dynamical mechanisms play a role. Where thermodynamic aspects are generally well understood, there is large uncertainty associated with current and future changes in dynamics. We study the climatic and meteorological factors that influenced the catastrophic flooding in the Balkans, where we focus on large-scale circulation. We show that the Vb cyclone was unusually stationary, bringing extreme rainfall for several consecutive days, and that this situation was likely linked to a quasi-stationary circumglobal Rossby wave train. We provide evidence that this quasi-stationary wave was amplified by wave resonance. Statistical analysis of daily spring rainfall over the Balkan region reveals significant upward trends over 1950-2014, especially in the high quantiles relevant for flooding events. These changes cannot be explained by simple thermodynamic arguments, and we thus argue that dynamical processes likely played a role in increasing flood risks over the Balkans.

Interannual and Decadal Variability of Summer Rainfall over South America

NASA Technical Reports Server (NTRS)

Zhou, Jiayu; Lau, K.-M.

1999-01-01

Using the CPC (Climate Prediction Center) Merged Analysis of Precipitation product along with the Goddard Earth Observing System reanalysis and the Climate Analysis Center sea surface temperature (SST) data, we conduct a diagnostic study of the interannual and decadal scale variability of summer rainfall over South America. Results show three leading modes of rainfall variation identified with interannual, decadal, and long-term trend variability. Together, these modes explain more than half the total variance. The first mode is highly correlated with El Nino/southern oscillation (ENSO), showing severe drought over Northeast Brazil and copious rainfall over the Ecuador coast and the area of Uruguay-Southern Brazil in El Nino years. This pattern is attributed to the large scale zonal shift of the Walker circulation and local Hadley cell anomaly induced by positive (negative) SST anomaly over the eastern (western) equatorial Pacific. In El Nino years, two convective belts indicated by upper tropospheric velocity potential trough and mid-tropospheric rising motion, which are somewhat symmetric about the equator, extend toward the northeast and the southeast into the tropical North and South Atlantic respectively. Sandwiched between the ascent is a region of descending motion over Northeast Brazil. The southern branch of the anomalous Hadley cell is dynamically linked to the increase of rainfall over Uruguay-Southern Brazil. The regional response of anomalous circulation shows a stronger South American summer monsoon and an enhanced (weakened) subtropical high over the South Atlantic (South Pacific) Ocean. The decadal variation displays a meridional shift of the Intertropical Convergence Zone (ITCZ), which is tie to the anomalous cross-equatorial SST gradient over the Atlantic and the eastern Pacific. In conjunction with this mode is a large scale mass swing between the polar regions and midlatitudes in both hemispheres. Over the South Atlantic and the South Pacific, the changes of the strength of the subtropical high and the associated surface wind are dynamically consistent with the distribution of local SST anomalies, suggesting the importance of the atmospheric forcing in the decadal time scale. The decadal mode also presents a weak summer monsoon in its positive phase, which reduces the moisture supply from the equatorial Atlantic and the Amazon Basin and results in negative rainfall anomalies over the central Andes and Gran Chaco. The long-term trend shows decrease of rainfall from the northwest coast to the southeast subtropical region and a southward shift of Atlantic ITCZ that leads to increased rainfall over northern and eastern Brazil. Our result shows a close link of this mode to the observed SST warming trend over the subtropical South Atlantic and a remote connection to the interdecadal SST variation over the extratropical North Atlantic found in previous studies.

Trend and variability in western and central Africa streamflow, and their relation to climate variability between 1950 and 2010

NASA Astrophysics Data System (ADS)

Sidibe, Moussa; Dieppois, Bastien; Mahé, Gil; Paturel, Jean-Emmanuel; Rouché, Nathalie; Amoussou, Ernest; Anifowose, Babatunde; Lawler, Damian

2017-04-01

Unprecedented drought episodes that struck western and central Africa between the late 1960s and 1980s. This triggered many studies investigating rainfall variability and its impacts on food production systems. However, most studies were focused at the catchment scale. In this study, we examine how rainfall variability has impacted on river flow at the subcontinental scale between 1950 and 2010, as well as the key large-scale controls on this relationship. For the first time, we establish a complete, gap-filled, monthly streamflow data set, which extends from 1950 to 2010, over the western and central African region. To achieve this, we used linear regression modelling across and between 600 flow gauging stations (see initial database information at http://www.hydrosciences.fr/sierem/index_en.htm). Streamflow trend and variability are then seasonally assessed at this subcontinental scale and compared to those observed in three different rainfall data sets (i.e. CRU TS3.24, GPCC V7, IRD-HSM). Long-term trends and variability in streamflow are mainly consistent with trends in rainfall. However, these relationships may have been moderated by: i) changes in land use; and ii) contributions from groundwater resources. In particular, we note that the recent post 1990s partial recovery in Sahel rainfall could have, at least partially, positively impacted river flows (e.g. the Senegal and Niger rivers). Using multi-temporal trend and continuous wavelet analysis, the time-evolution of western and central African river flows are analysed, and are all characterized by very strong decadal fluctuations, which can be interpreted as modulations in the baseflow. These decadal fluctuations, which are also significantly detected in rainfall, are likely related to large-scale sea-surface temperature (SST) anomaly patterns, such as the tropical Atlantic SST variability, the Atlantic Multidecadal Oscillation, the Interdecadal Pacific Oscillation and/or the Pacific Decadal Oscillation. Furthermore, hitherto-poorly understood hydroclimatic processes related to these teleconnections at decadal timescales will be examined in this study. Influences of the catchment properties (e.g. size, shape, vegetation and landuse cover, soil type, ground-water level, direction of stream flow across climate zones) on these decadal fluctuations in river flows will also be assessed. This study therefore aims to improve the ability of current regional and global climate models to simulate such ranges of variability, to significantly improve regional hydroclimate understanding, as a means for improving the development of future scenarios for water resources in western and central Africa.

TRMM Latent Heating Retrieval and Comparisons with Field Campaigns and Large-Scale Analyses

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Takayabu, Yukuri; Lang, S.; Shige, S.; Olson, W.; Hou, A.; Jiang, X.; Zhang, C.; Lau, W.; Krishnamurti, T.;

Predicting monthly precipitation along coastal Ecuador: ENSO and transfer function models

NASA Astrophysics Data System (ADS)

de Guenni, Lelys B.; García, Mariangel; Muñoz, Ángel G.; Santos, José L.; Cedeño, Alexandra; Perugachi, Carlos; Castillo, José

2017-08-01

It is well known that El Niño-Southern Oscillation (ENSO) modifies precipitation patterns in several parts of the world. One of the most impacted areas is the western coast of South America, where Ecuador is located. El Niño events that occurred in 1982-1983, 1987-1988, 1991-1992, and 1997-1998 produced important positive rainfall anomalies in the coastal zone of Ecuador, bringing considerable damage to livelihoods, agriculture, and infrastructure. Operational climate forecasts in the region provide only seasonal scale (e.g., 3-month averages) information, but during ENSO events it is key for decision-makers to use reliable sub-seasonal scale forecasts, which at the present time are still non-existent in most parts of the world. This study analyzes the potential predictability of coastal Ecuador rainfall at monthly scale. Instead of the discrete approach that considers training models using only particular seasons, continuous (i.e., all available months are used) transfer function models are built using standard ENSO indices to explore rainfall forecast skill along the Ecuadorian coast and Galápagos Islands. The modeling approach considers a large-scale contribution, represented by the role of a sea-surface temperature index, and a local-scale contribution represented here via the use of previous precipitation observed in the same station. The study found that the Niño3 index is the best ENSO predictor of monthly coastal rainfall, with a lagged response varying from 0 months (simultaneous) for Galápagos up to 3 months for the continental locations considered. Model validation indicates that the skill is similar to the one obtained using principal component regression models for the same kind of experiments. It is suggested that the proposed approach could provide skillful rainfall forecasts at monthly scale for up to a few months in advance.

Development of a flash flood warning system based on real-time radar data and process-based erosion modelling

NASA Astrophysics Data System (ADS)

Schindewolf, Marcus; Kaiser, Andreas; Buchholtz, Arno; Schmidt, Jürgen

2017-04-01

Extreme rainfall events and resulting flash floods led to massive devastations in Germany during spring 2016. The study presented aims on the development of a early warning system, which allows the simulation and assessment of negative effects on infrastructure by radar-based heavy rainfall predictions, serving as input data for the process-based soil loss and deposition model EROSION 3D. Our approach enables a detailed identification of runoff and sediment fluxes in agricultural used landscapes. In a first step, documented historical events were analyzed concerning the accordance of measured radar rainfall and large scale erosion risk maps. A second step focused on a small scale erosion monitoring via UAV of source areas of heavy flooding events and a model reconstruction of the processes involved. In all examples damages were caused to local infrastructure. Both analyses are promising in order to detect runoff and sediment delivering areas even in a high temporal and spatial resolution. Results prove the important role of late-covering crops such as maize, sugar beet or potatoes in runoff generation. While e.g. winter wheat positively affects extensive runoff generation on undulating landscapes, massive soil loss and thus muddy flows are observed and depicted in model results. Future research aims on large scale model parameterization and application in real time, uncertainty estimation of precipitation forecast and interface developments.

High Resolution Flash Flood Forecasting Using a Wireless Sensor Network in the Dallas-Fort Worth Metroplex

NASA Astrophysics Data System (ADS)

Bartos, M. D.; Kerkez, B.; Noh, S.; Seo, D. J.

2017-12-01

In this study, we develop and evaluate a high resolution urban flash flood monitoring system using a wireless sensor network (WSN), a real-time rainfall-runoff model, and spatially-explicit radar rainfall predictions. Flooding is the leading cause of natural disaster fatalities in the US, with flash flooding in particular responsible for a majority of flooding deaths. While many riverine flood models have been operationalized into early warning systems, there is currently no model that is capable of reliably predicting flash floods in urban areas. Urban flash floods are particularly difficult to model due to a lack of rainfall and runoff data at appropriate scales. To address this problem, we develop a wide-area flood-monitoring wireless sensor network for the Dallas-Fort Worth metroplex, and use this network to characterize rainfall-runoff response over multiple heterogeneous catchments. First, we deploy a network of 22 wireless sensor nodes to collect real-time stream stage measurements over catchments ranging from 2-80 km2 in size. Next, we characterize the rainfall-runoff response of each catchment by combining stream stage data with gage and radar-based precipitation measurements. Finally, we demonstrate the potential for real-time flash flood prediction by joining the derived rainfall-runoff models with real-time radar rainfall predictions. We find that runoff response is highly heterogeneous among catchments, with large variabilities in runoff response detected even among nearby gages. However, when spatially-explicit rainfall fields are included, spatial variability in runoff response is largely captured. This result highlights the importance of increased spatial coverage for flash flood prediction.

Evaluation of interpolation techniques for the creation of gridded daily precipitation (1 × 1 km2); Cyprus, 1980-2010

NASA Astrophysics Data System (ADS)

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

2014-01-01

High-resolution gridded daily data sets are essential for natural resource management and the analyses of climate changes and their effects. This study aims to evaluate the performance of 15 simple or complex interpolation techniques in reproducing daily precipitation at a resolution of 1 km2 over topographically complex areas. Methods are tested considering two different sets of observation densities and different rainfall amounts. We used rainfall data that were recorded at 74 and 145 observational stations, respectively, spread over the 5760 km2 of the Republic of Cyprus, in the Eastern Mediterranean. Regression analyses utilizing geographical copredictors and neighboring interpolation techniques were evaluated both in isolation and combined. Linear multiple regression (LMR) and geographically weighted regression methods (GWR) were tested. These included a step-wise selection of covariables, as well as inverse distance weighting (IDW), kriging, and 3D-thin plate splines (TPS). The relative rank of the different techniques changes with different station density and rainfall amounts. Our results indicate that TPS performs well for low station density and large-scale events and also when coupled with regression models. It performs poorly for high station density. The opposite is observed when using IDW. Simple IDW performs best for local events, while a combination of step-wise GWR and IDW proves to be the best method for large-scale events and high station density. This study indicates that the use of step-wise regression with a variable set of geographic parameters can improve the interpolation of large-scale events because it facilitates the representation of local climate dynamics.

Prediction and monitoring of monsoon intraseasonal oscillations over Indian monsoon region in an ensemble prediction system using CFSv2

NASA Astrophysics Data System (ADS)

Abhilash, S.; Sahai, A. K.; Borah, N.; Chattopadhyay, R.; Joseph, S.; Sharmila, S.; De, S.; Goswami, B. N.; Kumar, Arun

2014-05-01

An ensemble prediction system (EPS) is devised for the extended range prediction (ERP) of monsoon intraseasonal oscillations (MISO) of Indian summer monsoon (ISM) using National Centers for Environmental Prediction Climate Forecast System model version 2 at T126 horizontal resolution. The EPS is formulated by generating 11 member ensembles through the perturbation of atmospheric initial conditions. The hindcast experiments were conducted at every 5-day interval for 45 days lead time starting from 16th May to 28th September during 2001-2012. The general simulation of ISM characteristics and the ERP skill of the proposed EPS at pentad mean scale are evaluated in the present study. Though the EPS underestimates both the mean and variability of ISM rainfall, it simulates the northward propagation of MISO reasonably well. It is found that the signal-to-noise ratio of the forecasted rainfall becomes unity by about 18 days. The potential predictability error of the forecasted rainfall saturates by about 25 days. Though useful deterministic forecasts could be generated up to 2nd pentad lead, significant correlations are found even up to 4th pentad lead. The skill in predicting large-scale MISO, which is assessed by comparing the predicted and observed MISO indices, is found to be ~17 days. It is noted that the prediction skill of actual rainfall is closely related to the prediction of large-scale MISO amplitude as well as the initial conditions related to the different phases of MISO. An analysis of categorical prediction skills reveals that break is more skillfully predicted, followed by active and then normal. The categorical probability skill scores suggest that useful probabilistic forecasts could be generated even up to 4th pentad lead.

Influence of rainfall data scarcity on non-point source pollution prediction: Implications for physically based models

NASA Astrophysics Data System (ADS)

Chen, Lei; Xu, Jiajia; Wang, Guobo; Liu, Hongbin; Zhai, Limei; Li, Shuang; Sun, Cheng; Shen, Zhenyao

2018-07-01

Hydrological and non-point source pollution (H/NPS) predictions in ungagged basins have become the key problem for watershed studies, especially for those large-scale catchments. However, few studies have explored the comprehensive impacts of rainfall data scarcity on H/NPS predictions. This study focused on: 1) the effects of rainfall spatial scarcity (by removing 11%-67% of stations based on their locations) on the H/NPS results; and 2) the impacts of rainfall temporal scarcity (10%-60% data scarcity in time series); and 3) the development of a new evaluation method that incorporates information entropy. A case study was undertaken using the Soil and Water Assessment Tool (SWAT) in a typical watershed in China. The results of this study highlighted the importance of critical-site rainfall stations that often showed greater influences and cross-tributary impacts on the H/NPS simulations. Higher missing rates above a certain threshold as well as missing locations during the wet periods resulted in poorer simulation results. Compared to traditional indicators, information entropy could serve as a good substitute because it reflects the distribution of spatial variability and the development of temporal heterogeneity. This paper reports important implications for the application of Distributed Hydrological Models and Semi-distributed Hydrological Models, as well as for the optimal design of rainfall gauges among large basins.

A single scaling parameter as a first approximation to describe the rainfall pattern of a place: application on Catalonia

NASA Astrophysics Data System (ADS)

Casas-Castillo, M. Carmen; Llabrés-Brustenga, Alba; Rius, Anna; Rodríguez-Solà, Raúl; Navarro, Xavier

2018-02-01

As well as in other natural processes, it has been frequently observed that the phenomenon arising from the rainfall generation process presents fractal self-similarity of statistical type, and thus, rainfall series generally show scaling properties. Based on this fact, there is a methodology, simple scaling, which is used quite broadly to find or reproduce the intensity-duration-frequency curves of a place. In the present work, the relationship of the simple scaling parameter with the characteristic rainfall pattern of the area of study has been investigated. The calculation of this scaling parameter has been performed from 147 daily rainfall selected series covering the temporal period between 1883 and 2016 over the Catalonian territory (Spain) and its nearby surroundings, and a discussion about the relationship between the scaling parameter spatial distribution and rainfall pattern, as well as about trends of this scaling parameter over the past decades possibly due to climate change, has been presented.

Characterizing multiscale variability of zero intermittency in spatial rainfall

NASA Technical Reports Server (NTRS)

Kumar, Praveen; Foufoula-Georgiou, Efi

1994-01-01

In this paper the authors study how zero intermittency in spatial rainfall, as described by the fraction of area covered by rainfall, changes with spatial scale of rainfall measurement or representation. A statistical measure of intermittency that describes the size distribution of 'voids' (nonrainy areas imbedded inside rainy areas) as a function of scale is also introduced. Morphological algorithms are proposed for reconstructing rainfall intermittency at fine scales given the intermittency at coarser scales. These algorithms are envisioned to be useful in hydroclimatological studies where the rainfall spatial variability at the subgrid scale needs to be reconstructed from the results of synoptic- or mesoscale meteorological numerical models. The developed methodologies are demsonstrated and tested using data from a severe springtime midlatitude squall line and a mild midlatitude winter storm monitored by a meteorological radar in Norman, Oklahoma.

North-East monsoon rainfall extremes over the southern peninsular India and their association with El Niño

NASA Astrophysics Data System (ADS)

Singh, Prem; Gnanaseelan, C.; Chowdary, J. S.

2017-12-01

The present study investigates the relationship between extreme north-east (NE) monsoon rainfall (NEMR) over the Indian peninsula region and El Niño forcing. This turns out to be a critical science issue especially after the 2015 Chennai flood. The puzzle being while most El Niños favour good NE monsoon, some don't. In fact some El Niño years witnessed deficit NE monsoon. Therefore two different cases (or classes) of El Niños are considered for analysis based on standardized NEMR index and Niño 3.4 index with case-1 being both Niño-3.4 and NEMR indices greater than +1 and case-2 being Niño-3.4 index greater than +1 and NEMR index less than -1. Composite analysis suggests that SST anomalies in the central and eastern Pacific are strong in both cases but large differences are noted in the spatial distribution of SST over the Indo-western Pacific region. This questions our understanding of NEMR as mirror image of El Niño conditions in the Pacific. It is noted that the favourable excess NEMR in case-1 is due to anomalous moisture transport from Bay of Bengal and equatorial Indian Ocean to southern peninsular India. Strong SST gradient between warm western Indian Ocean (and Bay of Bengal) and cool western Pacific induced strong easterly wind anomalies during NE monsoon season favour moisture transport towards the core NE monsoon region. Further anomalous moisture convergence and convection over the core NE monsoon region supported positive rainfall anomalies in case-1. While in case-2, weak SST gradients over the Indo-western Pacific and absence of local low level convergence over NE monsoon region are mainly responsible for deficit rainfall. The ocean dynamics in the Indian Ocean displayed large differences during case-1 and case-2, suggesting the key role of Rossby wave dynamics in the Indian Ocean on NE monsoon extremes. Apart from the large scale circulation differences the number of cyclonic systems land fall for case-1 and case-2 have also contributed for variations in NE monsoon rainfall extremes during El Niño years. This study indicates that despite having strong warming in the central and eastern Pacific, NE monsoon rainfall variations over the southern peninsular India is mostly determined by SST gradient over the Indo-western Pacific region and number of systems formation in the Bay of Bengal and their land fall. The paper concludes that though the favourable large scale circulation induced by Pacific is important in modulating the NE monsoon rainfall the local air sea interaction plays a key role in modulating or driving rainfall extremes associated with El Niño.

Required spatial resolution of hydrological models to evaluate urban flood resilience measures

NASA Astrophysics Data System (ADS)

Gires, A.; Giangola-Murzyn, A.; Tchiguirinskaia, I.; Schertzer, D.; Lovejoy, S.

2012-04-01

During a flood in urban area, several non-linear processes (rainfall, surface runoff, sewer flow, and sub-surface flow) interact. Fully distributed hydrological models are a useful tool to better understand these complex interactions between natural processes and man built environment. Developing an efficient model is a first step to improve the understanding of flood resilience in urban area. Given that the previously mentioned underlying physical phenomenon exhibit different relevant scales, determining the required spatial resolution of such model is tricky but necessary issue. For instance such model should be able to properly represent large scale effects of local scale flood resilience measures such as stop logs. The model should also be as simple as possible without being simplistic. In this paper we test two types of model. First we use an operational semi-distributed model over a 3400 ha peri-urban area located in Seine-Saint-Denis (North-East of Paris). In this model, the area is divided into sub-catchments of average size 17 ha that are considered as homogenous, and only the sewer discharge is modelled. The rainfall data, whose resolution is 1 km is space and 5 min in time, comes from the C-band radar of Trappes, located in the West of Paris, and operated by Météo-France. It was shown that the spatial resolution of both the model and the rainfall field did not enable to fully grasp the small scale rainfall variability. To achieve this, first an ensemble of realistic rainfall fields downscaled to a resolution of 100 m is generated with the help of multifractal space-time cascades whose characteristic exponents are estimated on the available radar data. Second the corresponding ensemble of sewer hydrographs is simulated by inputting each rainfall realization to the model. It appears that the probability distribution of the simulated peak flow exhibits a power-law behaviour. This indicates that there is a great uncertainty associated with small scale rainfall. Second we focus on a 50 ha catchment of this area and implement Multi-Hydro, a fully distributed urban hydrological model currently being developed at Ecole des Ponts ParisTech (El Tabach et al., 2009). The version used in this paper consists in an interactive coupling between a 2D model representing infiltration and surface runoff (TREX, Two dimensional Runoff, Erosion and eXport model, Velleux et al., 2011) and a 1D model of sewer networks (SWMM, Storm Water Management Model, Rossman, 2007). Spatial resolution ranging from 2 m to 50 m for land use, topography and rainfall are tested. A special highlight on the impact of small scales rainfall is done. To achieve this the previously mentioned methodology is implemented with rainfall fields downscaled to 10 m in space and 20 s in time. Finally, we will discuss the gains generated by the implementation of the fully distributed model.

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.

Diagnosing Possible Anthropogenic Contributions to Heavy Colorado Rainfall in September 2013

NASA Astrophysics Data System (ADS)

Pall, Pardeep; Patricola, Christina; Wehner, Michael; Stone, Dáithí; Paciorek, Christopher; Collins, William

2015-04-01

Unusually heavy rainfall occurred over the Colorado Front Range during early September 2013, with record or near-record totals recorded in several locations. It was associated predominantly with a stationary large-scale weather pattern (akin to the North American Monsoon, which occurs earlier in the year) that drove a strong plume of deep moisture inland from the Gulf of Mexico against the Front Range foothills. The resulting floods across the South Platte River basin impacted several thousands of people and many homes, roads, and businesses. To diagnose possible anthropogenic contributions to the odds of such heavy rainfall, we adapt an existing event attribution paradigm of modelling an 'event that was' for September 2013 and comparing it to a modelled 'event that might have been' for that same time but for the absence of historical anthropogenic drivers of climate. Specifically, we first perform 'event that was' simulations with the regional Weather Research and Forecasting (WRF) model at 12 km resolution over North America, driven by NCEP2 re-analysis. We then re-simulate, having adjusted the re-analysis to 'event that might have been conditions' by modifying atmospheric greenhouse gas and other pollutant concentrations, temperature, humidity, and winds, as well as sea ice coverage, and sea-surface temperatures - all according to estimates from global climate model simulations. Thus our findings are highly conditional on the driving re-analysis and adjustments therein, but the setup allows us to elucidate possible mechanisms responsible for heavy Colorado rainfall in September 2013. Our model results suggests that, given an insignificant change in the pattern of large-scale driving weather, there is an increase in atmospheric water vapour under anthropogenic climate warming leading to a substantial increase in the probability of heavy rainfall occurring over the South Platte River basin in September 2013.

Diagnosing Possible Anthropogenic Contributions to Heavy Colorado Rainfall in September 2013

NASA Astrophysics Data System (ADS)

Pall, P.; Patricola, C. M.; Wehner, M. F.; Stone, D. A.; Paciorek, C. J.; Collins, W.

2014-12-01

Unusually heavy rainfall occurred over the Colorado Front Range during early September 2013, with record or near-record totals recorded in several locations. It was associated predominantly with a stationary large-scale weather pattern (akin to the North American Monsoon, which occurs earlier in the year) that drove a strong plume of deep moisture inland from the Gulf of Mexico against the Front Range foothills. The resulting floods impacted several thousands of people and many homes, roads, and businesses. To diagnose possible anthropogenic contributions to the odds of such heavy rainfall, we adapt an existing event attribution paradigm of modelling a 'world that was' for September 2013 and comparing it to a modelled 'world that might have been' for that same time but for the absence of historical anthropogenic drivers of climate. Specifically, we first perform 'world that was' simulations with the regional WRF model at 12 km resolution over North America, driven by NCEP2 re-analysis. We then re-simulate, having adjusted the re-analysis to 'world that might have been conditions' by modifying atmospheric greenhouse gas and other pollutant concentrations, temperature, humidity, and winds, as well as sea ice coverage, and sea-surface temperatures - all according to estimates from global climate model simulations. Thus our findings are highly conditional on the driving re-analysis and adjustments therein, but the setup allows us to elucidate possible mechanisms responsible for heavy Colorado rainfall in September 2013. For example, preliminary analysis suggests that, given no change in the pattern of large-scale driving weather, there is an increase in atmospheric water vapour under anthropogenic climate warming leading to a substantial increase in the odds of heavy rainfall over the Front Range.

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.

The effects of large-scale afforestation and climate change on water allocation in the Macquarie River catchment, NSW, Australia.

PubMed

Herron, Natasha; Davis, Richard; Jones, Roger

2002-08-01

Widespread afforestation has been proposed as one means of addressing the increasing dryland and stream salinity problem in Australia. However, modelling results presented here suggest that large-scale tree planting will substantially reduce river flows and impose costs on downstream water users if planted in areas of high runoff yield. Streamflow reductions in the Macquarie River, NSW, Australia are estimated for a number of tree planting scenarios and global warming forecasts. The modelling framework includes the Sacramento rainfall-runoff model and IQQM, a streamflow routing tool, as well as various global climate model outputs from which daily rainfall and potential evaporation data files have been generated in OzClim, a climate scenario generator. For a 10% increase in tree cover in the headwaters of the Macquarie, we estimate a 17% reduction in inflows to Burrendong Dam. The drying trend for a mid-range scenario of regional rainfall and potential evaporation caused by a global warming of 0.5 degree C may cause an additional 5% reduction in 2030. These flow reductions will decrease the frequency of bird-breeding events in Macquarie Marshes (a RAMSAR protected wetland) and reduce the security of supply to irrigation areas downstream. Inter-decadal climate variability is predicted to have a very significant influence on catchment hydrologic behaviour. A further 20% reduction in flows from the long-term historical mean is possible, should we move into an extended period of below average rainfall years, such as occurred in eastern Australia between 1890 and 1948. Because current consumptive water use is largely adapted to the wetter conditions of post 1949, a return to prolonged dry periods would cause significant environmental stress given the agricultural and domestic water developments that have been instituted.

On the dust load and rainfall relationship in South Asia: an analysis from CMIP5

NASA Astrophysics Data System (ADS)

Singh, Charu; Ganguly, Dilip; Dash, S. K.

2018-01-01

This study is aimed at examining the consistency of the relationship between load of dust and rainfall simulated by different climate models and its implication for the Indian summer monsoon system. Monthly mean outputs of 12 climate models, obtained from the archive of the Coupled Model Intercomparison Project phase 5 (CMIP5) for the period 1951-2004, are analyzed to investigate the relationship between dust and rainfall. Comparative analysis of the model simulated precipitation with the India Meteorological Department (IMD) gridded rainfall, CRU TS3.21 and GPCP version 2.2 data sets show significant differences between the spatial patterns of JJAS rainfall as well as annual cycle of rainfall simulated by various models and observations. Similarly, significant inter-model differences are also noted in the simulation of load of dust, nevertheless it is further noted that most of the CMIP5 models are able to capture the major dust sources across the study region. Although the scatter plot analysis and the lead-lag pattern correlation between the dust load and the rainfall show strong relationship between the dust load over distant sources and the rainfall in the South Asian region in individual models, the temporal scale of this association indicates large differences amongst the models. Our results caution that it would be pre-mature to draw any robust conclusions on the time scale of the relationship between dust and the rainfall in the South Asian region based on either CMIP5 results or limited number of previous studies. Hence, we would like to emphasize upon the fact that any conclusions drawn on the relationship between the dust load and the South Asian rainfall using model simulation is highly dependent on the degree of complexity incorporated in those models such as the representation of aerosol life cycle, their interaction with clouds, precipitation and other components of the climate system.

Thermodynamic sensitivities in observed and simulated extreme-rain-producing mesoscale convective systems

NASA Astrophysics Data System (ADS)

Schumacher, R. S.; Peters, J. M.

2015-12-01

Mesoscale convective systems (MCSs) are responsible for a large fraction of warm-season extreme rainfall events over the continental United States, as well as other midlatitude regions globally. The rainfall production in these MCSs is determined by numerous factors, including the large-scale forcing for ascent, the organization of the convection, cloud microphysical processes, and the surrounding thermodynamic and kinematic environment. Furthermore, heavy-rain-producing MCSs are most common at night, which means that well-studied mechanisms for MCS maintenance and organization such as cold pools (gravity currents) are not always at work. In this study, we use numerical model simulations and recent field observations to investigate the sensitivity of low-level MCS structures, and their influences on rainfall, to the details of the thermodynamic environment. In particular, small alterations to the initial conditions in idealized and semi-idealized simulations result in comparatively large precipitation changes, both in terms of the intensity and the spatial distribution. The uncertainties in the thermodynamic enviroments in the model simulations will be compared with high-resolution observations from the Plains Elevated Convection At Night (PECAN) field experiment in 2015. The results have implications for the paradigms of "surface-based" versus "elevated" convection, as well as for the predictability of warm-season convective rainfall.

Termites promote resistance of decomposition to spatiotemporal variability in rainfall.

PubMed

Veldhuis, Michiel P; Laso, Francisco J; Olff, Han; Berg, Matty P

2017-02-01

The ecological impact of rapid environmental change will depend on the resistance of key ecosystems processes, which may be promoted by species that exert strong control over local environmental conditions. Recent theoretical work suggests that macrodetritivores increase the resistance of African savanna ecosystems to changing climatic conditions, but experimental evidence is lacking. We examined the effect of large fungus-growing termites and other non-fungus-growing macrodetritivores on decomposition rates empirically with strong spatiotemporal variability in rainfall and temperature. Non-fungus-growing larger macrodetritivores (earthworms, woodlice, millipedes) promoted decomposition rates relative to microbes and small soil fauna (+34%) but both groups reduced their activities with decreasing rainfall. However, fungus-growing termites increased decomposition rates strongest (+123%) under the most water-limited conditions, making overall decomposition rates mostly independent from rainfall. We conclude that fungus-growing termites are of special importance in decoupling decomposition rates from spatiotemporal variability in rainfall due to the buffered environment they create within their extended phenotype (mounds), that allows decomposition to continue when abiotic conditions outside are less favorable. This points at a wider class of possibly important ecological processes, where soil-plant-animal interactions decouple ecosystem processes from large-scale climatic gradients. This may strongly alter predictions from current climate change models. © 2016 by the Ecological Society of America.

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

PubMed

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

2012-01-01

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

Increase of Coastal Cliff Rockfall Trigerred By Rainfall On The Chalk Coast of NW France During The Year 2001

NASA Astrophysics Data System (ADS)

Duperret, A.; Genter, A.; Daigneault, M.; Mortimore, R. N.

Coastal chalk cliffs exposed on each part of the English Channel suffer numerous collapses, with mean volumes varying between 10 000 and 100 000 cubic meters. Between October 1998 and October 2001, a minimum of 52 collapses have been ob- served along 120 km of the French chalk coastline located in Upper-Normandy and Picardy. The chalk coastline has evidenced 4 collapses in 1999 and 6 collapses in 2000 (winter and spring), whereas 28 collapses with volume greater than 1000 m3 was recorded in 2001 (winter, spring and summer). The increase of large-scale collapses during 2001 is interpreted as an excess of rainfalls recorded previously. Most of these collapses extend all over the vertical cliff height and are mainly controlled by ground- water infiltration. The modality of water circulation through the chalk rock depends on the chalk lithology and the hydrogeological properties of pre-existing fractures. In the framework of the European scientific project named ROCC (Risk of Cliff Col- lapse), the chalk lithology and the pre-existing fracture pattern have been investigated in order to determine the response of the rock mass to subaerial and marine solicita- tions, including rainfall conditions. Such data have been reported in a GIS system in order to determine the degree of cliff sensibility to collapses. Some rainfall-triggered collapses will be presented to illustrate the diversity of the rock mass response to rain- fall excess, in terms of rock mass characteristics and time delay: (1) a collapse was witnessed at Puys, the 17th May 2000, after two periods of intense rainfall inducing floods, during the two previous months. The occurrence of impervious marl seams levels within the chalk and its low fracture content may have generated water over- pressure and consequently stress concentration on the marl seams, which conduct to the rupture. The delay between rainfall and the rupture may be explained by the low velocity of groundwater through a poorly fractured porous chalk. (2) a series of large- scale collapses has been evidenced at Yport in June 2001, at Grandes Dalles the 15th July 2001 and at Benouville the 24th July 2001. These collapses occurred after a dry period, during the previous three months. A collapse occurred again at Yport the 27th August 2001, after an increase of rainfall during August 2001. All these sites present the same lithological chalk succession than at Puys, but their fracture pattern is made of large-scale subvertical fractures expanding all over the cliff height. Some of them 1 which correspond to dissolution pipes are filled with clays-with-flints. The sharp in- crease of collapses during the summer 2001 could be related to the superimposition of dry periods which alternate with heavy rainfalls, in karst environment. 2

Streamflow prediction using multi-site rainfall obtained from hydroclimatic teleconnection

NASA Astrophysics Data System (ADS)

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

2010-12-01

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

Continental Tele-connections of ET and Precipitation: Tractable Models, Viable Management, and Potential Monitoring.

NASA Astrophysics Data System (ADS)

Selker, J. S.; Higgins, C. W.; Tai, L. C. M.

2014-12-01

The linkage between large-scale manipulation of land cover and resulting patterns of precipitation has been a long-standing problem. For example, what is the impact of the Columbia River project's 2,700 km^2 irrigated area (applying approximately 300 m^3/s) on the down-wind continental rainfall in North America? Similarly, can we identify places on earth where planting large-scale runoff-reducing forests might increase down-wind precipitation, thus leading to magnified carbon capture? In this talk we present an analytical Lagrangian framework for the prediction of incremental increases in down-wind precipitation due to land surface evaporation and transpiration. We compare these predictions to recently published rainfall recycling values from the literature. Focus is on the Columbia basin (Pacific Northwest of hte USA), with extensions to East Africa. We further explore the monitoring requirements for verification of any such impact, and see if the planned TAHMO African Observatory (TAHMO.org) has the potential to document any such processes over the 25-year and 1,000 km scales.

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 rainfall disaggregation scheme for sub-hourly time scales: Coupling a Bartlett-Lewis based model with adjusting procedures

NASA Astrophysics Data System (ADS)

Kossieris, Panagiotis; Makropoulos, Christos; Onof, Christian; Koutsoyiannis, Demetris

2018-01-01

Many hydrological applications, such as flood studies, require the use of long rainfall data at fine time scales varying from daily down to 1 min time step. However, in the real world there is limited availability of data at sub-hourly scales. To cope with this issue, stochastic disaggregation techniques are typically employed to produce possible, statistically consistent, rainfall events that aggregate up to the field data collected at coarser scales. A methodology for the stochastic disaggregation of rainfall at fine time scales was recently introduced, combining the Bartlett-Lewis process to generate rainfall events along with adjusting procedures to modify the lower-level variables (i.e., hourly) so as to be consistent with the higher-level one (i.e., daily). In the present paper, we extend the aforementioned scheme, initially designed and tested for the disaggregation of daily rainfall into hourly depths, for any sub-hourly time scale. In addition, we take advantage of the recent developments in Poisson-cluster processes incorporating in the methodology a Bartlett-Lewis model variant that introduces dependence between cell intensity and duration in order to capture the variability of rainfall at sub-hourly time scales. The disaggregation scheme is implemented in an R package, named HyetosMinute, to support disaggregation from daily down to 1-min time scale. The applicability of the methodology was assessed on a 5-min rainfall records collected in Bochum, Germany, comparing the performance of the above mentioned model variant against the original Bartlett-Lewis process (non-random with 5 parameters). The analysis shows that the disaggregation process reproduces adequately the most important statistical characteristics of rainfall at wide range of time scales, while the introduction of the model with dependent intensity-duration results in a better performance in terms of skewness, rainfall extremes and dry proportions.

The physics of rainclouds, what is behind rainfall trends?

NASA Astrophysics Data System (ADS)

Junkermann, Wolfgang; Hacker, Jorg

2017-04-01

In several locations in the world rainfall was significantly declining during the last four decades since about 1970, despite during the same timespan the water vapor availability in the planetary boundary layer (PBL) was increasing by about five percent. Increasing water vapor levels in the PBL are a result of climate change and well in agreement with the observed one degree increase of air temperature over the oceans. Increasing water vapor availability due to an increase in evaporation should lead to a higher turnover rate within the hydrological cycle, which should result either in more frequent or in more intense rainfall. Several regional observations especially along the Australian coastline show a contrary picture. Often rainfall is less frequent and the annual rainfall is declining. Also the number of rainy days goes down. This behavior could be caused by a number of different processes affecting both, the amount of liquid water in the atmosphere and the microphysical properties of clouds. Within the discussions are: -A change in the large scale advection patterns due to global warming, shifting the trajectories of low pressure systems, a slow process that takes several decades. -A change in land use by deforestation leading to lower roughness, higher albedo and lower convective energy. Such a land use change might happen within about one decade (e.g. Western Australia). -A change in aerosol abundance. Addition of anthropogenic cloud condensation nuclei lead instantly to smaller cloud droplets and subsequently to a regional to continental scale redistribution of rainfall within the time scales of cloud lifetime (hours to days). Airborne experiments show that indeed the number of aerosols in several of the respective areas investigated up to now was increasing roughly in time with the observed rainfall changes. However, only in few of the areas the availability of historical aerosol data is sufficient for a more detailed investigation. We show results from experiments in search for physical reasons for a regional scale rainfall decline observed along the Australian coastline. Here the historical database including an airborne survey in the early 70's allows to reconstruct a 'laboratory' notebook an aerosol trends. This makes the area a perfect 'natural laboratory' for such studies on the physical background for climate change trends and to disentangle different climate / hydrological cycle relevant physical processes.

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.

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

NASA Astrophysics Data System (ADS)

Evans, Jason P.; Boyer-Souchet, Irène

2012-05-01

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

Deforestation effects on Amazon forest resilience

NASA Astrophysics Data System (ADS)

Zemp, D. C.; Schleussner, C.-F.; Barbosa, H. M. J.; Rammig, A.

2017-06-01

Through vegetation-atmosphere feedbacks, rainfall reductions as a result of Amazon deforestation could reduce the resilience on the remaining forest to perturbations and potentially lead to large-scale Amazon forest loss. We track observation-based water fluxes from sources (evapotranspiration) to sinks (rainfall) to assess the effect of deforestation on continental rainfall. By studying 21st century deforestation scenarios, we show that deforestation can reduce dry season rainfall by up to 20% far from the deforested area, namely, over the western Amazon basin and the La Plata basin. As a consequence, forest resilience is systematically eroded in the southwestern region covering a quarter of the current Amazon forest. Our findings suggest that the climatological effects of deforestation can lead to permanent forest loss in this region. We identify hot spot regions where forest loss should be avoided to maintain the ecological integrity of the Amazon forest.

The Sahel Region of West Africa: Examples of Climate Analyses Motivated By Drought Management Needs

NASA Astrophysics Data System (ADS)

Ndiaye, O.; Ward, M. N.; Siebert, A. B.

2011-12-01

The Sahel is one of the most drought-prone regions in the world. This paper focuses on climate sources of drought, and some new analyses mostly driven by users needing climate information to help in drought management strategies. The Sahel region of West Africa is a transition zone between equatorial climate and vegetation to the south, and desert to the north. The climatology of the region is dominated by dry conditions for most of the year, with a single peak in rainfall during boreal summer. The seasonal rainfall total contains both interannual variability and substantial decadal to multidecadal variability (MDV). This brings climate analysis and drought management challenges across this range of timescales. The decline in rainfall from the wet decades of the 1950s and 60s to the dry decades of the 1970s and 80s has been well documented. In recent years, a moderate recovery has emerged, with seasonal totals in the period 1994-2010 significantly higher than the average rainfall 1970-1993. These MDV rainfall fluctuations have expression in large-scale sea-surface temperature fluctuations in all ocean basins, placing the changes in drought frequency within broader ocean-atmosphere climate fluctuation. We have evaluated the changing character of low seasonal rainfall total event frequencies in the Sahel region 1950-2010, highlighting the role of changes in the mean, variance and distribution shape of seasonal rainfall totals as the climate has shifted through the three observed phases. We also consider the extent to which updating climate normals in real-time can damp the bias in expected event frequency, an important issue for the feasibility of index insurance as a drought management tool in the presence of a changing climate. On the interannual timescale, a key factor long discussed for agriculture is the character of rainfall onset. An extended dry spell often occurs early in the rainy season before the crop is fully established, and this often leads to crop failure. This can be viewed as a special case of agricultural drought. Therefore, improving climate information around the time of planting can play a key role in agricultural risk management. Rainfall onset indices have been calculated for stations across Senegal. The problem is climatically challenging because the physical processes that impact rainfall onset appear to span aspects normally studied separately: weather system character, propagating intraseasonal features, and large-scale sea-surface temperature influence. We present aspects of all these, and ideas on how to combine them into seamless information to support agriculture.

Use of Machine Learning Techniques for Identification of Robust Teleconnections to East African Rainfall Variability

NASA Technical Reports Server (NTRS)

Roberts, J. Brent; Robertson, F. R.; Funk, C.

2014-01-01

Hidden Markov models can be used to investigate structure of subseasonal variability. East African short rain variability has connections to large-scale tropical variability. MJO - Intraseasonal variations connected with appearance of "wet" and "dry" states. ENSO/IOZM SST and circulation anomalies are apparent during years of anomalous residence time in the subseasonal "wet" state. Similar results found in previous studies, but we can interpret this with respect to variations of subseasonal wet and dry modes. Reveal underlying connections between MJO/IOZM/ENSO with respect to East African rainfall.

Large scale rainfall diversity and satellite propagation

NASA Technical Reports Server (NTRS)

Lin, H. P.; Vogel, W. J.

1992-01-01

From the NOAA 15 minute precipitation file for the U.S., data was selected for 128 stations covering a 17 year period and the probability of simultaneous rainfall at several stations was calculated. We assumed that the chosen stations were located in separate beams of a multi-beam communications satellite with shared fade mitigation resources. In order to estimate the demands made on these resources, we determined the number of stations at which rainfall rates exceeded 10 to 40 mm/hr. We found a 1 percent probability that at least 5 of the 128 stations have rain at or over 10 mm/hr in any 15 minute interval. Rain at 2 stations was found to correlate over distances less than about 600 miles.

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.

Trend and variability in western and central Africa streamflow, and major drivers of variability between 1950 and 2005

NASA Astrophysics Data System (ADS)

Dieppois, B.; Sidibe, M.; Mahe, G. M.; Paturel, J. E.; Anifowose, B. A.; Lawler, D.; Amoussou, E.

2017-12-01

Unprecedented drought episodes that struck western and central Africa between the late 1960s and 1980s, triggered many studies investigating rainfall variability and its impacts on water resources and food production systems. However, most studies were focused at the catchment scale. In this study, we aim at investigating the key large-scale controls determining and modulating climate-river flows relationships at the subcontinental scale between 1950 and 2005. Using the first complete monthly streamflow data set (1950-2005) over western and central Africa, streamflow trend and variability are seasonally assessed at this subcontinental scale and compared to those observed in other hydroclimatic variables (precipitation, temperature and potential evapotranspiration). Long-term trends and variability in streamflow are mainly consistent with trends in rainfall. In particular, the recent post-1990s partial recovery in Sahel rainfall could have, at least partially, positively impacted river flows (e.g. the Senegal and Niger rivers). However, these relationships may have been moderated by: i) changes in land use; and ii) contributions from groundwater resources. In addition, the time-evolution of river flows is shown to be primarily driven by very strong decadal fluctuations, which can be interpreted as modulations in the baseflow, as determined using multi-temporal trend and continuous wavelet analysis. These decadal fluctuations, which are also significantly detected in rainfall, are likely related to large-scale sea-surface temperature (SST) anomaly patterns (such as the tropical Atlantic SST variability, the Atlantic Multidecadal Oscillation, the Interdecadal Pacific Oscillation and the Pacific Decadal Oscillation), which are together modulating the West African monsoon. Furthermore, influences of the catchment properties (e.g. size, vegetation and land use cover, soil properties, direction of stream flow across climate zones) on these decadal fluctuations in river flows have been examined. This study therefore aims to improve the ability of current global to regional climate models to simulate such ranges of variability and understand regional hydroclimate, as a means for improving the development of future scenarios for water resources in western and central Africa.

Retrieval of Latent Heating from TRMM Measurements

NASA Technical Reports Server (NTRS)

Tao, W.-K.; Smith, E. A.; Adler, R. F.; Hou, A. Y.; Meneghini, R.; Simpson, J.; Haddad, Z. S.; Iguchi, T.; Satoh, S.; Kakar, R.;

Climate change impact assessment on food security in Indonesia

NASA Astrophysics Data System (ADS)

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

2013-04-01

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

Variations in Global Precipitation: Climate-scale to Floods

NASA Technical Reports Server (NTRS)

Adler, Robert

2006-01-01

Variations in global precipitation from climate-scale to small scale are examined using satellite-based analyses of the Global Precipitation Climatology Project (GPCP) and information from the Tropical Rainfall Measuring Mission (TRMM). Global and large regional rainfall variations and possible long-term changes are examined using the 27- year (1979-2005) monthly dataset from the GPCP. In addition to global patterns associated with phenomena such as ENSO, the data set is explored for evidence of longterm change. Although the global change of precipitation in the data set is near zero, the data set does indicate a small upward trend in the Tropics (25S-25N), especially over ocean. Techniques are derived to isolate and eliminate variations due to ENS0 and major volcanic eruptions and the significance of the trend is examined. The status of TRMM estimates is examined in terms of evaluating and improving the long-term global data set. To look at rainfall variations on a much smaller scale TRMM data is used in combination with observations from other satellites to produce a 3-hr resolution, eight-year data set for examination of weather events and for practical applications such as detecting floods. Characteristics of the data set are presented and examples of recent flood events are examined.

Use NU-WRF and GCE Model to Simulate the Precipitation Processes During MC3E Campaign

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Wu, Di; Matsui, Toshi; Li, Xiaowen; Zeng, Xiping; Peter-Lidard, Christa; Hou, Arthur

2012-01-01

One of major CRM approaches to studying precipitation processes is sometimes referred to as "cloud ensemble modeling". This approach allows many clouds of various sizes and stages of their lifecycles to be present at any given simulation time. Large-scale effects derived from observations are imposed into CRMs as forcing, and cyclic lateral boundaries are used. The advantage of this approach is that model results in terms of rainfall and QI and Q2 usually are in good agreement with observations. In addition, the model results provide cloud statistics that represent different types of clouds/cloud systems during their lifetime (life cycle). The large-scale forcing derived from MC3EI will be used to drive GCE model simulations. The model-simulated results will be compared with observations from MC3E. These GCE model-simulated datasets are especially valuable for LH algorithm developers. In addition, the regional scale model with very high-resolution, NASA Unified WRF is also used to real time forecast during the MC3E campaign to ensure that the precipitation and other meteorological forecasts are available to the flight planning team and to interpret the forecast results in terms of proposed flight scenarios. Post Mission simulations are conducted to examine the sensitivity of initial and lateral boundary conditions to cloud and precipitation processes and rainfall. We will compare model results in terms of precipitation and surface rainfall using GCE model and NU-WRF

Topographic relationships for design rainfalls over Australia

NASA Astrophysics Data System (ADS)

Johnson, F.; Hutchinson, M. F.; The, C.; Beesley, C.; Green, J.

2016-02-01

Design rainfall statistics are the primary inputs used to assess flood risk across river catchments. These statistics normally take the form of Intensity-Duration-Frequency (IDF) curves that are derived from extreme value probability distributions fitted to observed daily, and sub-daily, rainfall data. The design rainfall relationships are often required for catchments where there are limited rainfall records, particularly catchments in remote areas with high topographic relief and hence some form of interpolation is required to provide estimates in these areas. This paper assesses the topographic dependence of rainfall extremes by using elevation-dependent thin plate smoothing splines to interpolate the mean annual maximum rainfall, for periods from one to seven days, across Australia. The analyses confirm the important impact of topography in explaining the spatial patterns of these extreme rainfall statistics. Continent-wide residual and cross validation statistics are used to demonstrate the 100-fold impact of elevation in relation to horizontal coordinates in explaining the spatial patterns, consistent with previous rainfall scaling studies and observational evidence. The impact of the complexity of the fitted spline surfaces, as defined by the number of knots, and the impact of applying variance stabilising transformations to the data, were also assessed. It was found that a relatively large number of 3570 knots, suitably chosen from 8619 gauge locations, was required to minimise the summary error statistics. Square root and log data transformations were found to deliver marginally superior continent-wide cross validation statistics, in comparison to applying no data transformation, but detailed assessments of residuals in complex high rainfall regions with high topographic relief showed that no data transformation gave superior performance in these regions. These results are consistent with the understanding that in areas with modest topographic relief, as for most of the Australian continent, extreme rainfall is closely aligned with elevation, but in areas with high topographic relief the impacts of topography on rainfall extremes are more complex. The interpolated extreme rainfall statistics, using no data transformation, have been used by the Australian Bureau of Meteorology to produce new IDF data for the Australian continent. The comprehensive methods presented for the evaluation of gridded design rainfall statistics will be useful for similar studies, in particular the importance of balancing the need for a continentally-optimum solution that maintains sufficient definition at the local scale.

Vertical structure and physical processes of the Madden-Julian Oscillation: Biases and uncertainties at short range

NASA Astrophysics Data System (ADS)

Xavier, Prince K.; Petch, Jon C.; Klingaman, Nicholas P.; Woolnough, Steve J.; Jiang, Xianan; Waliser, Duane E.; Caian, Mihaela; Cole, Jason; Hagos, Samson M.; Hannay, Cecile; Kim, Daehyun; Miyakawa, Tomoki; Pritchard, Michael S.; Roehrig, Romain; Shindo, Eiki; Vitart, Frederic; Wang, Hailan

2015-05-01

An analysis of diabatic heating and moistening processes from 12 to 36 h lead time forecasts from 12 Global Circulation Models are presented as part of the "Vertical structure and physical processes of the Madden-Julian Oscillation (MJO)" project. A lead time of 12-36 h is chosen to constrain the large-scale dynamics and thermodynamics to be close to observations while avoiding being too close to the initial spin-up of the models as they adjust to being driven from the Years of Tropical Convection (YOTC) analysis. A comparison of the vertical velocity and rainfall with the observations and YOTC analysis suggests that the phases of convection associated with the MJO are constrained in most models at this lead time although the rainfall in the suppressed phase is typically overestimated. Although the large-scale dynamics is reasonably constrained, moistening and heating profiles have large intermodel spread. In particular, there are large spreads in convective heating and moistening at midlevels during the transition to active convection. Radiative heating and cloud parameters have the largest relative spread across models at upper levels during the active phase. A detailed analysis of time step behavior shows that some models show strong intermittency in rainfall and differences in the precipitation and dynamics relationship between models. The wealth of model outputs archived during this project is a very valuable resource for model developers beyond the study of the MJO. In addition, the findings of this study can inform the design of process model experiments, and inform the priorities for field experiments and future observing systems.

Impacts of Wildfire on Interception Losses and Net Precipitation in a Sub-Alpine Rocky Mountain Watershed in Alberta, Canada.

NASA Astrophysics Data System (ADS)

Williams, C.; Silins, U.; Wagner, M. J.; Bladon, K. D.; Martens, A. M.; Anderson, A.; Stone, M.; Emelko, M. B.

2014-12-01

Interception of precipitation in sub-alpine forests is likely to be strongly reduced after wildfire, potentially producing large increases in net precipitation. Objectives of this study were to describe changes in rainfall and snow interception, and net precipitation after the severe 2003 Lost Creek wildfire as part of the Southern Rockies Watershed Project in the south-west Rocky Mountains of Alberta, Canada. Throughfall troughs and stemflow gauges were used to explore relationships between throughfall, stemflow, and net rainfall with variation in gross rainfall in burned and undisturbed stands during the summers of 2006-2008. These relationships were used to scale the effects of the wildfire on net rainfall for the first decade after the wildfire (2004-2013) using a 10 year rainfall record in the watershed. Annual snowpack surveys (5 snow courses in each of burned and reference stands) measured peak snowpack depth, density, and snow water equivalent (SWE) for this same period. Mean annual P was 1140 mm (684-1519 mm) during the first 10 years after the wildfire, with 61% falling as snow. Throughfall and stemflow in the burned forest accounted for 86% and 7% of gross rainfall, respectively, compared with 53% and 0.002% in the unburned stands in the summers of 2006-2008. Scaled rainfall interception relationships (=f(rainfall event size)) indicated annual increases in net rainfall were 192 mm/yr (133-347 mm) for 10 years after the fire. Similarly, mean increases in peak SWE were 134 mm/yr (93-216 mm). Collectively, the mean increase in net precipitation was 325 mm/yr (226-563 mm; 29%) for the first decade after the wildfire. Hydrologic forcing by increased net precipitation may be a particularly important element of wildfire impacts on sub-alpine watersheds. Furthermore, because of the very slow growth rates of sub-alpine forests, increases in net precipitation are likely to persist and affect precipitation-runoff relationships for decades in these environments.

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

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

The role of Natural Flood Management in managing floods in large scale basins during extreme events

NASA Astrophysics Data System (ADS)

Quinn, Paul; Owen, Gareth; ODonnell, Greg; Nicholson, Alex; Hetherington, David

2016-04-01

There is a strong evidence database showing the negative impacts of land use intensification and soil degradation in NW European river basins on hydrological response and to flood impact downstream. However, the ability to target zones of high runoff production and the extent to which we can manage flood risk using nature-based flood management solution are less known. A move to planting more trees and having less intense farmed landscapes is part of natural flood management (NFM) solutions and these methods suggest that flood risk can be managed in alternative and more holistic ways. So what local NFM management methods should be used, where in large scale basin should they be deployed and how does flow is propagate to any point downstream? Generally, how much intervention is needed and will it compromise food production systems? If we are observing record levels of rainfall and flow, for example during Storm Desmond in Dec 2015 in the North West of England, what other flood management options are really needed to complement our traditional defences in large basins for the future? In this paper we will show examples of NFM interventions in the UK that have impacted at local scale sites. We will demonstrate the impact of interventions at local, sub-catchment (meso-scale) and finally at the large scale. These tools include observations, process based models and more generalised Flood Impact Models. Issues of synchronisation and the design level of protection will be debated. By reworking observed rainfall and discharge (runoff) for observed extreme events in the River Eden and River Tyne, during Storm Desmond, we will show how much flood protection is needed in large scale basins. The research will thus pose a number of key questions as to how floods may have to be managed in large scale basins in the future. We will seek to support a method of catchment systems engineering that holds water back across the whole landscape as a major opportunity to management water in large scale basins in the future. The broader benefits of engineering landscapes to hold water for pollution control, sediment loss and drought minimisation will also be shown.

Southern Hemisphere rainfall variability over the past 200 years

NASA Astrophysics Data System (ADS)

Gergis, Joëlle; Henley, Benjamin J.

2017-04-01

This study presents an analysis of three palaeoclimate rainfall reconstructions from the Southern Hemisphere regions of south-eastern Australia (SEA), southern South Africa (SAF) and southern South America (SSA). We provide a first comparison of rainfall variations in these three regions over the past two centuries, with a focus on identifying synchronous wet and dry periods. Despite the uncertainties associated with the spatial and temporal limitations of the rainfall reconstructions, we find evidence of dynamically-forced climate influences. An investigation of the twentieth century relationship between regional rainfall and the large-scale climate circulation features of the Pacific, Indian and Southern Ocean regions revealed that Indo-Pacific variations of the El Niño-Southern Oscillation (ENSO) and the Indian Ocean dipole dominate rainfall variability in SEA and SAF, while the higher latitude Southern Annular Mode (SAM) exerts a greater influence in SSA. An assessment of the stability of the regional rainfall-climate circulation modes over the past two centuries revealed a number of non-stationarities, the most notable of which occurs during the early nineteenth century around 1820. This corresponds to a time when the influence of ENSO on SEA, SAF and SSA rainfall weakens and there is a strengthening of the influence of SAM. We conclude by advocating the use of long-term palaeoclimate data to estimate decadal rainfall variability for future water resource management.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

Large scale pre-rain vegetation green up across Africa.

PubMed

Adole, Tracy; Dash, Jadunandan; Atkinson, Peter M

2018-05-16

Information on the response of vegetation to different environmental drivers, including rainfall, forms a critical input to ecosystem models. Currently, such models are run based on parameters that, in some cases, are either assumed or lack supporting evidence (e.g., that vegetation growth across Africa is rainfall-driven). A limited number of studies have reported that the onset of rain across Africa does not fully explain the onset of vegetation growth, for example, drawing on the observation of pre-rain flush effects in some parts of Africa. The spatial extent of this pre-rain green-up effect, however, remains unknown, leaving a large gap in our understanding that may bias ecosystem modelling. This paper provides the most comprehensive spatial assessment to-date of the magnitude and frequency of the different patterns of phenology response to rainfall across Africa, and for different vegetation types. To define the relations between phenology and rainfall, we investigated the spatial variation in the difference, in number of days, between the start of rainy season (SRS) and start of vegetation growing season (SOS); and between the end of rainy season (ERS) and end of vegetation growing season (EOS). We reveal a much more extensive spread of pre-rain green-up over Africa than previously reported, with pre-rain green-up being the norm rather than the exception. We also show the relative sparsity of post-rain green-up, confined largely to the Sudano-Sahel region. While the pre-rain green-up phenomenon is well documented, its large spatial extent was not anticipated. Our results, thus, contrast with the widely held view that rainfall drives the onset and end of the vegetation growing season across Africa. Our findings point to a much more nuanced role of rainfall in Africa's vegetation growth cycle than previously thought, specifically as one of a set of several drivers, with important implications for ecosystem modelling. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Mixing to Monsoons: Air-Sea Interactions in the Bay of Bengal

NASA Astrophysics Data System (ADS)

Lucas, A. J.; Shroyer, E. L.; Wijesekera, H. W.; Fernando, H. J. S.; D'Asaro, E.; Ravichandran, M.; Jinadasa, S. U. P.; MacKinnon, J. A.; Nash, J. D.; Sharma, R.; Centurioni, L.; Farrar, J. T.; Weller, R.; Pinkel, R.; Mahadevan, A.; Sengupta, D.; Tandon, A.

2014-07-01

More than 1 billion people depend on rainfall from the South Asian monsoon for their livelihoods. Summertime monsoonal precipitation is highly variable on intraseasonal time scales, with alternating "active" and "break" periods. These intraseasonal oscillations in large-scale atmospheric convection and winds are closely tied to 1°C-2°C variations of sea surface temperature in the Bay of Bengal.

Legume abundance along successional and rainfall gradients in Neotropical forests.

PubMed

Gei, Maga; Rozendaal, Danaë M A; Poorter, Lourens; Bongers, Frans; Sprent, Janet I; Garner, Mira D; Aide, T Mitchell; Andrade, José Luis; Balvanera, Patricia; Becknell, Justin M; Brancalion, Pedro H S; Cabral, George A L; César, Ricardo Gomes; Chazdon, Robin L; Cole, Rebecca J; Colletta, Gabriel Dalla; de Jong, Ben; Denslow, Julie S; Dent, Daisy H; DeWalt, Saara J; Dupuy, Juan Manuel; Durán, Sandra M; do Espírito Santo, Mário Marcos; Fernandes, G Wilson; Nunes, Yule Roberta Ferreira; Finegan, Bryan; Moser, Vanessa Granda; Hall, Jefferson S; Hernández-Stefanoni, José Luis; Junqueira, André B; Kennard, Deborah; Lebrija-Trejos, Edwin; Letcher, Susan G; Lohbeck, Madelon; Marín-Spiotta, Erika; Martínez-Ramos, Miguel; Meave, Jorge A; Menge, Duncan N L; Mora, Francisco; Muñoz, Rodrigo; Muscarella, Robert; Ochoa-Gaona, Susana; Orihuela-Belmonte, Edith; Ostertag, Rebecca; Peña-Claros, Marielos; Pérez-García, Eduardo A; Piotto, Daniel; Reich, Peter B; Reyes-García, Casandra; Rodríguez-Velázquez, Jorge; Romero-Pérez, I Eunice; Sanaphre-Villanueva, Lucía; Sanchez-Azofeifa, Arturo; Schwartz, Naomi B; de Almeida, Arlete Silva; Almeida-Cortez, Jarcilene S; Silver, Whendee; de Souza Moreno, Vanessa; Sullivan, Benjamin W; Swenson, Nathan G; Uriarte, Maria; van Breugel, Michiel; van der Wal, Hans; Veloso, Maria das Dores Magalhães; Vester, Hans F M; Vieira, Ima Célia Guimarães; Zimmerman, Jess K; Powers, Jennifer S

2018-05-28

The nutrient demands of regrowing tropical forests are partly satisfied by nitrogen-fixing legume trees, but our understanding of the abundance of those species is biased towards wet tropical regions. Here we show how the abundance of Leguminosae is affected by both recovery from disturbance and large-scale rainfall gradients through a synthesis of forest inventory plots from a network of 42 Neotropical forest chronosequences. During the first three decades of natural forest regeneration, legume basal area is twice as high in dry compared with wet secondary forests. The tremendous ecological success of legumes in recently disturbed, water-limited forests is likely to be related to both their reduced leaflet size and ability to fix N 2 , which together enhance legume drought tolerance and water-use efficiency. Earth system models should incorporate these large-scale successional and climatic patterns of legume dominance to provide more accurate estimates of the maximum potential for natural nitrogen fixation across tropical forests.

Scale Dependence of Spatiotemporal Intermittence of Rain

NASA Technical Reports Server (NTRS)

Kundu, Prasun K.; Siddani, Ravi K.

2011-01-01

It is a common experience that rainfall is intermittent in space and time. This is reflected by the fact that the statistics of area- and/or time-averaged rain rate is described by a mixed distribution with a nonzero probability of having a sharp value zero. In this paper we have explored the dependence of the probability of zero rain on the averaging space and time scales in large multiyear data sets based on radar and rain gauge observations. A stretched exponential fannula fits the observed scale dependence of the zero-rain probability. The proposed formula makes it apparent that the space-time support of the rain field is not quite a set of measure zero as is sometimes supposed. We also give an ex.planation of the observed behavior in tenus of a simple probabilistic model based on the premise that rainfall process has an intrinsic memory.

A monsoon-like Southwest Australian circulation and its relation with rainfall in Southwest Western Australia

NASA Astrophysics Data System (ADS)

Feng, Juan; Li, Jianping; Li, Yun

2010-05-01

Using the NCEP/NCAR, ERA-40 reanalysis, and precipitation data from CMAP and Australian Bureau of Meteorology, the variability and circulation features influencing the southwest Western Australia (SWWA) winter rainfall are investigated. It is found that the climate of southwest Australia bears a strong seasonality in the annual cycle and exhibits a monsoon-like atmospheric circulation, which is termed as the southwest Australian circulation (SWAC) for its several distinct features characterizing a monsoonal circulation: the seasonal reversal of winds, alternate wet and dry seasons, and an evident land-sea thermal contrast. The seasonal march of the SWAC in extended winter (May to October) is demonstrated by pentad data. An index based on the dynamics normalized seasonality was introduced to describe the behavior and variation of the winter SWAC. It is found that the winter rainfall over SWWA has a significant positive correlation with the SWAC index in both early (May to July) and late (August to October) winter. In weaker winter SWAC years there is an anti-cyclonic anomaly over southern Indian Ocean resulting in weaker westerlies and northerlies which are not favorable for more rainfall over SWWA, and the opposite combination is true in the stronger winter SWAC years. The SWAC explains not only a large portion of the interannual variability of SWWA rainfall in both early and late winter, but also the long term drying trend over SWWA in early winter. The well-coupled SWAC-SWWA rainfall relationship seems to be largely independent of the well-known effects of large-scale atmospheric circulations such as the Southern Hemisphere Annular Mode (SAM), El Niño/Southern Oscillation (ENSO), Indian Ocean Dipole (IOD) and ENSO Modoki (EM). The result offers qualified support for the argument that the monsoon-like circulation may contribute to the rainfall decline in early winter over SWWA.

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.

Multifractal characterisation of a simulated surface flow: A case study with Multi-Hydro in Jouy-en-Josas, France

NASA Astrophysics Data System (ADS)

Gires, Auguste; Abbes, Jean-Baptiste; da Silva Rocha Paz, Igor; Tchiguirinskaia, Ioulia; Schertzer, Daniel

2018-03-01

In this paper we suggest to innovatively use scaling laws and more specifically Universal Multifractals (UM) to analyse simulated surface runoff and compare the retrieved scaling features with the rainfall ones. The methodology is tested on a 3 km2 semi-urbanised with a steep slope study area located in the Paris area along the Bièvre River. First Multi-Hydro, a fully distributed model is validated on this catchment for four rainfall events measured with the help of a C-band radar. The uncertainty associated with small scale unmeasured rainfall, i.e. occurring below the 1 km × 1 km × 5 min observation scale, is quantified with the help of stochastic downscaled rainfall fields. It is rather significant for simulated flow and more limited on overland water depth for these rainfall events. Overland depth is found to exhibit a scaling behaviour over small scales (10 m-80 m) which can be related to fractal features of the sewer network. No direct and obvious dependency between the overland depth multifractal features (quality of the scaling and UM parameters) and the rainfall ones was found.

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.

The impact of simulated mesoscale convective systems on global precipitation: A multiscale modeling study

NASA Astrophysics Data System (ADS)

Tao, Wei-Kuo; Chern, Jiun-Dar

2017-06-01

The importance of precipitating mesoscale convective systems (MCSs) has been quantified from TRMM precipitation radar and microwave imager retrievals. MCSs generate more than 50% of the rainfall in most tropical regions. MCSs usually have horizontal scales of a few hundred kilometers (km); therefore, a large domain with several hundred km is required for realistic simulations of MCSs in cloud-resolving models (CRMs). Almost all traditional global and climate models do not have adequate parameterizations to represent MCSs. Typical multiscale modeling frameworks (MMFs) may also lack the resolution (4 km grid spacing) and domain size (128 km) to realistically simulate MCSs. The impact of MCSs on precipitation is examined by conducting model simulations using the Goddard Cumulus Ensemble (GCE, a CRM) model and Goddard MMF that uses the GCEs as its embedded CRMs. Both models can realistically simulate MCSs with more grid points (i.e., 128 and 256) and higher resolutions (1 or 2 km) compared to those simulations with fewer grid points (i.e., 32 and 64) and low resolution (4 km). The modeling results also show the strengths of the Hadley circulations, mean zonal and regional vertical velocities, surface evaporation, and amount of surface rainfall are weaker or reduced in the Goddard MMF when using more CRM grid points and higher CRM resolution. In addition, the results indicate that large-scale surface evaporation and wind feedback are key processes for determining the surface rainfall amount in the GMMF. A sensitivity test with reduced sea surface temperatures shows both reduced surface rainfall and evaporation.

The role of storm scale, position and movement in controlling urban flood response

NASA Astrophysics Data System (ADS)

ten Veldhuis, Marie-claire; Zhou, Zhengzheng; Yang, Long; Liu, Shuguang; Smith, James

2018-01-01

The impact of spatial and temporal variability of rainfall on hydrological response remains poorly understood, in particular in urban catchments due to their strong variability in land use, a high degree of imperviousness and the presence of stormwater infrastructure. In this study, we analyze the effect of storm scale, position and movement in relation to basin scale and flow-path network structure on urban hydrological response. A catalog of 279 peak events was extracted from a high-quality observational dataset covering 15 years of flow observations and radar rainfall data for five (semi)urbanized basins ranging from 7.0 to 111.1 km2 in size. Results showed that the largest peak flows in the event catalog were associated with storm core scales exceeding basin scale, for all except the largest basin. Spatial scale of flood-producing storm events in the smaller basins fell into two groups: storms of large spatial scales exceeding basin size or small, concentrated events, with storm core much smaller than basin size. For the majority of events, spatial rainfall variability was strongly smoothed by the flow-path network, increasingly so for larger basin size. Correlation analysis showed that position of the storm in relation to the flow-path network was significantly correlated with peak flow in the smallest and in the two more urbanized basins. Analysis of storm movement relative to the flow-path network showed that direction of storm movement, upstream or downstream relative to the flow-path network, had little influence on hydrological response. Slow-moving storms tend to be associated with higher peak flows and longer lag times. Unexpectedly, position of the storm relative to impervious cover within the basins had little effect on flow peaks. These findings show the importance of observation-based analysis in validating and improving our understanding of interactions between the spatial distribution of rainfall and catchment variability.

Tropical Rainfall Variability on Interannual-to-Interdecadal/Longer-Time Scales Derived from the GPCP Monthly Product

NASA Technical Reports Server (NTRS)

Gu, Guojun; Adler, Robert F.; Huffman, George J.; Curtis, Scott

2006-01-01

Global and large regional rainfall variations and possible long-term changes are examined using the 26-year (1979-2004) GPCP monthly dataset (Adler et al., 2003). Our emphasis is to discriminate among variations due to ENSO, volcanic events, and possible long-term climate changes in the tropics. Although the global linear change of precipitation in the data set is near zero during the time period, an increase in tropical rainfall is noted, with a weaker decrease over northern hemisphere middle latitudes. Focusing on the tropics (25degS-25degN), the data set indicates an upward trend (0.06 mm/day/decade) and a downward trend (-0.02 mm/day/decade) over tropical ocean and land, respectively. This corresponds to an about 4.9% increase (ocean) and 1.6% decrease (land) during the entire 26-year time period. Techniques are applied to isolate and quantify variations due to ENSO and two major volcanic eruptions (El Chichon, March 1982; Pinatubo, June 1991) in order to examine longer time-scale changes. The ENSO events generally do not impact the tropical total rainfall, but, of course, induce significant anomalies with opposite signs over tropical land and ocean. The impact of the two volcanic eruptions is estimated to be about a 5% reduction in tropical rainfall over both land and ocean. A modified data set (with ENSO and volcano effects removed) retains the same approximate linear change slopes, but with reduced variance, thereby increasing the confidence levels associated with the long-term rainfall changes in the tropics 2

Piecewise Disassembly of a Large-Herbivore Community across a Rainfall Gradient: The UHURU Experiment

PubMed Central

Palmer, Todd M.; Charles, Grace K.; Helgen, Kristofer M.; Kinyua, Stephen N.; Maclean, Janet E.; Turner, Benjamin L.; Young, Hillary S.

2013-01-01

Large mammalian herbivores (LMH) strongly influence plant communities, and these effects can propagate indirectly throughout food webs. Most existing large-scale manipulations of LMH presence/absence consist of a single exclusion treatment, and few are replicated across environmental gradients. Thus, important questions remain about the functional roles of different LMH, and how these roles depend on abiotic context. In September 2008, we constructed a series of 1-ha herbivore-exclusion plots across a 20-km rainfall gradient in central Kenya. Dubbed "UHURU" (Ungulate Herbivory Under Rainfall Uncertainty), this experiment aims to illuminate the ecological effects of three size classes of LMH, and how rainfall regimes shape the direction and magnitude of these effects. UHURU consists of four treatments: total-exclusion (all ungulate herbivores), mesoherbivore-exclusion (LMH >120-cm tall), megaherbivore-exclusion (elephants and giraffes), and unfenced open plots. Each treatment is replicated three times at three locations (“sites”) along the rainfall gradient: low (440 mm/year), intermediate (580 mm/year), and high (640 mm/year). There was limited variation across sites in soil attributes and LMH activity levels. Understory-plant cover was greater in plots without mesoherbivores, but did not respond strongly to the exclusion of megaherbivores, or to the additional exclusion of dik-dik and warthog. Eleven of the thirteen understory plant species that responded significantly to exclusion treatment were more common in exclusion plots than open ones. Significant interactions between site and treatment on plant communities, although uncommon, suggested that differences between treatments may be greater at sites with lower rainfall. Browsers reduced densities of several common overstory species, along with growth rates of the three dominant Acacia species. Small-mammal densities were 2–3 times greater in total-exclusion than in open plots at all sites. Although we expect patterns to become clearer with time, results from 2008–2012 show that the effects of excluding successively smaller-bodied subsets of the LMH community are generally non-additive for a given response variable, and inconsistent across response variables, indicating that the different LMH size classes are not functionally redundant. Several response variables showed significant treatment-by-site interactions, suggesting that the nature of plant-herbivore interactions can vary across restricted spatial scales. PMID:23405122

Piecewise disassembly of a large-herbivore community across a rainfall gradient: the UHURU experiment.

PubMed

Goheen, Jacob R; Palmer, Todd M; Charles, Grace K; Helgen, Kristofer M; Kinyua, Stephen N; Maclean, Janet E; Turner, Benjamin L; Young, Hillary S; Pringle, Robert M

2013-01-01

Large mammalian herbivores (LMH) strongly influence plant communities, and these effects can propagate indirectly throughout food webs. Most existing large-scale manipulations of LMH presence/absence consist of a single exclusion treatment, and few are replicated across environmental gradients. Thus, important questions remain about the functional roles of different LMH, and how these roles depend on abiotic context. In September 2008, we constructed a series of 1-ha herbivore-exclusion plots across a 20-km rainfall gradient in central Kenya. Dubbed "UHURU" (Ungulate Herbivory Under Rainfall Uncertainty), this experiment aims to illuminate the ecological effects of three size classes of LMH, and how rainfall regimes shape the direction and magnitude of these effects. UHURU consists of four treatments: total-exclusion (all ungulate herbivores), mesoherbivore-exclusion (LMH >120-cm tall), megaherbivore-exclusion (elephants and giraffes), and unfenced open plots. Each treatment is replicated three times at three locations ("sites") along the rainfall gradient: low (440 mm/year), intermediate (580 mm/year), and high (640 mm/year). There was limited variation across sites in soil attributes and LMH activity levels. Understory-plant cover was greater in plots without mesoherbivores, but did not respond strongly to the exclusion of megaherbivores, or to the additional exclusion of dik-dik and warthog. Eleven of the thirteen understory plant species that responded significantly to exclusion treatment were more common in exclusion plots than open ones. Significant interactions between site and treatment on plant communities, although uncommon, suggested that differences between treatments may be greater at sites with lower rainfall. Browsers reduced densities of several common overstory species, along with growth rates of the three dominant Acacia species. Small-mammal densities were 2-3 times greater in total-exclusion than in open plots at all sites. Although we expect patterns to become clearer with time, results from 2008-2012 show that the effects of excluding successively smaller-bodied subsets of the LMH community are generally non-additive for a given response variable, and inconsistent across response variables, indicating that the different LMH size classes are not functionally redundant. Several response variables showed significant treatment-by-site interactions, suggesting that the nature of plant-herbivore interactions can vary across restricted spatial scales.

Mitigation of Sri Lanka Island Effects in Colombo Sounding Data during DYNAMO

NASA Astrophysics Data System (ADS)

Ciesielski, P. E.; Johnson, R. H.; Yoneyama, K.

2013-12-01

During the Dynamics of the MJO (DYNAMO) field campaign, upper-air soundings were launched at Colombo, Sri Lanka as part of the enhanced northern sounding array (NSA) of the experiment. The Colombo soundings were affected at low-levels by diurnal heating of this large island and by flow blocking due to elevated terrain to the east of the Colombo site. Because of the large spacing between sounding sites, these small-scale effects are aliased onto the larger scale impacting analyses and atmospheric budgets over the DYNAMO NSA. To mitigate these local island effects on the large-scale budgets, a procedure was designed which uses ECMWF-analyzed fields in the vicinity of Sri Lanka to estimate open-ocean conditions (i.e, as if this island were not present). These 'unperturbed' ECMWF fields at low-levels are then merged with observed Colombo soundings. This procedure effectively mutes the blocking effects and large diurnal cycle observed in the low-level Colombo fields. In westerly flow regimes, adjusted Colombo winds increase the low-level westerlies by 2-3 m/s with a similar increase of the low-level easterlies in easterly flow regimes. In general, over the NSA the impact of the adjusted Colombo winds results in more low-level divergence (convergence), more mid-level subsidence (rising motion) and reduced (increased) rainfall during the westerly (easterly) wind regimes. In comparison to independent TRMM rainfall estimates, both the mean budget-derived rainfall and its temporal correlation are improved by using the adjusted Colombo soundings. In addition, use of the 'unperturbed' fields result in a more realistic moisture budget analyses, both in its diurnal cycle and during the build-up phase of the November MJO when a gradual deepening of apparent drying was observed. Overall, use of the adjusted Colombo soundings appears to have a beneficial impact on the NSA analyses and budgets.

Uganda rainfall variability and prediction

NASA Astrophysics Data System (ADS)

Jury, Mark R.

2018-05-01

This study analyzes large-scale controls on Uganda's rainfall. Unlike past work, here, a May-October season is used because of the year-round nature of agricultural production, vegetation sensitivity to rainfall, and disease transmission. The Uganda rainfall record exhibits steady oscillations of ˜3 and 6 years over 1950-2013. Correlation maps at two-season lead time resolve the subtropical ridge over global oceans as an important feature. Multi-variate environmental predictors include Dec-May south Indian Ocean sea surface temperature, east African upper zonal wind, and South Atlantic wind streamfunction, providing a 33% fit to May-Oct rainfall time series. Composite analysis indicates that cool-phase El Niño Southern Oscillation supports increased May-Oct Uganda rainfall via a zonal overturning lower westerly/upper easterly atmospheric circulation. Sea temperature anomalies are positive in the east Atlantic and negative in the west Indian Ocean in respect of wet seasons. The northern Hadley Cell plays a role in limiting the northward march of the equatorial trough from May to October. An analysis of early season floods found that moist inflow from the west Indian Ocean converges over Uganda, generating diurnal thunderstorm clusters that drift southwestward producing high runoff.

Stochastic extreme downscaling model for an assessment of changes in rainfall intensity-duration-frequency curves over South Korea using multiple regional climate models

NASA Astrophysics Data System (ADS)

So, Byung-Jin; Kim, Jin-Young; Kwon, Hyun-Han; Lima, Carlos H. R.

2017-10-01

A conditional copula function based downscaling model in a fully Bayesian framework is developed in this study to evaluate future changes in intensity-duration frequency (IDF) curves in South Korea. The model incorporates a quantile mapping approach for bias correction while integrated Bayesian inference allows accounting for parameter uncertainties. The proposed approach is used to temporally downscale expected changes in daily rainfall, inferred from multiple CORDEX-RCMs based on Representative Concentration Pathways (RCPs) 4.5 and 8.5 scenarios, into sub-daily temporal scales. Among the CORDEX-RCMs, a noticeable increase in rainfall intensity is observed in the HadGem3-RA (9%), RegCM (28%), and SNU_WRF (13%) on average, whereas no noticeable changes are observed in the GRIMs (-2%) for the period 2020-2050. More specifically, a 5-30% increase in rainfall intensity is expected in all of the CORDEX-RCMs for 50-year return values under the RCP 8.5 scenario. Uncertainty in simulated rainfall intensity gradually decreases toward the longer durations, which is largely associated with the enhanced strength of the relationship with the 24-h annual maximum rainfalls (AMRs). A primary advantage of the proposed model is that projected changes in future rainfall intensities are well preserved.

Evaluating rainfall kinetic energy - intensity relationships with observed disdrometric data

NASA Astrophysics Data System (ADS)

Angulo-Martinez, Marta; Begueria, Santiago; Latorre, Borja

2016-04-01

Rainfall kinetic energy is required for determining erosivity, the ability of rainfall to detach soil particles and initiate erosion. Its determination relay on the use of disdrometers, i.e. devices capable of measuring the drop size distribution and velocity of falling raindrops. In the absence of such devices, rainfall kinetic energy is usually estimated with empirical expressions relating rainfall energy and intensity. We evaluated the performance of 14 rainfall energy equations in estimating one-minute rainfall energy and event total energy, in comparison with observed data from 821 rainfall episodes (more than 100 thousand one-minute observations) by means of an optical disdrometer. In addition, two sources of bias when using such relationships were evaluated: i) the influence of using theoretical terminal raindrop fall velocities instead of measured values; and ii) the influence of time aggregation (rainfall intensity data every 5-, 10-, 15-, 30-, and 60-minutes). Empirical relationships did a relatively good job when complete events were considered (R2 > 0.82), but offered poorer results for within-event (one-minute resolution) variation. Also, systematic biases where large for many equations. When raindrop size distribution was known, estimating the terminal fall velocities by empirical laws produced good results even at fine time resolution. The influence of time aggregation was very high in the estimated kinetic energy, although linear scaling may allow empirical correction. This results stress the importance of considering all these effects when rainfall energy needs to be estimated from more standard precipitation records. , and recommends the use of disdrometer data to locally determine rainfall kinetic energy.

Effect of rainfall simulator and plot scale on overland flow and phosphorus transport.

PubMed

Sharpley, Andrew; Kleinman, Peter

2003-01-01

Rainfall simulation experiments are widely used to study erosion and contaminant transport in overland flow. We investigated the use of two rainfall simulators designed to rain on 2-m-long (2-m2) and 10.7-m-long (32.6-m2) plots to estimate overland flow and phosphorus (P) transport in comparison with watershed-scale data. Simulated rainfall (75 mm h(-1)) generated more overland flow from 2-m-long (20 L m2) than from 10.7-m-long (10 L m2) plots established in grass, no-till corn (Zea mays L.), and recently tilled fields, because a relatively greater area of the smaller plots became saturated (>75% of area) during rainfall compared with large plots (<75% area). Although average concentrations of dissolved reactive phosphorus (DRP) in overland flow were greater from 2-m-long (0.50 mg L(-1)) than 10.7-m-long (0.35 mg L(-1)) plots, the relationship between DRP and Mehlich-3 soil P (as defined by regression slope) was similar for both plots and for published watershed data (0.0022 for grassed, 0.0036 for no-till, and 0.0112 for tilled sites). Conversely, sediment, particulate phosphorus (PP), and total phosphorus (TP) concentrations and selective transport of soil fines (<2 microm) were significantly lower from 2- than 10.7-m-long plots. However, slopes of the logarithmic regression between P enrichment ratio and sediment discharge were similar (0.281-0.301) for 2- and 10.7-m-long plots, and published watershed data. While concentrations and loads of P change with plot scales, processes governing DRP and PP transport in overland flow are consistent, supporting the limited use of small plots and rainfall simulators to assess the relationship between soil P and overland flow P as a function of soil type and management.

Rainfall variability over the tropical Pacific from July 1987 through December 1991 as inferred via monthly estimates from SSM/I

NASA Technical Reports Server (NTRS)

Berg, Wesley; Avery, Susan K.

1994-01-01

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 preiod from July 1987 through December 1991. The monthly estimates were calibrated using measurements from a network of Pacific atoll rain gauges and compared to other satellite-based rainfall estimation techniques. Based on these monthly estimates, an analysis of the variability of large-scale features over intraseasonal to interannual timescales has been performed. While the major precipitation features as well as the seasonal variability distributions show good agreement with expected values, the presence of a moderately intense El Nino during 1986-87 and an intense La Nina during 1988-89 highlights this time period.

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

NASA Astrophysics Data System (ADS)

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

2017-11-01

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

Spectral analysis of temporal non-stationary rainfall-runoff processes

NASA Astrophysics Data System (ADS)

Chang, Ching-Min; Yeh, Hund-Der

2018-04-01

This study treats the catchment as a block box system with considering the rainfall input and runoff output being a stochastic process. The temporal rainfall-runoff relationship at the catchment scale is described by a convolution integral on a continuous time scale. Using the Fourier-Stieltjes representation approach, a frequency domain solution to the convolution integral is developed to the spectral analysis of runoff processes generated by temporal non-stationary rainfall events. It is shown that the characteristic time scale of rainfall process increases the runoff discharge variability, while the catchment mean travel time constant plays the role in reducing the variability of runoff discharge. Similar to the behavior of groundwater aquifers, catchments act as a low-pass filter in the frequency domain for the rainfall input signal.

Heating Structures Derived from Satellite

NASA Technical Reports Server (NTRS)

Tao, W.-K.; Adler, R.; Haddad, Z.; Hou, A.; Kakar, R.; Krishnamurti, T. N.; Kummerow, C.; Lang, S.; Meneghini, R.; Olson, W.

2004-01-01

Rainfall is a key link in the hydrologic cycle and is a primary heat source for the atmosphere. The vertical distribution of latent-heat release, which is accompanied by rainfall, modulates the large-scale circulations of the tropics and in turn can impact midlatitude weather. This latent heat release is a consequence of phase changes between vapor, liquid, and solid water. The Tropical Rainfall Measuring Mission (TRMM), a joint U.S./Japan space project, was launched in November 1997. It provides an accurate measurement of rainfall over the global tropics which can be used to estimate the four-dimensional structure of latent heating over the global tropics. The distributions of rainfall and inferred heating can be used to advance our understanding of the global energy and water cycle. This paper describes several different algorithms for estimating latent heating using TRMM observations. The strengths and weaknesses of each algorithm as well as the heating products are also discussed. The validation of heating products will be exhibited. Finally, the application of this heating information to global circulation and climate models is presented.

Modelling landscape evolution at the flume scale

NASA Astrophysics Data System (ADS)

Cheraghi, Mohsen; Rinaldo, Andrea; Sander, Graham C.; Barry, D. Andrew

2017-04-01

The ability of a large-scale Landscape Evolution Model (LEM) to simulate the soil surface morphological evolution as observed in a laboratory flume (1-m × 2-m surface area) was investigated. The soil surface was initially smooth, and was subjected to heterogeneous rainfall in an experiment designed to avoid rill formation. Low-cohesive fine sand was placed in the flume while the slope and relief height were 5 % and 20 cm, respectively. Non-uniform rainfall with an average intensity of 85 mm h-1 and a standard deviation of 26 % was applied to the sediment surface for 16 h. We hypothesized that the complex overland water flow can be represented by a drainage discharge network, which was calculated via the micro-morphology and the rainfall distribution. Measurements included high resolution Digital Elevation Models that were captured at intervals during the experiment. The calibrated LEM captured the migration of the main flow path from the low precipitation area into the high precipitation area. Furthermore, both model and experiment showed a steep transition zone in soil elevation that moved upstream during the experiment. We conclude that the LEM is applicable under non-uniform rainfall and in the absence of surface incisions, thereby extending its applicability beyond that shown in previous applications. Keywords: Numerical simulation, Flume experiment, Particle Swarm Optimization, Sediment transport, River network evolution model.

The Tropical Rainfall Measuring Mission (TRMM) Progress Report

NASA Technical Reports Server (NTRS)

Simpson, Joanne; Meneghini, Robert; Kummerow, Christian D.; Meneghini, Robert; Hou, Arthur; Adler, Robert F.; Huffman, George; Barkstrom, Bruce; Wielicki, Bruce; Goodman, Steve

1999-01-01

Recognizing the importance of rain in the tropics and the accompanying latent heat release, NASA for the U.S. and NASDA for Japan have partnered in the design, construction and flight of an Earth Probe satellite to measure tropical rainfall and calculate the associated heating. Primary mission goals are 1) the understanding of crucial links in climate variability by the hydrological cycle, 2) improvement in the large-scale models of weather and climate 3) Improvement in understanding cloud ensembles and their impacts on larger scale circulations. The linkage with the tropical oceans and landmasses are also emphasized. The Tropical Rainfall Measuring Mission (TRMM) satellite was launched in November 1997 with fuel enough to obtain a four to five year data set of rainfall over the global tropics from 37'N to 37'S. This paper reports progress from launch date through the spring of 1999. The data system and its products and their access is described, as are the algorithms used to obtain the data. Some exciting early results from TRMM are described. Some important algorithm improvements are shown. These will be used in the first total data reprocessing, scheduled to be complete in early 2000. The reader is given information on how to access and use the data.

The Tropical Rainfall Measuring Mission (TRMM)

NASA Technical Reports Server (NTRS)

Simpson, Joanne; Kummerow, Christian D.; Meneghini, Robert; Hou, Arthur; Adler, Robert F.; Huffman, George; Barkstrom, Bruce; Wielicki, Bruce; Goodman, Steven J.; Christian, Hugh;

Documentary evidence of historical floods and extreme rainfall events in Sweden 1400-1800

NASA Astrophysics Data System (ADS)

Retsö, D.

2015-03-01

This article explores documentary evidence of floods and extreme rainfall events in Sweden in the pre-instrumental period (1400-1800). The survey shows that two sub-periods can be considered as flood-rich, 1590-1670 and the early 18th century. The result related to a low degree of human impact on hydrology during the period, suggests that climatic factors, such as lower temperatures and increased precipitation connected to the so-called Little Ice Age rather than large-scale atmospheric circulation patterns, should be considered as the main driver behind flood frequency and magnitude.

Centrifuge Modeling of Rainfall Induced Slope Failure

NASA Astrophysics Data System (ADS)

Ling, H.; Wu, M.

2006-12-01

Rainfall induces slope failure and debris flow which are considered as one of the major natural disasters. The scope of such failure is very large and it cannot be studied easily in the laboratory. Traditionally, small scale model tests are used to study such problem. Knowing that the behavior of soil is affected by the stress level, centrifuge modeling technique has been used to simulate more realistically full scale earth structures. In this study, two series of tests were conducted on slopes under the centrifugal field with and without the presence of rainfall. The soil used was a mixture of sand and 15 percent fines. The slopes of angle 60 degrees were prepared at optimum water content in order to achieve the maximum density. In the first series of tests, three different slope heights of 10 cm, 15 cm and 20 cm were used. The gravity was increased gradually until slope failure in order to obtain the prototype failure height. The slope model was cut after the test in order to obtain the configuration of failure surface. It was found that the slope geometry normalized by the height at failure provided unique results. Knowing the slope height or gravity at failure, the second series of tests with rainfall were conducted slightly below the critical height. That is, after attaining the desired gravity, the rainfall was induced in the centrifuge. Special nozzles were used and calibrated against different levels of gravity in order to obtain desired rainfall intensity. Five different rainfall intensities were used on the 15-cm slopes at 80g and 60g, which corresponded to 12 m and 9 m slope height, respectively. The duration until failure for different rainfall intensities was obtained. Similar to the first series of tests, the slope model was cut and investigated after the test. The results showed that the failure surface was not significantly affected by the rainfall. That is, the excess pore pressure induced by rainfall generated slope failure. The prediction curves of rainfall intensity versus duration were obtained from the test results. Such curves are extremely useful for disaster management. This study indicated feasibilities of using centrifuge modeling technique in simulating rainfall induced slope failure. The results obtained may also be used for validating numerical tools.

The potential of urban rainfall monitoring with crowdsourced automatic weather stations in Amsterdam

NASA Astrophysics Data System (ADS)

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

2017-02-01

The high density of built-up areas and resulting imperviousness of the land surface makes urban areas vulnerable to extreme rainfall, which can lead to considerable damage. In order to design and manage cities to be able to deal with the growing number of extreme rainfall events, rainfall data are required at higher temporal and spatial resolutions than those needed for rural catchments. However, the density of operational rainfall monitoring networks managed by local or national authorities is typically low in urban areas. A growing number of automatic personal weather stations (PWSs) link rainfall measurements to online platforms. Here, we examine the potential of such crowdsourced datasets for obtaining the desired resolution and quality of rainfall measurements for the capital of the Netherlands. Data from 63 stations in Amsterdam (˜ 575 km2) that measure rainfall over at least 4 months in a 17-month period are evaluated. In addition, a detailed assessment is made of three Netatmo stations, the largest contributor to this dataset, in an experimental setup. The sensor performance in the experimental setup and the density of the PWS network are promising. However, features in the online platforms, like rounding and thresholds, cause changes from the original time series, resulting in considerable errors in the datasets obtained. These errors are especially large during low-intensity rainfall, although they can be reduced by accumulating rainfall over longer intervals. Accumulation improves the correlation coefficient with gauge-adjusted radar data from 0.48 at 5 min intervals to 0.60 at hourly intervals. Spatial rainfall correlation functions derived from PWS data show much more small-scale variability than those based on gauge-adjusted radar data and those found in similar research using dedicated rain gauge networks. This can largely be attributed to the noise in the PWS data resulting from both the measurement setup and the processes occurring in the data transfer to the online PWS platform. A double mass comparison with gauge-adjusted radar data shows that the median of the stations resembles the rainfall reference better than the real-time (unadjusted) radar product. Averaging nearby raw PWS measurements further improves the match with gauge-adjusted radar data in that area. These results confirm that the growing number of internet-connected PWSs could successfully be used for urban rainfall monitoring.

Urban rainfall monitoring with crowdsourced automatic weather stations in Amsterdam

NASA Astrophysics Data System (ADS)

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

2017-04-01

The high density of built-up areas and resulting imperviousness of the land surface makes urban areas vulnerable to extreme rainfall, which can lead to considerable damage. In order to design and manage cities to be able to deal with the growing number of extreme rainfall events, rainfall data is required at higher temporal and spatial resolutions than those needed for rural catchments. However, the density of operational rainfall monitoring networks managed by local or national authorities is typically low in urban areas. A growing number of automatic personal weather stations (PWSs) link rainfall measurements to online platforms. Here, we examine the potential of such crowdsourced datasets for obtaining the desired resolution and quality of rainfall measurements for the capital of the Netherlands. Data from 63 stations in Amsterdam (˜575 km2}) that measure rainfall over at least 4 months in a 17-month period are evaluated. In addition, a detailed assessment is made of three Netatmo stations, the largest contributor to this dataset, in an experimental set-up. The sensor performance in the experimental set-up and the density of the PWS-network are promising. However, features in the online platforms, like rounding and thresholds, cause changes from the original time series, resulting in considerable errors in the datasets obtained. These errors are especially large during low intensity rainfall, although they can be reduced by accumulating rainfall over longer intervals. Accumulation improves the correlation coefficient with gauge-adjusted radar data from 0.48 at 5 min intervals to 0.60 at hourly intervals. Spatial rainfall correlation functions derived from PWS data show much more small-scale variability than those based on gauge-adjusted radar data and those found in similar research using dedicated rain gauge networks. This can largely be attributed to the noise in the PWS data resulting from both the measurement setup and the processes occurring in the data transfer to the online PWS-platform. A double mass comparison with gauge-adjusted radar data shows that the median of the stations resembles the rainfall reference better than the real-time (unadjusted) radar product. Averaging nearby raw PWS measurements further improves the match with gauge-adjusted radar data in that area. These results confirm that the growing number of internet-connected PWSs could successfully be used for urban rainfall monitoring.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Cosmic ray soil moisture observing systems comos in cap fields at El Reno Oklahoma

USDA-ARS?s Scientific Manuscript database

Soil water content (SWC) partitions rainfall into runoff and infiltration, modulates surface and atmospheric exchanges of water and energy, affects plant growth and crop yields, and impacts chemical and biological activities of soil, among other things. Thus, SWC, especially over large scales, is a...

The impact of inter-annual rainfall variability on food production in the Ganges basin

NASA Astrophysics Data System (ADS)

Siderius, Christian; Biemans, Hester; van Walsum, Paul; hellegers, Petra; van Ierland, Ekko; Kabat, Pavel

2014-05-01

Rainfall variability is expected to increase in the coming decades as the world warms. Especially in regions already water stressed, a higher rainfall variability will jeopardize food security. Recently, the impact of inter-annual rainfall variability has received increasing attention in regional to global analysis on water availability and food security. But the description of the dynamics behind it is still incomplete in most models. Contemporary land surface and hydrological models used for such analyses describe variability in production primarily as a function of yield, a process driven by biophysical parameters, thereby neglecting yearly variations in cropped area, a process driven largely by management decisions. Agricultural statistics for northern India show that the latter process could explain up to 40% of the observed inter-annual variation in food production in various states. We added a simple dynamic land use decision module to a land surface model (LPJmL) and analyzed to what extent this improved the estimation of variability in food production. Using this improved modelling framework we then assessed if and at which scale rainfall variability affects meeting the food self-sufficiency threshold. Early results for the Ganges Basin indicate that, while on basin level variability in crop production is still relatively low, several districts and states are highly affected (RSTD > 50%). Such insight can contribute to better recommendations on the most effective measures, at the most appropriate scale, to buffer variability in food production.

North Indian heavy rainfall event during June 2013: diagnostics and extended range prediction

NASA Astrophysics Data System (ADS)

Joseph, Susmitha; Sahai, A. K.; Sharmila, S.; Abhilash, S.; Borah, N.; Chattopadhyay, R.; Pillai, P. A.; Rajeevan, M.; Kumar, Arun

2015-04-01

The Indian summer monsoon of 2013 covered the entire country by 16 June, one month earlier than its normal date. Around that period, heavy rainfall was experienced in the north Indian state of Uttarakhand, which is situated on the southern slope of Himalayan Ranges. The heavy rainfall and associated landslides caused serious damages and claimed many lives. This study investigates the scientific rationale behind the incidence of the extreme rainfall event in the backdrop of large scale monsoon environment. It is found that a monsoonal low pressure system that provided increased low level convergence and abundant moisture, and a midlatitude westerly trough that generated strong upper level divergence, interacted with each other and helped monsoon to cover the entire country and facilitated the occurrence of the heavy rainfall event in the orographic region. The study also examines the skill of an ensemble prediction system (EPS) in predicting the Uttarakhand event on extended range time scale. The EPS is implemented on both high (T382) and low (T126) resolution versions of the coupled general circulation model CFSv2. Although the models predicted the event 10-12 days in advance, they failed to predict the midlatitude influence on the event. Possible reasons for the same are also discussed. In both resolutions of the model, the event was triggered by the generation and northwestward movement of a low pressure system developed over the Bay of Bengal. The study advocates the usefulness of high resolution models in predicting extreme events.

Censored rainfall modelling for estimation of fine-scale extremes

NASA Astrophysics Data System (ADS)

Cross, David; Onof, Christian; Winter, Hugo; Bernardara, Pietro

2018-01-01

Reliable estimation of rainfall extremes is essential for drainage system design, flood mitigation, and risk quantification. However, traditional techniques lack physical realism and extrapolation can be highly uncertain. In this study, we improve the physical basis for short-duration extreme rainfall estimation by simulating the heavy portion of the rainfall record mechanistically using the Bartlett-Lewis rectangular pulse (BLRP) model. Mechanistic rainfall models have had a tendency to underestimate rainfall extremes at fine temporal scales. Despite this, the simple process representation of rectangular pulse models is appealing in the context of extreme rainfall estimation because it emulates the known phenomenology of rainfall generation. A censored approach to Bartlett-Lewis model calibration is proposed and performed for single-site rainfall from two gauges in the UK and Germany. Extreme rainfall estimation is performed for each gauge at the 5, 15, and 60 min resolutions, and considerations for censor selection discussed.

Vertical structure and physical processes of the Madden-Julian Oscillation: Biases and uncertainties at short range

DOE PAGES

Xavier, Prince K.; Petch, Jon C.; Klingaman, Nicholas P.; ...

2015-05-26

We present an analysis of diabatic heating and moistening processes from 12 to 36 h lead time forecasts from 12 Global Circulation Models as part of the “Vertical structure and physical processes of the Madden-Julian Oscillation (MJO)” project. A lead time of 12–36 h is chosen to constrain the large-scale dynamics and thermodynamics to be close to observations while avoiding being too close to the initial spin-up of the models as they adjust to being driven from the Years of Tropical Convection (YOTC) analysis. A comparison of the vertical velocity and rainfall with the observations and YOTC analysis suggests thatmore » the phases of convection associated with the MJO are constrained in most models at this lead time although the rainfall in the suppressed phase is typically overestimated. Although the large-scale dynamics is reasonably constrained, moistening and heating profiles have large intermodel spread. In particular, there are large spreads in convective heating and moistening at midlevels during the transition to active convection. Radiative heating and cloud parameters have the largest relative spread across models at upper levels during the active phase. A detailed analysis of time step behavior shows that some models show strong intermittency in rainfall and differences in the precipitation and dynamics relationship between models. In conclusion, the wealth of model outputs archived during this project is a very valuable resource for model developers beyond the study of the MJO. Additionally, the findings of this study can inform the design of process model experiments, and inform the priorities for field experiments and future observing systems.« less

Nonlinear effects of microtopography on macroscopic rainfall-runoff partitioning a the hillslope scale: a modelling study

NASA Astrophysics Data System (ADS)

Caviedes-Voullième, Daniel; Domin, Andrea; Hinz, Christoph

2017-04-01

The quantitative description and prediction of hydrological response of hillslopes or hillslope-scale catchments to rainfall events is becoming evermore relevant. At the hillslope scale, the onset of runoff and the overall rainfall-runoff transformation are controlled by multiple interacting small-scale processes, that, when acting together produce a response described in terms of hydrological variables well-defined at the catchment and hillslope scales. We hypothesize that small scale features such microtopography of the land surface will will govern large scale signatures of temporal runoff evolution. This can be tested directly by numerical modelling of well-defined surface geometries and adequate process description. It requires a modelling approach consistent with fundamental fluid mechanics, well-designed numerical methods, and computational efficiency. In this work, an idealized rectangular domain representing a hillslope with an idealized 2D sinusoidal microtopography is studied by simulating surface water redistribution by means of a 2D diffusive-wave (zero-inertia) shallow water model. By studying more than 500 surfaces and performing extensive sensitivity analysis forced by a single rainfall pulse, the dependency of characteristic hydrological responses to microtopographical properties was assessed. Despite of the simplicity of periodic surface and the rain event, results indicate complex surface flow dynamics during the onset of runoff observed at the macro and micro scales. Macro scale regimes were defined in terms of characteristics hydrograph shapes and those were related to surface geometry. The reference regime was defined for smooth topography and consisted of a simple hydrograph with smoothly rising and falling limbs with an intermediate steady state. In constrast, rough surface geometry yields stepwise rising limbs and shorter steady states. Furthermore, the increase in total infiltration over the whole domain relative to the smooth reference case shows a strong non-linear dependency on slope and the ratio of the characteristic wavelength and amplitude of microtopography. The coupled analysis of spatial and hydrological results also suggests that the hydrological behaviour can be explained by the spatiotemporal variations triggered by surface connectivity. This study significantly extents previous work on 1D domains, as our results reveal complexities that require 2D representation of the runoff processes.

A new perspective on the regional hydrologic cycle over North and South America

NASA Astrophysics Data System (ADS)

Weng, Shu-Ping

The GEOS-1 vertically-integrated 3-hr moisture flux reanalyses and hourly-gridded United States station precipitation plus a satellite-based, 6-hr global precipitation estimate were employed to investigate the impacts of nocturnal low-level jets (LLJs) on the regional hydrological cycle over the central United States (Part I) and the subtropical plains of South America (Part II). Research stressed the influences of upper-level synoptic-scale waves (i.e., synoptic-scale forcings) upon the regional hydrologic processes, which were explored by the impacts associated with the occurrence of LLJ. Besides the conventional budget analysis, the adopted `synoptic-forcing approach' was proven illustrative in describing these impacts through the down-scaling process of LLJs. In Part 1, the major findings include: (1)the seasonal-averaged hydrological cycle over the Great Plains is strongly affected by the occurrence of GPLLJ, (2)the synoptic-scale forcing provided by the upper-level propagating jet (ULJ) streams is essential in generating the large-scale precipitation after the GPLLJ forms from the diurnal boundary layer process, (3)without the dynamic coupling between the ULJ and LLJ, the impact of LLJ on the hydrological cycle is demonstrated to be less important, and (4)the importance of synoptic-scale forcings in preconditioning the setting of wet/dry seasons in the interannual variability of rainfall anomaly is further illustrated by examining the changes of intensity as well as the occurrence frequency between the different types of LLJ. In Part II of this study, it was found that the occurrence of Andean LLJ represents a transient episode that detours the climatic rainfall activity along the South Atlantic Convergent Zone (SACZ) to the subtropical plains (Brazilian Nordeste) in its southwestern (northeastern) flank. The appearance of a seesaw pattern in the rainfall and flux convergence anomalies along the southeastern portion of South America, which is spatially in quadrature with the seasonal mean circulation, reflects the synoptic-scale forcing generated by the upper-level propagating transient-scale waves. In this regard, the function of the Andean LLJ in providing a scale-interaction mechanism that links the synoptic-scale setting with the localized rainfall event is the same as the GPLLJ. Due to the unique geographic background such as the narrow east-west landmass extension and the relative orientation between the Andean LLJ and the ULJ, however, the enhanced rainfall activity over the subtropical plains in response to the perturbed flux convergence is smaller than the case in the GPLLJ.

Use of isotopic spike from Tropical Storm to understand water exchange on large scale: study case of Rafael Storm in the Lesser Antilles archipelago, October 2012.

NASA Astrophysics Data System (ADS)

Lambs, Luc

2014-05-01

Aim The tracking of the rainfall from Tropical Storm Raphael of mid October 2012 was used to better understand how the eco-hydrology and the water cycle function in wet areas, such as mangrove growing in salty ponds on a number of tropical islands. Location Guadeloupe and Saint Martin Islands in the Leeward Islands archipelago, Lesser Antilles. Methods Compared to normal tropical rainfall, tropical storms display distinct depleted heavy stable water isotopes which can be used as isotopic spikes to understand these special rainfall inflows. Rainfall, groundwater, river and pond water were sampled before, during and after the storm. Results In Guadeloupe where the tropical storm started, the rainfall isotopic signal reached values of d18O= -9 to -8 o on October 12-14th 2012, whereas the normal range is d18O= -4 to -2 o as measured from 2009 to 2012. It was possible to detect such a depleted signal in the groundwater and in the mangrove forest during the days after the storm event. Main conclusions The use of such natural isotopic spikes provides an opportunity to obtain a dynamic and time reference on a large scale for the study of the hydro-ecosystems and the effects on the impacted tropical islands. A few days after the cyclone, the isotopic spikes were found in river, groundwater and mangrove water pools with values up to d18O= -8.6 o . For the water basins on the windward side, the downhill salty pond water was almost completely renewed. By contrast, only 20 to 50 % of the water in the ponds located on the leeward side was renewed. No specific elevation in the d-excess values was noted, certainly due to the relatively long distance from the eye of the storm (180 to 300 km), which meant that there was no spray water evaporative process.

Attribution of extreme rainfall from Hurricane Harvey, August 2017

NASA Astrophysics Data System (ADS)

van Oldenborgh, Geert Jan; van der Wiel, Karin; Sebastian, Antonia; Singh, Roop; Arrighi, Julie; Otto, Friederike; Haustein, Karsten; Li, Sihan; Vecchi, Gabriel; Cullen, Heidi

2017-12-01

During August 25-30, 2017, Hurricane Harvey stalled over Texas and caused extreme precipitation, particularly over Houston and the surrounding area on August 26-28. This resulted in extensive flooding with over 80 fatalities and large economic costs. It was an extremely rare event: the return period of the highest observed three-day precipitation amount, 1043.4 mm 3dy-1 at Baytown, is more than 9000 years (97.5% one-sided confidence interval) and return periods exceeded 1000 yr (750 mm 3dy-1) over a large area in the current climate. Observations since 1880 over the region show a clear positive trend in the intensity of extreme precipitation of between 12% and 22%, roughly two times the increase of the moisture holding capacity of the atmosphere expected for 1 °C warming according to the Clausius-Clapeyron (CC) relation. This would indicate that the moisture flux was increased by both the moisture content and stronger winds or updrafts driven by the heat of condensation of the moisture. We also analysed extreme rainfall in the Houston area in three ensembles of 25 km resolution models. The first also shows 2 × CC scaling, the second 1 × CC scaling and the third did not have a realistic representation of extreme rainfall on the Gulf Coast. Extrapolating these results to the 2017 event, we conclude that global warming made the precipitation about 15% (8%-19%) more intense, or equivalently made such an event three (1.5-5) times more likely. This analysis makes clear that extreme rainfall events along the Gulf Coast are on the rise. And while fortifying Houston to fully withstand the impact of an event as extreme as Hurricane Harvey may not be economically feasible, it is critical that information regarding the increasing risk of extreme rainfall events in general should be part of the discussion about future improvements to Houston’s flood protection system.

Studies of regional-scale climate variability and change. Hidden Markov models and coupled ocean-atmosphere modes

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

Ghil, M.; Kravtsov, S.; Robertson, A. W.

2008-10-14

This project was a continuation of previous work under DOE CCPP funding, in which we had developed a twin approach of probabilistic network (PN) models (sometimes called dynamic Bayesian networks) and intermediate-complexity coupled ocean-atmosphere models (ICMs) to identify the predictable modes of climate variability and to investigate their impacts on the regional scale. We had developed a family of PNs (similar to Hidden Markov Models) to simulate historical records of daily rainfall, and used them to downscale GCM seasonal predictions. Using an idealized atmospheric model, we had established a novel mechanism through which ocean-induced sea-surface temperature (SST) anomalies might influencemore » large-scale atmospheric circulation patterns on interannual and longer time scales; we had found similar patterns in a hybrid coupled ocean-atmosphere-sea-ice model. The goal of the this continuation project was to build on these ICM results and PN model development to address prediction of rainfall and temperature statistics at the local scale, associated with global climate variability and change, and to investigate the impact of the latter on coupled ocean-atmosphere modes. Our main results from the grant consist of extensive further development of the hidden Markov models for rainfall simulation and downscaling together with the development of associated software; new intermediate coupled models; a new methodology of inverse modeling for linking ICMs with observations and GCM results; and, observational studies of decadal and multi-decadal natural climate results, informed by ICM results.« less

The significance of spatial variability of rainfall on streamflow: A synthetic analysis at the Upper Lee catchment, UK

NASA Astrophysics Data System (ADS)

Pechlivanidis, Ilias; McIntyre, Neil; Wheater, Howard

2017-04-01

Rainfall, one of the main inputs in hydrological modeling, is a highly heterogeneous process over a wide range of scales in space, and hence the ignorance of the spatial rainfall information could affect the simulated streamflow. Calibration of hydrological model parameters is rarely a straightforward task due to parameter equifinality and parameters' 'nature' to compensate for other uncertainties, i.e. structural and forcing input. In here, we analyse the significance of spatial variability of rainfall on streamflow as a function of catchment scale and type, and antecedent conditions using the continuous time, semi-distributed PDM hydrological model at the Upper Lee catchment, UK. The impact of catchment scale and type is assessed using 11 nested catchments ranging in scale from 25 to 1040 km2, and further assessed by artificially changing the catchment characteristics and translating these to model parameters with uncertainty using model regionalisation. Synthetic rainfall events are introduced to directly relate the change in simulated streamflow to the spatial variability of rainfall. Overall, we conclude that the antecedent catchment wetness and catchment type play an important role in controlling the significance of the spatial distribution of rainfall on streamflow. Results show a relationship between hydrograph characteristics (streamflow peak and volume) and the degree of spatial variability of rainfall for the impermeable catchments under dry antecedent conditions, although this decreases at larger scales; however this sensitivity is significantly undermined under wet antecedent conditions. Although there is indication that the impact of spatial rainfall on streamflow varies as a function of catchment scale, the variability of antecedent conditions between the synthetic catchments seems to mask this significance. Finally, hydrograph responses to different spatial patterns in rainfall depend on assumptions used for model parameter estimation and also the spatial variation in parameters indicating the need of an uncertainty framework in such investigation.

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.

Role of moisture transport for Central American precipitation

NASA Astrophysics Data System (ADS)

María Durán-Quesada, Ana; Gimeno, Luis; Amador, Jorge

2017-02-01

A climatology of moisture sources linked with Central American precipitation was computed based upon Lagrangian trajectories for the analysis period 1980-2013. The response of the annual cycle of precipitation in terms of moisture supply from the sources was analysed. Regional precipitation patterns are mostly driven by moisture transport from the Caribbean Sea (CS). Moisture supply from the eastern tropical Pacific (ETPac) and northern South America (NSA) exhibits a strong seasonal pattern but weaker compared to CS. The regional distribution of rainfall is largely influenced by a local signal associated with surface fluxes during the first part of the rainy season, whereas large-scale dynamics forces rainfall during the second part of the rainy season. The Caribbean Low Level Jet (CLLJ) and the Chocó Jet (CJ) are the main conveyors of regional moisture, being key to define the seasonality of large-scale forced rainfall. Therefore, interannual variability of rainfall is highly dependent of the regional LLJs to the atmospheric variability modes. The El Niño-Southern Oscillation (ENSO) was found to be the dominant mode affecting moisture supply for Central American precipitation via the modulation of regional phenomena. Evaporative sources show opposite anomaly patterns during warm and cold ENSO phases, as a result of the strengthening and weakening, respectively, of the CLLJ during the summer months. Trends in both moisture supply and precipitation over the last three decades were computed, results suggest that precipitation trends are not homogeneous for Central America. Trends in moisture supply from the sources identified show a marked north-south seesaw, with an increasing supply from the CS Sea to northern Central America. Long-term trends in moisture supply are larger for the transition months (March and October). This might have important implications given that any changes in the conditions seen during the transition to the rainy season may induce stronger precipitation trends.

Convective Mode and Mesoscale Heavy Rainfall Forecast Challenges during a High-Impact Weather Period along the Gulf Coast and Florida from 17-20 May 2016

NASA Astrophysics Data System (ADS)

Bosart, L. F.; Wallace, B. C.

2017-12-01

Two high-impact convective storm forecast challenges occurred between 17-20 May 2016 during NOAA's Hazardous Weather Testbed Spring Forecast Experiment (SFE) at the Storm Prediction Center. The first forecast challenge was 286 mm of unexpected record-breaking rain that fell on Vero Beach (VRB), Florida, between 1500 UTC 17 May and 0600 UTC 18 May, more than doubling the previous May daily rainfall record. The record rains in VRB occurred subsequent to the formation of a massive MCS over the central Gulf of Mexico between 0900-1000 UTC 17 May. This MCS, linked to the earlier convection associated with an anomalously strong subtropical jet (STJ) over the Gulf of Mexico, moved east-northeastward toward Florida. The second forecast challenge was a large MCS that formed over the Mexican mountains near the Texas-Mexican border, moved eastward and grew upscale prior to 1200 UTC 19 May. This MCS further strengthened offshore after 1800 UTC 19 May beneath the STJ. SPC SFE participants expected this MCS to move east-northeastward and bring heavy rain due to training echoes along the Gulf coast as far eastward as the Florida panhandle. Instead, this MCS transitioned into a bowing MCS that resembled a low-end derecho and produced a 4-6 hPa cold pool with widespread surface wind gusts between 35-50 kt. Both MCS events occurred in a large-scale baroclinic environment along the northern Gulf coast. Both MCS events responded to antecedent convection within this favorable large-scale environment. Rainfall amounts with the first heavy rain-producing MCS were severely underestimated by models and forecasters alike. The second MCS produced the greatest forecaster angst because rainfall totals were forecast too high (MCS propagated too fast) and severe wind reports were much more widespread than anticipated (because of cold pool formation). This presentation will attempt to untangle what happened and why it happened.

Rainfall-enhanced blooming in typhoon wakes

PubMed Central

Lin, Y.-C.; Oey, L.-Y.

2016-01-01

Strong phytoplankton blooming in tropical-cyclone (TC) wakes over the oligotrophic oceans potentially contributes to long-term changes in global biogeochemical cycles. Yet blooming has traditionally been discussed using anecdotal events and its biophysical mechanics remain poorly understood. Here we identify dominant blooming patterns using 16 years of ocean-color data in the wakes of 141 typhoons in western North Pacific. We observe right-side asymmetric blooming shortly after the storms, attributed previously to sub-mesoscale re-stratification, but thereafter a left-side asymmetry which coincides with the left-side preference in rainfall due to the large-scale wind shear. Biophysical model experiments and observations demonstrate that heavier rainfall freshens the near-surface water, leading to stronger stratification, decreased turbulence and enhanced blooming. Our results suggest that rainfall plays a previously unrecognized, critical role in TC-induced blooming, with potentially important implications for global biogeochemical cycles especially in view of the recent and projected increases in TC-intensity that harbingers stronger mixing and heavier rain under the storm. PMID:27545899

Rainfall-enhanced blooming in typhoon wakes.

PubMed

Lin, Y-C; Oey, L-Y

2016-08-22

Strong phytoplankton blooming in tropical-cyclone (TC) wakes over the oligotrophic oceans potentially contributes to long-term changes in global biogeochemical cycles. Yet blooming has traditionally been discussed using anecdotal events and its biophysical mechanics remain poorly understood. Here we identify dominant blooming patterns using 16 years of ocean-color data in the wakes of 141 typhoons in western North Pacific. We observe right-side asymmetric blooming shortly after the storms, attributed previously to sub-mesoscale re-stratification, but thereafter a left-side asymmetry which coincides with the left-side preference in rainfall due to the large-scale wind shear. Biophysical model experiments and observations demonstrate that heavier rainfall freshens the near-surface water, leading to stronger stratification, decreased turbulence and enhanced blooming. Our results suggest that rainfall plays a previously unrecognized, critical role in TC-induced blooming, with potentially important implications for global biogeochemical cycles especially in view of the recent and projected increases in TC-intensity that harbingers stronger mixing and heavier rain under the storm.

Rainfall-enhanced blooming in typhoon wakes

NASA Astrophysics Data System (ADS)

Lin, Y.-C.; Oey, L.-Y.

2016-08-01

Strong phytoplankton blooming in tropical-cyclone (TC) wakes over the oligotrophic oceans potentially contributes to long-term changes in global biogeochemical cycles. Yet blooming has traditionally been discussed using anecdotal events and its biophysical mechanics remain poorly understood. Here we identify dominant blooming patterns using 16 years of ocean-color data in the wakes of 141 typhoons in western North Pacific. We observe right-side asymmetric blooming shortly after the storms, attributed previously to sub-mesoscale re-stratification, but thereafter a left-side asymmetry which coincides with the left-side preference in rainfall due to the large-scale wind shear. Biophysical model experiments and observations demonstrate that heavier rainfall freshens the near-surface water, leading to stronger stratification, decreased turbulence and enhanced blooming. Our results suggest that rainfall plays a previously unrecognized, critical role in TC-induced blooming, with potentially important implications for global biogeochemical cycles especially in view of the recent and projected increases in TC-intensity that harbingers stronger mixing and heavier rain under the storm.

Rainfall-enhanced blooming in typhoon wakes

NASA Astrophysics Data System (ADS)

Lin, Y.; Oey, L. Y.

2016-12-01

Strong phytoplankton blooming in tropical-cyclone (TC) wakes over the oligotrophic oceans potentially contributes to long-term changes in global biogeochemical cycles. Yet blooming has traditionally been discussed using anecdotal events and its biophysical mechanics remain poorly understood. Here we identify dominant blooming patterns using 16 years of ocean-color data in the wakes of 141 typhoons in western North Pacific. We observe right-side asymmetric blooming shortly after the storms, attributed previously to sub-mesoscale re-stratification, but thereafter a left-side asymmetry which coincides with the left-side preference in rainfall due to the large-scale wind shear. Biophysical model experiments and observations demonstrate that heavier rainfall freshens the near-surface water, leading to stronger stratification, decreased turbulence and enhanced blooming. Our results suggest that rainfall plays a previously unrecognized, critical role in TC-induced blooming, with potentially important implications for global biogeochemical cycles especially in view of the recent and projected increases in TC-intensity that harbingers stronger mixing and heavier rain under the storm.

A New Look at Rainfall Fluctuations and Scaling Properties of Spatial Rainfall Using Orthogonal Wavelets.

NASA Astrophysics Data System (ADS)

Kumar, Praveen; Foufoula-Georgiou, Efi

1993-02-01

It has been observed that the finite-dimensional distribution functions of rainfall cannot obey simple scaling laws due to rainfall intermittency (mixed distribution with an atom at zero) and the probability of rainfall being an increasing function of area. Although rainfall fluctuations do not suffer these limitations, it is interesting to note that very few attempts have been made to study them in terms of their self-similarity characteristics. This is due to the lack of unambiguous definition of fluctuations in multidimensions. This paper shows that wavelet transforms offer a convenient and consistent method for the decomposition of inhomogeneous and anisotropic rainfall fields in two dimensions and that the components of this decomposition can be looked at as fluctuations of the rainfall field. It is also shown that under some mild assumptions, the component fields can be treated as homogeneous and thus are amenable to second-order analysis, which can provide useful insight into the nature of the process. The fact that wavelet transforms are a space-scale method also provides a convenient tool to study scaling characteristics of the process. Orthogonal wavelets are used, and these properties are investigated for a squall-line storm to study the presence of self-similarity.

A new look at rainfall fluctuations and scaling properties of spatial rainfall using orthogonal wavelets

NASA Technical Reports Server (NTRS)

Kumar, Praveen; Foufoula-Georgiou, Efi

1993-01-01

It has been observed that the finite-dimensional distribution functions of rainfall cannot obey simple scaling laws due to rainfall intermittency (mixed distribution with an atom at zero) and the probability of rainfall being an increasing function of area. Although rainfall fluctuations do not suffer these limitations, it is interesting to note that very few attempts have been made to study them in terms of their self-similarity characteristics. This is due to the lack of unambiguous definition of fluctuations in multidimensions. This paper shows that wavelet transforms offer a convenient and consistent method for the decomposition of inhomogeneous and anisotropic rainfall fields in two dimensions and that the components of this decomposition can be looked at as fluctuations of the rainfall field. It is also shown that under some mild assumptions, the component fields can be treated as homogeneous and thus are amenable to second-order analysis, which can provide useful insight into the nature of the process. The fact that wavelet transforms are a space-scale method also provides a convenient tool to study scaling characteristics of the process. Orthogonal wavelets are used, and these properties are investigated for a squall-line storm to study the presence of self-similarity.

From GCM grid cell to agricultural plot: scale issues affecting modelling of climate impact

PubMed Central

Baron, Christian; Sultan, Benjamin; Balme, Maud; Sarr, Benoit; Traore, Seydou; Lebel, Thierry; Janicot, Serge; Dingkuhn, Michael

2005-01-01

General circulation models (GCM) are increasingly capable of making relevant predictions of seasonal and long-term climate variability, thus improving prospects of predicting impact on crop yields. This is particularly important for semi-arid West Africa where climate variability and drought threaten food security. Translating GCM outputs into attainable crop yields is difficult because GCM grid boxes are of larger scale than the processes governing yield, involving partitioning of rain among runoff, evaporation, transpiration, drainage and storage at plot scale. This study analyses the bias introduced to crop simulation when climatic data is aggregated spatially or in time, resulting in loss of relevant variation. A detailed case study was conducted using historical weather data for Senegal, applied to the crop model SARRA-H (version for millet). The study was then extended to a 10°N–17° N climatic gradient and a 31 year climate sequence to evaluate yield sensitivity to the variability of solar radiation and rainfall. Finally, a down-scaling model called LGO (Lebel–Guillot–Onibon), generating local rain patterns from grid cell means, was used to restore the variability lost by aggregation. Results indicate that forcing the crop model with spatially aggregated rainfall causes yield overestimations of 10–50% in dry latitudes, but nearly none in humid zones, due to a biased fraction of rainfall available for crop transpiration. Aggregation of solar radiation data caused significant bias in wetter zones where radiation was limiting yield. Where climatic gradients are steep, these two situations can occur within the same GCM grid cell. Disaggregation of grid cell means into a pattern of virtual synoptic stations having high-resolution rainfall distribution removed much of the bias caused by aggregation and gave realistic simulations of yield. It is concluded that coupling of GCM outputs with plot level crop models can cause large systematic errors due to scale incompatibility. These errors can be avoided by transforming GCM outputs, especially rainfall, to simulate the variability found at plot level. PMID:16433096

The Influence of the Madden-Julian Oscillation (mjo) on Extreme Rainfall Over the Central and Southern Peruvian Andes

NASA Astrophysics Data System (ADS)

Heidinger, H.; Jones, C.; Carvalho, L. V.

2015-12-01

Extreme rainfall is important for the Andean region because of the large contribution of these events to the seasonal totals and consequent impacts on water resources for agriculture, water consumption, industry and hydropower generation, as well as the occurrence of floods and landslides. Over Central and Southern Peruvian Andes (CSPA), rainfall exceeding the 90th percentile contributed between 44 to 100% to the total Nov-Mar 1979-2010 rainfall. Additionally, precipitation from a large majority of stations in the CSPA exhibits statistically significant spectral peaks on intraseasonal time-scales (20 to 70 days). The Madden-Julian Oscillation (MJO) is the most important intraseasonal mode of atmospheric circulation and moist convection in the tropics and the occurrence of extreme weather events worldwide. Mechanisms explaining the relationships between the MJO and precipitation in the Peruvian Andes have not been properly described yet. The present study examines the relationships between the activity and phases of the MJO and the occurrence of extreme rainfall over the CSPA. We found that the frequency of extreme rainfall events increase in the CSPA when the MJO is active. MJO phases 5, 6 and 7 contribute to the overall occurrence of extreme rainfall events over the CSPA. However, how the MJO phases modulate extreme rainfall depends on the location of the stations. For instance, extreme precipitation (above the 90th percentile) in stations in the Amazon basin are slightly more sensitive to phases 2, 3 and 4; the frequency of extremes in stations in the Pacific basin increases in phases 5, 6 and 7 whereas phase 2, 3 and 7 modulates extreme precipitation in stations in the Titicaca basin. Greater variability among stations is observed when using the 95th and 99th percentiles to identify extremes. Among the main mechanisms that explain the increase in extreme rainfall events in the Peruvian Andes is the intensification of the easterly moisture flux anomalies, which are favored during certain phases of the MJO. Here dynamical mechanisms linking the MJO to the occurrence of extreme rainfall in stations in the Peruvian Andes are investigated using composites of integrated moisture flux and geopotential height anomalies.

Long term changes in flooding and heavy rainfall associated with North Atlantic tropical cyclones: Roles of the North Atlantic Oscillation and El Niño-Southern Oscillation

NASA Astrophysics Data System (ADS)

Aryal, Yog N.; Villarini, Gabriele; Zhang, Wei; Vecchi, Gabriel A.

2018-04-01

The aim of this study is to examine the contribution of North Atlantic tropical cyclones (TCs) to flooding and heavy rainfall across the continental United States. Analyses highlight the spatial variability in these hazards, their temporal changes in terms of frequency and magnitude, and their connection to large-scale climate, in particular to the North Atlantic Oscillation (NAO) and El Niño-Southern Oscillation (ENSO). We use long-term stream and rain gage measurements, and our analyses are based on annual maxima (AMs) and peaks-over-threshold (POTs). TCs contribute to ∼20-30% of AMs and POTs over Florida and coastal areas of the eastern United States, and the contribution decreases as we move inland. We do not detect statistically significant trends in the magnitude or frequency of TC floods. Regarding the role of climate, NAO and ENSO do not play a large role in controlling the frequency and magnitude of TC flooding. The connection between heavy rainfall and TCs is comparable to what observed in terms of flooding. Unlike flooding, NAO plays a significant role in TC-related extreme rainfall along the U.S. East Coast, while ENSO is most strongly linked to the TC precipitation in Texas.

Fires in Seasonally Dry Tropical Forest: Testing the Varying Constraints Hypothesis across a Regional Rainfall Gradient.

PubMed

Mondal, Nandita; Sukumar, Raman

2016-01-01

The "varying constraints hypothesis" of fire in natural ecosystems postulates that the extent of fire in an ecosystem would differ according to the relative contribution of fuel load and fuel moisture available, factors that vary globally along a spatial gradient of climatic conditions. We examined if the globally widespread seasonally dry tropical forests (SDTFs) can be placed as a single entity in this framework by analyzing environmental influences on fire extent in a structurally diverse SDTF landscape in the Western Ghats of southern India, representative of similar forests in monsoonal south and southeast Asia. We used logistic regression to model fire extent with factors that represent fuel load and fuel moisture at two levels-the overall landscape and within four defined moisture regimes (between 700 and1700 mm yr-1)-using a dataset of area burnt and seasonal rainfall from 1990 to 2010. The landscape scale model showed that the extent of fire in a given year within this SDTF is dependent on the combined interaction of seasonal rainfall and extent burnt the previous year. Within individual moisture regimes the relative contribution of these factors to the annual extent burnt varied-early dry season rainfall (i.e., fuel moisture) was the predominant factor in the wettest regime, while wet season rainfall (i.e., fuel load) had a large influence on fire extent in the driest regime. Thus, the diverse structural vegetation types associated with SDTFs across a wide range of rainfall regimes would have to be examined at finer regional or local scales to understand the specific environmental drivers of fire. Our results could be extended to investigating fire-climate relationships in STDFs of monsoonal Asia.

Fires in Seasonally Dry Tropical Forest: Testing the Varying Constraints Hypothesis across a Regional Rainfall Gradient

PubMed Central

Mondal, Nandita; Sukumar, Raman

2016-01-01

The “varying constraints hypothesis” of fire in natural ecosystems postulates that the extent of fire in an ecosystem would differ according to the relative contribution of fuel load and fuel moisture available, factors that vary globally along a spatial gradient of climatic conditions. We examined if the globally widespread seasonally dry tropical forests (SDTFs) can be placed as a single entity in this framework by analyzing environmental influences on fire extent in a structurally diverse SDTF landscape in the Western Ghats of southern India, representative of similar forests in monsoonal south and southeast Asia. We used logistic regression to model fire extent with factors that represent fuel load and fuel moisture at two levels—the overall landscape and within four defined moisture regimes (between 700 and1700 mm yr-1)—using a dataset of area burnt and seasonal rainfall from 1990 to 2010. The landscape scale model showed that the extent of fire in a given year within this SDTF is dependent on the combined interaction of seasonal rainfall and extent burnt the previous year. Within individual moisture regimes the relative contribution of these factors to the annual extent burnt varied—early dry season rainfall (i.e., fuel moisture) was the predominant factor in the wettest regime, while wet season rainfall (i.e., fuel load) had a large influence on fire extent in the driest regime. Thus, the diverse structural vegetation types associated with SDTFs across a wide range of rainfall regimes would have to be examined at finer regional or local scales to understand the specific environmental drivers of fire. Our results could be extended to investigating fire-climate relationships in STDFs of monsoonal Asia. PMID:27441689

New spatial and temporal indices of Indian summer monsoon rainfall

NASA Astrophysics Data System (ADS)

Dwivedi, Sanjeev; Uma, R.; Lakshmi Kumar, T. V.; Narayanan, M. S.; Pokhrel, Samir; Kripalani, R. H.

2018-02-01

The overall yearly seasonal performance of Indian southwest monsoon rainfall (ISMR) for the whole Indian land mass is presently expressed by the India Meteorological Department (IMD) by a single number, the total quantum of rainfall. Any particular year is declared as excess/deficit or normal monsoon rainfall year on the basis of this single number. It is well known that monsoon rainfall also has high interannual variability in spatial and temporal scales. To account for these aspects in ISMR, we propose two new spatial and temporal indices. These indices have been calculated using the 115 years of IMD daily 0.25° × 0.25° gridded rainfall data. Both indices seem to go in tandem with the in vogue seasonal quantum index. The anomaly analysis indicates that the indices during excess monsoon years behave randomly, while for deficit monsoon years the phase of all the three indices is the same. Evaluation of these indices is also studied with respect to the existing dynamical indices based on large-scale circulation. It is found that the new temporal indices have better link with circulation indices as compared to the new spatial indices. El Nino and Southern Oscillation (ENSO) especially over the equatorial Pacific Ocean still have the largest influence in both the new indices. However, temporal indices have much better remote influence as compared to that of spatial indices. Linkages over the Indian Ocean regions are very different in both the spatial and temporal indices. Continuous wavelet transform (CWT) analysis indicates that the complete spectrum of oscillation of the QI is shared in the lower oscillation band by the spatial index and in the higher oscillation band by the temporal index. These new indices may give some extra dimension to study Indian summer monsoon variability.

Reduced precipitation over large water bodies in the Brazilian Amazon shown from TRMM data

NASA Astrophysics Data System (ADS)

Paiva, Rodrigo Cauduro Dias; Buarque, Diogo Costa; Clarke, Robin T.; Collischonn, Walter; Allasia, Daniel Gustavo

2011-02-01

Tropical Rainfall Measurement Mission (TRMM) data show lower rainfall over large water bodies in the Brazilian Amazon. Mean annual rainfall (P), number of wet days (rainfall > 2 mm) (W) and annual rainfall accumulated over 3-hour time intervals (P3hr) were computed from TRMM 3B42 data for 1998-2009. Reduced rainfall was marked over the Rio Solimões/Amazon, along most Amazon tributaries and over the Balbina reservoir. In a smaller test area, a heuristic argument showed that P and W were reduced by 5% and 6.5% respectively. Allowing for TRMM 3B42 spatial resolution, the reduction may be locally greater. Analyses of diurnal rainfall patterns showed that rainfall is lowest over large rivers during the afternoon, when most rainfall is convective, but at night and early morning the opposite occurs, with increased rainfall over rivers, although this pattern is less marked. Rainfall patterns reported from studies of smaller Amazonian regions therefore exist more widely.

Dynamic Rainfall Patterns and the Simulation of Changing Scenarios: A behavioral watershed response

NASA Astrophysics Data System (ADS)

Chu, M.; Guzman, J.; Steiner, J. L.; Hou, C.; Moriasi, D.

2015-12-01

Rainfall is one of the fundamental drivers that control hydrologic responses including runoff production and transport phenomena that consequently drive changes in aquatic ecosystems. Quantifying the hydrologic responses to changing scenarios (e.g., climate, land use, and management) using environmental models requires a realistic representation of probable rainfall in its most sensible spatio-temporal dimensions matching that of the phenomenon under investigation. Downscaling projected rainfall from global circulation models (GCMs) is the most common practice in deriving rainfall datasets to be used as main inputs to hydrologic models which in turn are used to assess the impacts of climate changes on ecosystems. Downscaling assumes that local climate is a combination of large-scale climatic/atmospheric conditions and local conditions. However, the representation of the latter is generally beyond the capacity of current GCMs. The main objective of this study was to develop and implement a synthetic rainfall generator to downscale expected rainfall trends to 1 x 1 km rainfall daily patterns that mimic the dynamic propagation of probability distribution functions (pdf) derived from historic rainfall data (rain-gauge or radar estimated). Future projections were determined based on actual and expected changes in the pdf and stochastic processes to account for variability. Watershed responses in terms of streamflow and nutrients loads were evaluated using synthetically generated rainfall patterns and actual data. The framework developed in this study will allow practitioners to generate rainfall datasets that mimic the temporal and spatial patterns exclusive to their study area under full disclosure of the uncertainties involved. This is expected to provide significantly more accurate environmental models than is currently available and would provide practitioners with ways to evaluate the spectrum of systemic responses to changing scenarios.

Observed Recent Trends in Tropical Cyclone Rainfall Over Major Ocean Basins

NASA Technical Reports Server (NTRS)

Lau, K. M.; Zhou, Y. P.

2011-01-01

In this study, we use Tropical Rainfall Measuring Mission (TRMM) and Global Precipitation Climatology Project (GPCP) rainfall data together with historical storm track records to examine the trend of tropical cyclone (TC) rainfall in major ocean basins during recent decades (1980-2007). We find that accumulated total rainfall along storm tracks for all tropical cyclones shows a weak positive trend over the whole tropics. However, total rainfall associated with weak storms, and intense storms (Category 4-5) both show significant positive trends, while total rainfall associated with intermediate storms (Category1-3) show a significant negative trend. Storm intensity defined as total rain produced per unit storm also shows increasing trend for all storm types. Basin-wide, from the first half (1980-1993) to the second half (1994-2007) of the data period, the North Atlantic shows the pronounced increase in TC number and TC rainfall while the Northeast Pacific shows a significant decrease in all storm types. Except for the Northeast Pacific, all other major basins (North Atlantic, Northwest Pacific, Southern Oceans, and Northern Indian Ocean) show a significant increase in total number and rainfall amount in Category 4-5 storms. Overall, trends in TC rainfall in different ocean basins are consistent with long-term changes in the ambient large-scale environment, including SST, vertical wind shear, sea level pressure, mid-tropospheric humidity, and Maximum Potential Intensity (MPI). Notably the pronounced positive (negative) trend of TC rainfall in the North Atlantic (Northeast Pacific) appears to be related to the most (least) rapid increase in SST and MPI, and the largest decrease (increase) in vertical wind shear in the region, relative to other ocean basins.

Analysis of the sensitivity to rainfall spatio-temporal variability of an operational urban rainfall-runoff model in a multifractal framework

NASA Astrophysics Data System (ADS)

Gires, A.; Tchiguirinskaia, I.; Schertzer, D. J.; Lovejoy, S.

2011-12-01

In large urban areas, storm water management is a challenge with enlarging impervious areas. Many cities have implemented real time control (RTC) of their urban drainage system to either reduce overflow or limit urban contamination. A basic component of RTC is hydraulic/hydrologic model. In this paper we use the multifractal framework to suggest an innovative way to test the sensitivity of such a model to the spatio-temporal variability of its rainfall input. Indeed the rainfall variability is often neglected in urban context, being considered as a non-relevant issue at the scales involve. Our results show that on the contrary the rainfall variability should be taken into account. Universal multifractals (UM) rely on the concept of multiplicative cascade and are a standard tool to analyze and simulate with a reduced number of parameters geophysical processes that are extremely variable over a wide range of scales. This study is conducted on a 3 400 ha urban area located in Seine-Saint-Denis, in the North of Paris (France). We use the operational semi-distributed model that was calibrated by the local authority (Direction Eau et Assainnissement du 93) that is in charge of urban drainage. The rainfall data comes from the C-Band radar of Trappes operated by Météo-France. The rainfall event of February 9th, 2009 was used. A stochastic ensemble approach was implemented to quantify the uncertainty on discharge associated to the rainfall variability occurring at scales smaller than 1 km x 1 km x 5 min that is usually available with C-band radar networks. An analysis of the quantiles of the simulated peak flow showed that the uncertainty exceeds 20 % for upstream links. To evaluate a potential gain from a direct use of the rainfall data available at the resolution of X-band radar, we performed similar analysis of the rainfall fields of the degraded resolution of 9 km x 9 km x 20 min. The results show a clear decrease in uncertainty when the original resolution of C-band radar data is used. This analysis highlights the interest of implementing X-band radars in urban areas. Indeed such radars provide the rainfall data at a hectometric resolution that would enable a better nowcasting and management of storm water. The multifractal properties of the simulated hydrographs were analysed with the help of simulated rainfall fields of resolution 111 m x 111 m x 1 min, lasting 4 hours, and corresponding to a 5 year return period event. On the whole, the discharge exhibits a good scaling behaviour over the range 4 h - 5 min. Both UM parameters tend to be greater for the discharge than for the rainfall. The notion of maximum probable singularity was used to clarify the consequences on the assessment of extremes. It appears that the urban drainage network basically reproduces the extremes, or only slightly damps them, at least in terms of multifractal statistics. The results were obtained with the financial support from the EU FP7 SMARTesT Project and the Chair "Hydrology for Resilient Cities" (sponsored by Veolia) of Ecole des Ponts ParisTech.

A theoretically consistent stochastic cascade for temporal disaggregation of intermittent rainfall

NASA Astrophysics Data System (ADS)

Lombardo, F.; Volpi, E.; Koutsoyiannis, D.; Serinaldi, F.

2017-06-01

Generating fine-scale time series of intermittent rainfall that are fully consistent with any given coarse-scale totals is a key and open issue in many hydrological problems. We propose a stationary disaggregation method that simulates rainfall time series with given dependence structure, wet/dry probability, and marginal distribution at a target finer (lower-level) time scale, preserving full consistency with variables at a parent coarser (higher-level) time scale. We account for the intermittent character of rainfall at fine time scales by merging a discrete stochastic representation of intermittency and a continuous one of rainfall depths. This approach yields a unique and parsimonious mathematical framework providing general analytical formulations of mean, variance, and autocorrelation function (ACF) for a mixed-type stochastic process in terms of mean, variance, and ACFs of both continuous and discrete components, respectively. To achieve the full consistency between variables at finer and coarser time scales in terms of marginal distribution and coarse-scale totals, the generated lower-level series are adjusted according to a procedure that does not affect the stochastic structure implied by the original model. To assess model performance, we study rainfall process as intermittent with both independent and dependent occurrences, where dependence is quantified by the probability that two consecutive time intervals are dry. In either case, we provide analytical formulations of main statistics of our mixed-type disaggregation model and show their clear accordance with Monte Carlo simulations. An application to rainfall time series from real world is shown as a proof of concept.

Conditional flood frequency and catchment state: a simulation approach

NASA Astrophysics Data System (ADS)

Brettschneider, Marco; Bourgin, François; Merz, Bruno; Andreassian, Vazken; Blaquiere, Simon

2017-04-01

Catchments have memory and the conditional flood frequency distribution for a time period ahead can be seen as non-stationary: it varies with the catchment state and climatic factors. From a risk management perspective, understanding the link of conditional flood frequency to catchment state is a key to anticipate potential periods of higher flood risk. Here, we adopt a simulation approach to explore the link between flood frequency obtained by continuous rainfall-runoff simulation and the initial state of the catchment. The simulation chain is based on i) a three state rainfall generator applied at the catchment scale, whose parameters are estimated for each month, and ii) the GR4J lumped rainfall-runoff model, whose parameters are calibrated with all available data. For each month, a large number of stochastic realizations of the continuous rainfall generator for the next 12 months are used as inputs for the GR4J model in order to obtain a large number of stochastic realizations for the next 12 months. This process is then repeated for 50 different initial states of the soil moisture reservoir of the GR4J model and for all the catchments. Thus, 50 different conditional flood frequency curves are obtained for the 50 different initial catchment states. We will present an analysis of the link between the catchment states, the period of the year and the strength of the conditioning of the flood frequency compared to the unconditional flood frequency. A large sample of diverse catchments in France will be used.

Parallelization of the TRIGRS model for rainfall-induced landslides using the message passing interface

USGS Publications Warehouse

Alvioli, M.; Baum, R.L.

2016-01-01

We describe a parallel implementation of TRIGRS, the Transient Rainfall Infiltration and Grid-Based Regional Slope-Stability Model for the timing and distribution of rainfall-induced shallow landslides. We have parallelized the four time-demanding execution modes of TRIGRS, namely both the saturated and unsaturated model with finite and infinite soil depth options, within the Message Passing Interface framework. In addition to new features of the code, we outline details of the parallel implementation and show the performance gain with respect to the serial code. Results are obtained both on commercial hardware and on a high-performance multi-node machine, showing the different limits of applicability of the new code. We also discuss the implications for the application of the model on large-scale areas and as a tool for real-time landslide hazard monitoring.

Landslides Are Common In The Amazon Rainforests Of SE Peru

NASA Astrophysics Data System (ADS)

Khanal, S. P.; Muttiah, R. S.; Janovec, J. P.

2005-12-01

The recent landslides in La Conchita, California, Mumbai, India, Ratnapura, Sri Lanka and Sugozu village, Turkey have dramatically illustrated prolonged rainfall on water induced change in soil shear stress. In these examples, the human footprint may have also erased or altered the natural river drainage from small to large scales. By studying patterns of landslides in natural ecosystems, government officials, policy makers, engineers, geologists and others may be better informed about likely success of prevention or amelioration programs in risk prone areas. Our study area in the Los Amigos basin in Amazon rainforests of Southeastern Peru, has recorded several hundred landslides. The area has no large human settlements. The basin is characterized by heavy rainfall, dense vegetation, river meander and uniform soils. Our objectives were: 1). Determine the spatial pattern of landslides using GIS and Remotely sensed data, 2). Model the statistical relationship between environmental variables and, 3). Evaluate influence of drainage on landscape and soil loss. GIS layers consisted of: 50cm aerial imagery, DEMs, digitized streams, soils, geology, rainfall from the TRMM satellite, and vegetation cover from the LANDSAT and MODIS sensors.

RainyDay: An Online, Open-Source Tool for Physically-based Rainfall and Flood Frequency Analysis

NASA Astrophysics Data System (ADS)

Wright, D.; Yu, G.; Holman, K. D.

2017-12-01

Flood frequency analysis in ungaged or changing watersheds typically requires rainfall intensity-duration-frequency (IDF) curves combined with hydrologic models. IDF curves only depict point-scale rainfall depth, while true rainstorms exhibit complex spatial and temporal structures. Floods result from these rainfall structures interacting with watershed features such as land cover, soils, and variable antecedent conditions as well as river channel processes. Thus, IDF curves are traditionally combined with a variety of "design storm" assumptions such as area reduction factors and idealized rainfall space-time distributions to translate rainfall depths into inputs that are suitable for flood hydrologic modeling. The impacts of such assumptions are relatively poorly understood. Meanwhile, modern precipitation estimates from gridded weather radar, grid-interpolated rain gages, satellites, and numerical weather models provide more realistic depictions of rainfall space-time structure. Usage of such datasets for rainfall and flood frequency analysis, however, are hindered by relatively short record lengths. We present RainyDay, an open-source stochastic storm transposition (SST) framework for generating large numbers of realistic rainfall "scenarios." SST "lengthens" the rainfall record by temporal resampling and geospatial transposition of observed storms to extract space-time information from regional gridded rainfall data. Relatively short (10-15 year) records of bias-corrected radar rainfall data are sufficient to estimate rainfall and flood events with much longer recurrence intervals including 100-year and 500-year events. We describe the SST methodology as implemented in RainyDay and compare rainfall IDF results from RainyDay to conventional estimates from NOAA Atlas 14. Then, we demonstrate some of the flood frequency analysis properties that are possible when RainyDay is integrated with a distributed hydrologic model, including robust estimation of flood hazards in a changing watershed. The U.S. Bureau of Reclamation is supporting the development of a web-based variant of RainyDay, a "beta" version of which is available at http://her.cee.wisc.edu/projects/rainyday/.

Precipitation Climatology over Mediterranean Basin from Ten Years of TRMM Measurements

NASA Technical Reports Server (NTRS)

Mehta, Amita V.; Yang, Song

2008-01-01

Climatological features of mesoscale rain activities over the Mediterranean region between 5 W-40 E and 28 N-48 N are examined using the Tropical Rainfall Measuring Mission (TRMM) 3B42 and 2A25 rain products. The 3B42 rainrates at 3-hourly, 0.25 deg x 0.25 deg spatial resolution for the last 10 years (January 1998 to July 2007) are used to form and analyze the 5-day mean and monthly mean climatology of rainfall. Results show considerable regional and seasonal differences of rainfall over the Mediterranean Region. The maximum rainfall (3-5 mm/day) occurs over the mountain regions of Europe, while the minimum rainfall is observed over North Africa (approximately 0.5 mm/day). The main rainy season over the Mediterranean Sea extends from October to March, with maximum rainfall occurring during November-December. Over the Mediterranean Sea, an average rainrate of approximately 1-2 mm/day is observed, but during the rainy season there is 20% larger rainfall over the western Mediterranean Sea than that over the eastern Mediterranean Sea. During the rainy season, mesoscale rain systems generally propagate from west to east and from north to south over the Mediterranean region, likely to be associated with Mediterranean cyclonic disturbances resulting from interactions among large-scale circulation, orography, and land-sea temperature contrast.

Changing character of rainfall in eastern China, 1951-2007.

PubMed

Day, Jesse A; Fung, Inez; Liu, Weihan

2018-02-27

The topography and continental configuration of East Asia favor the year-round existence of storm tracks that extend thousands of kilometers from China into the northwestern Pacific Ocean, producing zonally elongated patterns of rainfall that we call "frontal rain events." In spring and early summer (known as "Meiyu Season"), frontal rainfall intensifies and shifts northward during a series of stages collectively known as the East Asian summer monsoon. Using a technique called the Frontal Rain Event Detection Algorithm, we create a daily catalog of all frontal rain events in east China during 1951-2007, quantify their attributes, and classify all rainfall on each day as either frontal, resulting from large-scale convergence, or nonfrontal, produced by local buoyancy, topography, or typhoons. Our climatology shows that the East Asian summer monsoon consists of a series of coupled changes in frontal rain event frequency, latitude, and daily accumulation. Furthermore, decadal changes in the amount and distribution of rainfall in east China are overwhelmingly due to changes in frontal rainfall. We attribute the "South Flood-North Drought" pattern observed beginning in the 1980s to changes in the frequency of frontal rain events, while the years 1994-2007 witnessed an uptick in event daily accumulation relative to the rest of the study years. This particular signature may reflect the relative impacts of global warming, aerosol loading, and natural variability on regional rainfall, potentially via shifting the East Asian jet stream.

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

PubMed

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

2008-09-01

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

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.

Exogenous factors matter when interpreting the results of an impact evaluation: a case study of rainfall and child health programme intervention in Rwanda.

PubMed

Mukabutera, Assumpta; Thomson, Dana R; Hedt-Gauthier, Bethany L; Atwood, Sidney; Basinga, Paulin; Nyirazinyoye, Laetitia; Savage, Kevin P; Habimana, Marcellin; Murray, Megan

2017-12-01

Public health interventions are often implemented at large scale, and their evaluation seems to be difficult because they are usually multiple and their pathways to effect are complex and subject to modification by contextual factors. We assessed whether controlling for rainfall-related variables altered estimates of the efficacy of a health programme in rural Rwanda and have a quantifiable effect on an intervention evaluation outcomes. We conducted a retrospective quasi-experimental study using previously collected cross-sectional data from the 2005 and 2010 Rwanda Demographic and Health Surveys (DHS), 2010 DHS oversampled data, monthly rainfall data collected from meteorological stations over the same period, and modelled output of long-term rainfall averages, soil moisture, and rain water run-off. Difference-in-difference models were used. Rainfall factors confounded the PIH intervention impact evaluation. When we adjusted our estimates of programme effect by controlling for a variety of rainfall variables, several effectiveness estimates changed by 10% or more. The analyses that did not adjust for rainfall-related variables underestimated the intervention effect on the prevalence of ARI by 14.3%, fever by 52.4% and stunting by 10.2%. Conversely, the unadjusted analysis overestimated the intervention's effect on diarrhoea by 56.5% and wasting by 80%. Rainfall-related patterns have a quantifiable effect on programme evaluation results and highlighted the importance and complexity of controlling for contextual factors in quasi-experimental design evaluations. © 2017 John Wiley & Sons Ltd.

Real-time prediction of rain-triggered lahars: incorporating seasonality and catchment recovery

NASA Astrophysics Data System (ADS)

Jones, Robbie; Manville, Vern; Peakall, Jeff; Froude, Melanie J.; Odbert, Henry M.

2017-12-01

Rain-triggered lahars are a significant secondary hydrological and geomorphic hazard at volcanoes where unconsolidated pyroclastic material produced by explosive eruptions is exposed to intense rainfall, often occurring for years to decades after the initial eruptive activity. Previous studies have shown that secondary lahar initiation is a function of rainfall parameters, source material characteristics and time since eruptive activity. In this study, probabilistic rain-triggered lahar forecasting models are developed using the lahar occurrence and rainfall record of the Belham River valley at the Soufrière Hills volcano (SHV), Montserrat, collected between April 2010 and April 2012. In addition to the use of peak rainfall intensity (PRI) as a base forecasting parameter, considerations for the effects of rainfall seasonality and catchment evolution upon the initiation of rain-triggered lahars and the predictability of lahar generation are also incorporated into these models. Lahar probability increases with peak 1 h rainfall intensity throughout the 2-year dataset and is higher under given rainfall conditions in year 1 than year 2. The probability of lahars is also enhanced during the wet season, when large-scale synoptic weather systems (including tropical cyclones) are more common and antecedent rainfall and thus levels of deposit saturation are typically increased. The incorporation of antecedent conditions and catchment evolution into logistic-regression-based rain-triggered lahar probability estimation models is shown to enhance model performance and displays the potential for successful real-time prediction of lahars, even in areas featuring strongly seasonal climates and temporal catchment recovery.

Hierarchical analysis of vegetation dynamics over 71 years: Soil-rainfall interactions in a Chihuahuan Desert ecosystem

USDA-ARS?s Scientific Manuscript database

Proliferation of woody plants in grasslands and savannas (hereafter, “rangelands”) is a persistent problem globally. This widely-observed shift from grass to shrub dominance in rangelands worldwide has been heterogeneous in space and time largely due to cross-scale interactions between soils, climat...

LAND COVER CHANGE AND LARGE SCALE HYDROLOGIC MODELING OF THE SAN PEDRO RIVER AND CATSKILL/DELAWARE BASINS

EPA Science Inventory

This study is based on the assumption that land cover change and rainfall spatial variability affect the r-ainfall-runoff relationships on the watershed. Hydrologic response is an integrated indicator of watershed condition, and changes in land cover may affect the overall health...

Estimating Vegetation Rainfall Interception Using Remote Sensing Observations at Very High Resolution

NASA Astrophysics Data System (ADS)

Cui, Y.; Zhao, P.; Hong, Y.; Fan, W.; Yan, B.; Xie, H.

2017-12-01

Abstract: As an important compont of evapotranspiration, vegetation rainfall interception is the proportion of gross rainfall that is intercepted, stored and subsequently evaporated from all parts of vegetation during or following rainfall. Accurately quantifying the vegetation rainfall interception at a high resolution is critical for rainfall-runoff modeling and flood forecasting, and is also essential for understanding its further impact on local, regional, and even global water cycle dynamics. In this study, the Remote Sensing-based Gash model (RS-Gash model) is developed based on a modified Gash model for interception loss estimation using remote sensing observations at the regional scale, and has been applied and validated in the upper reach of the Heihe River Basin of China for different types of vegetation. To eliminate the scale error and the effect of mixed pixels, the RS-Gash model is applied at a fine scale of 30 m with the high resolution vegetation area index retrieved by using the unified model of bidirectional reflectance distribution function (BRDF-U) for the vegetation canopy. Field validation shows that the RMSE and R2 of the interception ratio are 3.7% and 0.9, respectively, indicating the model's strong stability and reliability at fine scale. The temporal variation of vegetation rainfall interception loss and its relationship with precipitation are further investigated. In summary, the RS-Gash model has demonstrated its effectiveness and reliability in estimating vegetation rainfall interception. When compared to the coarse resolution results, the application of this model at 30-m fine resolution is necessary to resolve the scaling issues as shown in this study. Keywords: rainfall interception; remote sensing; RS-Gash analytical model; high resolution

Weakening of Indian Summer Monsoon Rainfall due to Changes in Land Use Land Cover

PubMed Central

Paul, Supantha; Ghosh, Subimal; Oglesby, Robert; Pathak, Amey; Chandrasekharan, Anita; Ramsankaran, RAAJ

2016-01-01

Weakening of Indian summer monsoon rainfall (ISMR) is traditionally linked with large-scale perturbations and circulations. However, the impacts of local changes in land use and land cover (LULC) on ISMR have yet to be explored. Here, we analyzed this topic using the regional Weather Research and Forecasting model with European Center for Medium range Weather Forecast (ECMWF) reanalysis data for the years 2000–2010 as a boundary condition and with LULC data from 1987 and 2005. The differences in LULC between 1987 and 2005 showed deforestation with conversion of forest land to crop land, though the magnitude of such conversion is uncertain because of the coarse resolution of satellite images and use of differential sources and methods for data extraction. We performed a sensitivity analysis to understand the impacts of large-scale deforestation in India on monsoon precipitation and found such impacts are similar to the observed changes in terms of spatial patterns and magnitude. We found that deforestation results in weakening of the ISMR because of the decrease in evapotranspiration and subsequent decrease in the recycled component of precipitation. PMID:27553384

Continuous Sub-daily Rainfall Simulation for Regional Flood Risk Assessment - Modelling of Spatio-temporal Correlation Structure of Extreme Precipitation in the Austrian Alps

NASA Astrophysics Data System (ADS)

Salinas, J. L.; Nester, T.; Komma, J.; Bloeschl, G.

2017-12-01

Generation of realistic synthetic spatial rainfall is of pivotal importance for assessing regional hydroclimatic hazard as the input for long term rainfall-runoff simulations. The correct reproduction of observed rainfall characteristics, such as regional intensity-duration-frequency curves, and spatial and temporal correlations is necessary to adequately model the magnitude and frequency of the flood peaks, by reproducing antecedent soil moisture conditions before extreme rainfall events, and joint probability of flood waves at confluences. In this work, a modification of the model presented by Bardossy and Platte (1992), where precipitation is first modeled on a station basis as a multivariate autoregressive model (mAr) in a Normal space. The spatial and temporal correlation structures are imposed in the Normal space, allowing for a different temporal autocorrelation parameter for each station, and simultaneously ensuring the positive-definiteness of the correlation matrix of the mAr errors. The Normal rainfall is then transformed to a Gamma-distributed space, with parameters varying monthly according to a sinusoidal function, in order to adapt to the observed rainfall seasonality. One of the main differences with the original model is the simulation time-step, reduced from 24h to 6h. Due to a larger availability of daily rainfall data, as opposite to sub-daily (e.g. hourly), the parameters of the Gamma distributions are calibrated to reproduce simultaneously a series of daily rainfall characteristics (mean daily rainfall, standard deviations of daily rainfall, and 24h intensity-duration-frequency [IDF] curves), as well as other aggregated rainfall measures (mean annual rainfall, and monthly rainfall). The calibration of the spatial and temporal correlation parameters is performed in a way that the catchment-averaged IDF curves aggregated at different temporal scales fit the measured ones. The rainfall model is used to generate 10.000 years of synthetic precipitation, fed into a rainfall-runoff model to derive the flood frequency in the Tirolean Alps in Austria. Given the number of generated events, the simulation framework is able to generate a large variety of rainfall patterns, as well as reproduce the variograms of relevant extreme rainfall events in the region of interest.

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.

Comparison between fully distributed model and semi-distributed model in urban hydrology modeling

NASA Astrophysics Data System (ADS)

Ichiba, Abdellah; Gires, Auguste; Giangola-Murzyn, Agathe; Tchiguirinskaia, Ioulia; Schertzer, Daniel; Bompard, Philippe

2013-04-01

Water management in urban areas is becoming more and more complex, especially because of a rapid increase of impervious areas. There will also possibly be an increase of extreme precipitation due to climate change. The aims of the devices implemented to handle the large amount of water generate by urban areas such as storm water retention basins are usually twofold: ensure pluvial flood protection and water depollution. These two aims imply opposite management strategies. To optimize the use of these devices there is a need to implement urban hydrological models and improve fine-scale rainfall estimation, which is the most significant input. In this paper we suggest to compare two models and their sensitivity to small-scale rainfall variability on a 2.15 km2 urban area located in the County of Val-de-Marne (South-East of Paris, France). The average impervious coefficient is approximately 34%. In this work two types of models are used. The first one is CANOE which is semi-distributed. Such models are widely used by practitioners for urban hydrology modeling and urban water management. Indeed, they are easily configurable and the computation time is reduced, but these models do not take fully into account either the variability of the physical properties or the variability of the precipitations. An alternative is to use distributed models that are harder to configure and require a greater computation time, but they enable a deeper analysis (especially at small scales and upstream) of the processes at stake. We used the Multi-Hydro fully distributed model developed at the Ecole des Ponts ParisTech. It is an interacting core between open source software packages, each of them representing a portion of the water cycle in urban environment. Four heavy rainfall events that occurred between 2009 and 2011 are analyzed. The data comes from the Météo-France radar mosaic and the resolution is 1 km in space and 5 min in time. The closest radar of the Météo-France network is a C-band one located at 37 km West. In this work we compare the hydrological response of two models for the 4 rainfall events first with the available radar data. Then a particular focus is made on the impact of small-scale unmeasured rainfall variability (i.e. occurring at scales below the available one). More precisely scaling properties of rainfall are used to generate an ensemble of downscaled rainfall fields (simply by continuing the underlying cascade process whose relevant parameters are estimated on the available range of scales). An ensemble of hydrological responses is then simulated, and the variability within it analyzed. It appears that the associated uncertainty is significant and should be taken into account. Finally we will discuss the interest of deploying X-band radars (which provide an hectometric resolution) in urban environment and the potential benefits of using these models and small-scale rainfall data for the management of sewerage and retentions basin. Further analysis on these issues will be carried out next year with the installation of an X-band radar near Marne-la-Vallée (located at roughly 10 Km of the studied catchment) in the framework of the RainGain project (European project financed by the Interreg IVB funds).

A Coupled Approach with Stochastic Rainfall-Runoff Simulation and Hydraulic Modeling for Extreme Flood Estimation on Large Watersheds

NASA Astrophysics Data System (ADS)

Paquet, E.

2015-12-01

The SCHADEX method aims at estimating the distribution of peak and daily discharges up to extreme quantiles. It couples a precipitation probabilistic model based on weather patterns, with a stochastic rainfall-runoff simulation process using a conceptual lumped model. It allows exploring an exhaustive set of hydrological conditions and watershed responses to intense rainfall events. Since 2006, it has been widely applied in France to about one hundred watersheds for dam spillway design, and also aboard (Norway, Canada and central Europe among others). However, its application to large watersheds (above 10 000 km²) faces some significant issues: spatial heterogeneity of rainfall and hydrological processes and flood peak damping due to hydraulic effects (flood plains, natural or man-made embankment) being the more important. This led to the development of an extreme flood simulation framework for large and heterogeneous watersheds, based on the SCHADEX method. Its main features are: Division of the large (or main) watershed into several smaller sub-watersheds, where the spatial homogeneity of the hydro-meteorological processes can reasonably be assumed, and where the hydraulic effects can be neglected. Identification of pilot watersheds where discharge data are available, thus where rainfall-runoff models can be calibrated. They will be parameters donors to non-gauged watersheds. Spatially coherent stochastic simulations for all the sub-watersheds at the daily time step. Identification of a selection of simulated events for a given return period (according to the distribution of runoff volumes at the scale of the main watershed). Generation of the complete hourly hydrographs at each of the sub-watersheds outlets. Routing to the main outlet with hydraulic 1D or 2D models. The presentation will be illustrated with the case-study of the Isère watershed (9981 km), a French snow-driven watershed. The main novelties of this method will be underlined, as well as its perspectives and future improvements.

Scaling of hydrologic and erosion parameters derived from rainfall simulation

NASA Astrophysics Data System (ADS)

Sheridan, Gary; Lane, Patrick; Noske, Philip; Sherwin, Christopher

2010-05-01

Rainfall simulation experiments conducted at the temporal scale of minutes and the spatial scale of meters are often used to derive parameters for erosion and water quality models that operate at much larger temporal and spatial scales. While such parameterization is convenient, there has been little effort to validate this approach via nested experiments across these scales. In this paper we first review the literature relevant to some of these long acknowledged issues. We then present rainfall simulation and erosion plot data from a range of sources, including mining, roading, and forestry, to explore the issues associated with the scaling of parameters such as infiltration properties and erodibility coefficients.

Impact of rainfall on the moisture content of large woody fuels

Treesearch

Helen H. Mohr; Thomas A. Waldrop

2013-01-01

This unreplicated case study evaluates the impact of rainfall on large woody fuels over time. We know that one rainfall event may decrease the Keetch-Byram Drought Index, but this study shows no real increase in fuel moisture in 1,000- hour fuels after just one rainfall. Several rain events over time are required for the moisture content of large woody fuels to...

The rainfall plot: its motivation, characteristics and pitfalls.

PubMed

Domanska, Diana; Vodák, Daniel; Lund-Andersen, Christin; Salvatore, Stefania; Hovig, Eivind; Sandve, Geir Kjetil

2017-05-18

A visualization referred to as rainfall plot has recently gained popularity in genome data analysis. The plot is mostly used for illustrating the distribution of somatic cancer mutations along a reference genome, typically aiming to identify mutation hotspots. In general terms, the rainfall plot can be seen as a scatter plot showing the location of events on the x-axis versus the distance between consecutive events on the y-axis. Despite its frequent use, the motivation for applying this particular visualization and the appropriateness of its usage have never been critically addressed in detail. We show that the rainfall plot allows visual detection even for events occurring at high frequency over very short distances. In addition, event clustering at multiple scales may be detected as distinct horizontal bands in rainfall plots. At the same time, due to the limited size of standard figures, rainfall plots might suffer from inability to distinguish overlapping events, especially when multiple datasets are plotted in the same figure. We demonstrate the consequences of plot congestion, which results in obscured visual data interpretations. This work provides the first comprehensive survey of the characteristics and proper usage of rainfall plots. We find that the rainfall plot is able to convey a large amount of information without any need for parameterization or tuning. However, we also demonstrate how plot congestion and the use of a logarithmic y-axis may result in obscured visual data interpretations. To aid the productive utilization of rainfall plots, we demonstrate their characteristics and potential pitfalls using both simulated and real data, and provide a set of practical guidelines for their proper interpretation and usage.

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

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

Satellite-based characterization of climatic conditions before large-scale general flowering events in Peninsular Malaysia

PubMed Central

Azmy, Muna Maryam; Hashim, Mazlan; Numata, Shinya; Hosaka, Tetsuro; Noor, Nur Supardi Md.; Fletcher, Christine

2016-01-01

General flowering (GF) is a unique phenomenon wherein, at irregular intervals, taxonomically diverse trees in Southeast Asian dipterocarp forests synchronize their reproduction at the community level. Triggers of GF, including drought and low minimum temperatures a few months previously has been limitedly observed across large regional scales due to lack of meteorological stations. Here, we aim to identify the climatic conditions that trigger large-scale GF in Peninsular Malaysia using satellite sensors, Tropical Rainfall Measuring Mission (TRMM) and Moderate Resolution Imaging Spectroradiometer (MODIS), to evaluate the climatic conditions of focal forests. We observed antecedent drought, low temperature and high photosynthetic radiation conditions before large-scale GF events, suggesting that large-scale GF events could be triggered by these factors. In contrast, we found higher-magnitude GF in forests where lower precipitation preceded large-scale GF events. GF magnitude was also negatively influenced by land surface temperature (LST) for a large-scale GF event. Therefore, we suggest that spatial extent of drought may be related to that of GF forests, and that the spatial pattern of LST may be related to that of GF occurrence. With significant new findings and other results that were consistent with previous research we clarified complicated environmental correlates with the GF phenomenon. PMID:27561887

Satellite-based characterization of climatic conditions before large-scale general flowering events in Peninsular Malaysia.

PubMed

Azmy, Muna Maryam; Hashim, Mazlan; Numata, Shinya; Hosaka, Tetsuro; Noor, Nur Supardi Md; Fletcher, Christine

2016-08-26

General flowering (GF) is a unique phenomenon wherein, at irregular intervals, taxonomically diverse trees in Southeast Asian dipterocarp forests synchronize their reproduction at the community level. Triggers of GF, including drought and low minimum temperatures a few months previously has been limitedly observed across large regional scales due to lack of meteorological stations. Here, we aim to identify the climatic conditions that trigger large-scale GF in Peninsular Malaysia using satellite sensors, Tropical Rainfall Measuring Mission (TRMM) and Moderate Resolution Imaging Spectroradiometer (MODIS), to evaluate the climatic conditions of focal forests. We observed antecedent drought, low temperature and high photosynthetic radiation conditions before large-scale GF events, suggesting that large-scale GF events could be triggered by these factors. In contrast, we found higher-magnitude GF in forests where lower precipitation preceded large-scale GF events. GF magnitude was also negatively influenced by land surface temperature (LST) for a large-scale GF event. Therefore, we suggest that spatial extent of drought may be related to that of GF forests, and that the spatial pattern of LST may be related to that of GF occurrence. With significant new findings and other results that were consistent with previous research we clarified complicated environmental correlates with the GF phenomenon.

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

The effect of large-scale model time step and multiscale coupling frequency on cloud climatology, vertical structure, and rainfall extremes in a superparameterized GCM

DOE PAGES

Yu, Sungduk; Pritchard, Michael S.

2015-12-17

The effect of global climate model (GCM) time step—which also controls how frequently global and embedded cloud resolving scales are coupled—is examined in the Superparameterized Community Atmosphere Model ver 3.0. Systematic bias reductions of time-mean shortwave cloud forcing (~10 W/m 2) and longwave cloud forcing (~5 W/m 2) occur as scale coupling frequency increases, but with systematically increasing rainfall variance and extremes throughout the tropics. An overarching change in the vertical structure of deep tropical convection, favoring more bottom-heavy deep convection as a global model time step is reduced may help orchestrate these responses. The weak temperature gradient approximation ismore » more faithfully satisfied when a high scale coupling frequency (a short global model time step) is used. These findings are distinct from the global model time step sensitivities of conventionally parameterized GCMs and have implications for understanding emergent behaviors of multiscale deep convective organization in superparameterized GCMs. Lastly, the results may also be useful for helping to tune them.« less

The effect of large-scale model time step and multiscale coupling frequency on cloud climatology, vertical structure, and rainfall extremes in a superparameterized GCM

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

Yu, Sungduk; Pritchard, Michael S.

The effect of global climate model (GCM) time step—which also controls how frequently global and embedded cloud resolving scales are coupled—is examined in the Superparameterized Community Atmosphere Model ver 3.0. Systematic bias reductions of time-mean shortwave cloud forcing (~10 W/m 2) and longwave cloud forcing (~5 W/m 2) occur as scale coupling frequency increases, but with systematically increasing rainfall variance and extremes throughout the tropics. An overarching change in the vertical structure of deep tropical convection, favoring more bottom-heavy deep convection as a global model time step is reduced may help orchestrate these responses. The weak temperature gradient approximation ismore » more faithfully satisfied when a high scale coupling frequency (a short global model time step) is used. These findings are distinct from the global model time step sensitivities of conventionally parameterized GCMs and have implications for understanding emergent behaviors of multiscale deep convective organization in superparameterized GCMs. Lastly, the results may also be useful for helping to tune them.« less

Distant Influence of Kuroshio Eddies on North Pacific Weather Patterns?

PubMed

Ma, Xiaohui; Chang, Ping; Saravanan, R; Montuoro, Raffaele; Hsieh, Jen-Shan; Wu, Dexing; Lin, Xiaopei; Wu, Lixin; Jing, Zhao

2015-12-04

High-resolution satellite measurements of surface winds and sea-surface temperature (SST) reveal strong coupling between meso-scale ocean eddies and near-surface atmospheric flow over eddy-rich oceanic regions, such as the Kuroshio and Gulf Stream, highlighting the importance of meso-scale oceanic features in forcing the atmospheric planetary boundary layer (PBL). Here, we present high-resolution regional climate modeling results, supported by observational analyses, demonstrating that meso-scale SST variability, largely confined in the Kuroshio-Oyashio confluence region (KOCR), can further exert a significant distant influence on winter rainfall variability along the U.S. Northern Pacific coast. The presence of meso-scale SST anomalies enhances the diabatic conversion of latent heat energy to transient eddy energy, intensifying winter cyclogenesis via moist baroclinic instability, which in turn leads to an equivalent barotropic downstream anticyclone anomaly with reduced rainfall. The finding points to the potential of improving forecasts of extratropical winter cyclones and storm systems and projections of their response to future climate change, which are known to have major social and economic impacts, by improving the representation of ocean eddy-atmosphere interaction in forecast and climate models.

An evaluation of the spatial resolution of soil moisture information

NASA Technical Reports Server (NTRS)

Hardy, K. R.; Cohen, S. H.; Rogers, L. K.; Burke, H. H. K.; Leupold, R. C.; Smallwood, M. D.

1981-01-01

Rainfall-amount patterns in the central regions of the U.S. were assessed. The spatial scales of surface features and their corresponding microwave responses in the mid western U.S. were investigated. The usefulness for U.S. government agencies of soil moisture information at scales of 10 km and 1 km. was ascertained. From an investigation of 494 storms, it was found that the rainfall resulting from the passage of most types of storms produces patterns which can be resolved on a 10 km scale. The land features causing the greatest problem in the sensing of soil moisture over large agricultural areas with a radiometer are bodies of water. Over the mid-western portions of the U.S., water occupies less than 2% of the total area, the consequently, the water bodies will not have a significant impact on the mapping of soil moisture. Over most of the areas, measurements at a 10-km resolution would adequately define the distribution of soil moisture. Crop yield models and hydrological models would give improved results if soil moisture information at scales of 10 km was available.

Application of hierarchical clustering method to classify of space-time rainfall patterns

NASA Astrophysics Data System (ADS)

Yu, Hwa-Lung; Chang, Tu-Je

2010-05-01

Understanding the local precipitation patterns is essential to the water resources management and flooding mitigation. The precipitation patterns can vary in space and time depending upon the factors from different spatial scales such as local topological changes and macroscopic atmospheric circulation. The spatiotemporal variation of precipitation in Taiwan is significant due to its complex terrain and its location at west pacific and subtropical area, where is the boundary between the pacific ocean and Asia continent with the complex interactions among the climatic processes. This study characterizes local-scale precipitation patterns by classifying the historical space-time precipitation records. We applied the hierarchical ascending clustering method to analyze the precipitation records from 1960 to 2008 at the six rainfall stations located in Lan-yang catchment at the northeast of the island. Our results identify the four primary space-time precipitation types which may result from distinct driving forces from the changes of atmospheric variables and topology at different space-time scales. This study also presents an important application of the statistical downscaling to combine large-scale upper-air circulation with local space-time precipitation patterns.

Rainfall Erosivity Database on the European Scale (REDES): A product of a high temporal resolution rainfall data collection in Europe

NASA Astrophysics Data System (ADS)

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

2016-04-01

The erosive force of rainfall is expressed as rainfall erosivity. Rainfall erosivity considers the rainfall amount and intensity, and is most commonly expressed as the R-factor in the (R)USLE model. The R-factor is calculated from a series of single storm events by multiplying the total storm kinetic energy with the measured maximum 30-minutes rainfall intensity. This estimation requests high temporal resolution (e.g. 30 minutes) rainfall data for sufficiently long time periods (i.e. 20 years) which are not readily available at European scale. The European Commission's Joint Research Centre(JRC) in collaboration with national/regional meteorological services and Environmental Institutions made an extensive data collection of high resolution rainfall data in the 28 Member States of the European Union plus Switzerland in order to estimate rainfall erosivity in Europe. This resulted in the Rainfall Erosivity Database on the European Scale (REDES) which included 1,541 rainfall stations in 2014 and has been updated with 134 additional stations in 2015. The interpolation of those point R-factor values with a Gaussian Process Regression (GPR) model has resulted in the first Rainfall Erosivity map of Europe (Science of the Total Environment, 511, 801-815). The intra-annual variability of rainfall erosivity is crucial for modelling soil erosion on a monthly and seasonal basis. The monthly feature of rainfall erosivity has been added in 2015 as an advancement of REDES and the respective mean annual R-factor map. Almost 19,000 monthly R-factor values of REDES contributed to the seasonal and monthly assessments of rainfall erosivity in Europe. According to the first results, more than 50% of the total rainfall erosivity in Europe takes place in the period from June to September. The spatial patterns of rainfall erosivity have significant differences between Northern and Southern Europe as summer is the most erosive period in Central and Northern Europe and autumn in the Mediterranean area. This spatio-temporal analysis of rainfall erosivity at European scale is very important for policy makers and farmers for soil conservation, optimization of agricultural land use and natural hazards prediction. REDES is also used in combination with future rainfall data from WorldClim to run climate change scenarios. The projection of REDES combined with climate change scenarios (HADGEM2, RCP4.5) and using a robust geo-statistical model resulted in a 10-20% increase of the R-factor in Europe till 2050.

Changing water cycle over Korea

NASA Astrophysics Data System (ADS)

Yoon, J.

2017-12-01

In 2015, Korea experienced relatively strong drought, and annual mean precipitation was the third lowest since observation started at 1969 causing adverse impact on the several sectors including farming industry. Most precipitation in Korea occurs during summer season. In case of 2015 Korean drought, summer rainfall was much below than normal. On the other hand, another severe drought occurred in 2017 spring, which was followed by a couple of heavy rainfall cases that caused human casualties and damage in various sectors. Here we want to analyze this fast shifting of water cycle over Korea with a focus on its causing mechanisms and large scale atmospheric circulation features.

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

NASA Astrophysics Data System (ADS)

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

2015-10-01

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

Design and hydraulic characteristics of a field-scale bi-phasic bioretention rain garden system for storm water management.

PubMed

Yang, H; Florence, D C; McCoy, E L; Dick, W A; Grewal, P S

2009-01-01

A field-scale bioretention rain garden system was constructed using a novel bi-phasic (i.e. sequence of anaerobic to aerobic) concept for improving retention and removal of storm water runoff pollutants. Hydraulic tests with bromide tracer and simulated runoff pollutants (nitrate-N, phosphate-P, Cu, Pb, and Zn) were performed in the system under a simulated continuous rainfall. The objectives of the tests were (1) to determine hydraulic characteristics of the system, and (2) to evaluate the movement of runoff pollutants through the system. For the 180 mm/24 h rainfall, the bi-phasic bioretention system effectively reduced both peak flow (approximately 70%) and runoff volume (approximately 42%). The breakthrough curves (BTCs) of bromide tracer suggest that the transport pattern of the system is similar to dispersed plug flow under this large runoff event. The BTCs of bromide showed mean 10% and 90% breakthrough times of 5.7 h and 12.5 h, respectively. Under the continuous rainfall, a significantly different transport pattern was found between each runoff pollutant. Nitrate-N was easily transported through the system with potential leaching risk from the initial soil medium, whereas phosphate-P and metals were significantly retained indicating sorption-mediated transport. These findings support the importance of hydraulics, in combination with the soil medium, when creating bioretention systems for bioremediation that are effective for various rainfall sizes and intervals.

A Physically-based Model For Rainfall-triggered Landslides At A Regional Scale

NASA Astrophysics Data System (ADS)

Teles, V.; Capolongo, D.; Bras, R. L.

Rainfall has long been recognized as a major cause of landslides. Historical records have shown that large rainfall can generate hundreds of landslides over hundreds of square kilometers. Although a great body of work has documented the morphology and mechanics of individual slope failure, few studies have considered the process at basin and regional scale. A landslide model is integrated in the landscape evolution model CHILD and simulates rainfall-triggered events based on a geotechnical index, the factor of safety, which takes into account the slope, the soil effective cohesion and weight, the friction angle, the regolith thickness and the saturated thickness. The stat- urated thickness is represented by the wetness index developed in the TOPMODEL. The topography is represented by a Triangulated Irregular Network (TIN). The factor of safety is computed at each node of the TIN. If the factor of safety is lower than 1, a landslide is intiated at this node. The regolith is then moved downstream. We applied the model to the Fortore basin whose valley cuts the flysch terrain that constitute the framework of the so called "sub-Apennines" chain that is the most eastern part of the Southern Apennines (Italy). We will discuss its value according to its sensitivity to the used parameters and compare it to the actual data available for this basin.

The Waves to Weather Challenge: Do Large-Scale Equatorial Waves Modulate Regional Rainfall in Southern Vietnam?

NASA Astrophysics Data System (ADS)

Fink, A. H.; van der Linden, R.; Phan-Van, T.; Pinto, J. G.

2014-12-01

About 85% of the annual precipitation in southern Vietnam (ca. 8-12°N, 104-110°E) occurs during the southwest monsoon season (June to October). Large-scale equatorial waves like the Madden-Julian Oscillation (MJO) and Convectively Coupled Equatorial Waves (CCEWs) are known to modulate the large-scale convective activity, often indicated by variations in (filtered) satellite-observed outgoing longwave radiation (OLR) anomalies. The present contribution analyses and quantifies the role of the MJO and CCEWs for rainfall not only in southern and central Vietnam as a whole, but also for smaller climatological sub-regions. Using circum-equatorial NOAA OLR (15°S-15°N), prominent spectral peaks are identified in wavenumber-frequency diagrams along the dispersion curves for the solutions of the shallow water equations. They are interpreted as CCEWs. Meridionally averaged wave-filtered OLR and its time derivatives are used to define phases and amplitudes of CCEWs. This will allow determining active and inactive phases of CCEWs in the vicinity of Vietnam. Eastward propagating deep convection is also related to the 30-90-day MJO. The OLR MJO Index (OMI) is used for the definition of convectively active and inactive phases of the MJO. TRMM 3B42 V7, APHRODITE MA V1101 data, and rain gauge measurements are used to investigate the relation between tropical wave phases and amplitudes and precipitation in southern and central Vietnam and adjacent regions. Results using the OMI are compared with those using the Real-time Multivariate MJO (RMM) Index. The major findings are: (a) Precipitation amounts in southern Vietnam are higher during convectively active phases of the MJO and CCEWs. The waves differ in terms of their relative importance for rainfall enhancement. (b) For increasing CCEW amplitudes, the difference between area-averaged precipitation during inactive and active phases increases. We provide evidence that precipitation amounts are higher when multiple wave types are in their convectively active phases over the Vietnam region.

Northward extent of East Asian monsoon covaries with intensity on orbital and millennial timescales.

PubMed

Goldsmith, Yonaton; Broecker, Wallace S; Xu, Hai; Polissar, Pratigya J; deMenocal, Peter B; Porat, Naomi; Lan, Jianghu; Cheng, Peng; Zhou, Weijian; An, Zhisheng

2017-02-21

The magnitude, rate, and extent of past and future East Asian monsoon (EAM) rainfall fluctuations remain unresolved. Here, late Pleistocene-Holocene EAM rainfall intensity is reconstructed using a well-dated northeastern China closed-basin lake area record located at the modern northwestern fringe of the EAM. The EAM intensity and northern extent alternated rapidly between wet and dry periods on time scales of centuries. Lake levels were 60 m higher than present during the early and middle Holocene, requiring a twofold increase in annual rainfall, which, based on modern rainfall distribution, requires a ∼400 km northward expansion/migration of the EAM. The lake record is highly correlated with both northern and southern Chinese cave deposit isotope records, supporting rainfall "intensity based" interpretations of these deposits as opposed to an alternative "water vapor sourcing" interpretation. These results indicate that EAM intensity and the northward extent covary on orbital and millennial timescales. The termination of wet conditions at 5.5 ka BP (∼35 m lake drop) triggered a large cultural collapse of Early Neolithic cultures in north China, and possibly promoted the emergence of complex societies of the Late Neolithic.

Northward extent of East Asian monsoon covaries with intensity on orbital and millennial timescales

PubMed Central

Goldsmith, Yonaton; Broecker, Wallace S.; Xu, Hai; Polissar, Pratigya J.; deMenocal, Peter B.; Porat, Naomi; Lan, Jianghu; Cheng, Peng; Zhou, Weijian; An, Zhisheng

2017-01-01

The magnitude, rate, and extent of past and future East Asian monsoon (EAM) rainfall fluctuations remain unresolved. Here, late Pleistocene–Holocene EAM rainfall intensity is reconstructed using a well-dated northeastern China closed-basin lake area record located at the modern northwestern fringe of the EAM. The EAM intensity and northern extent alternated rapidly between wet and dry periods on time scales of centuries. Lake levels were 60 m higher than present during the early and middle Holocene, requiring a twofold increase in annual rainfall, which, based on modern rainfall distribution, requires a ∼400 km northward expansion/migration of the EAM. The lake record is highly correlated with both northern and southern Chinese cave deposit isotope records, supporting rainfall “intensity based” interpretations of these deposits as opposed to an alternative “water vapor sourcing” interpretation. These results indicate that EAM intensity and the northward extent covary on orbital and millennial timescales. The termination of wet conditions at 5.5 ka BP (∼35 m lake drop) triggered a large cultural collapse of Early Neolithic cultures in north China, and possibly promoted the emergence of complex societies of the Late Neolithic. PMID:28167754

Northward extent of East Asian monsoon covaries with intensity on orbital and millennial timescales

NASA Astrophysics Data System (ADS)

Goldsmith, Yonaton; Broecker, Wallace S.; Xu, Hai; Polissar, Pratigya J.; deMenocal, Peter B.; Porat, Naomi; Lan, Jianghu; Cheng, Peng; Zhou, Weijian; An, Zhisheng

2017-02-01

The magnitude, rate, and extent of past and future East Asian monsoon (EAM) rainfall fluctuations remain unresolved. Here, late Pleistocene-Holocene EAM rainfall intensity is reconstructed using a well-dated northeastern China closed-basin lake area record located at the modern northwestern fringe of the EAM. The EAM intensity and northern extent alternated rapidly between wet and dry periods on time scales of centuries. Lake levels were 60 m higher than present during the early and middle Holocene, requiring a twofold increase in annual rainfall, which, based on modern rainfall distribution, requires a ˜400 km northward expansion/migration of the EAM. The lake record is highly correlated with both northern and southern Chinese cave deposit isotope records, supporting rainfall “intensity based” interpretations of these deposits as opposed to an alternative “water vapor sourcing” interpretation. These results indicate that EAM intensity and the northward extent covary on orbital and millennial timescales. The termination of wet conditions at 5.5 ka BP (˜35 m lake drop) triggered a large cultural collapse of Early Neolithic cultures in north China, and possibly promoted the emergence of complex societies of the Late Neolithic.

Evaluating the efficacy of distributed detention structures to reduce downstream flooding under variable rainfall, antecedent soil, and structural storage conditions

NASA Astrophysics Data System (ADS)

Thomas, Nicholas W.; Arenas Amado, Antonio; Schilling, Keith E.; Weber, Larry J.

2016-10-01

This research systematically analyzed the influence of antecedent soil wetness, rainfall depth, and the subsequent impact on peak flows in a 45 km2 watershed. Peak flows increased with increasing antecedent wetness and rainfall depth, with the highest peak flows occurring under intense precipitation on wet soils. Flood mitigation structures were included and investigated under full and empty initial storage conditions. Peak flows were reduced at the outlet of the watershed by 3-17%. The highest peak flow reductions occurred in scenarios with dry soil, empty project storage, and low rainfall depths. These analyses showed that with increased rainfall depth, antecedent moisture conditions became increasingly less impactful. Scaling invariance of peak discharges were shown to hold true within this basin and were fit through ordinary least squares regression for each design scenario. Scale-invariance relationships were extrapolated beyond the outlet of the analyzed basin to the point of intersection of with and without structure scenarios. In each scenario extrapolated peak discharge benefits depreciated at a drainage area of approximately 100 km2. The associated drainage area translated to roughly 2 km downstream of the Beaver Creek watershed outlet. This work provides an example of internal watershed benefits of structural flood mitigation efforts, and the impact the may exert outside of the basin. Additionally, the influence of 1.8 million in flood reduction tools was not sufficient to routinely address downstream flood concerns, shedding light on the additional investment required to alter peak flows in large basins.

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.

Landslides in West Coast Metropolitan Areas: The Role of Extreme Weather Events

NASA Technical Reports Server (NTRS)

Biasutti, Michela; Seager, Richard; Kirschbaum, Dalia B.

2016-01-01

Rainfall-induced landslides represent a pervasive issue in areas where extreme rainfall intersects complex terrain. A farsighted management of landslide risk requires assessing how landslide hazard will change in coming decades and thus requires, inter alia, that we understand what rainfall events are most likely to trigger landslides and how global warming will affect the frequency of such weather events. We take advantage of 9 years of landslide occurrence data compiled by collating Google news reports and of a high-resolution satellite-based daily rainfall data to investigate what weather triggers landslide along the West Coast US. We show that, while this landslide compilation cannot provide consistent and widespread monitoring everywhere, it captures enough of the events in the major urban areas that it can be used to identify the relevant relationships between landslides and rainfall events in Puget Sound, the Bay Area, and greater Los Angeles. In all these regions, days that recorded landslides have rainfall distributions that are skewed away from dry and low-rainfall accumulations and towards heavy intensities. However, large daily accumulation is the main driver of enhanced hazard of landslides only in Puget Sound. There, landslide are often clustered in space and time and major events are primarily driven by synoptic scale variability, namely "atmospheric rivers" of high humidity air hitting anywhere along the West Coast, and the interaction of frontal system with the coastal orography. The relationship between landslide occurrences and daily rainfall is less robust in California, where antecedent precipitation (in the case of the Bay area) and the peak intensity of localized downpours at sub-daily time scales (in the case of Los Angeles) are key factors not captured by the same-day accumulations. Accordingly, we suggest that the assessment of future changes in landslide hazard for the entire the West Coast requires consideration of future changes in the occurrence and intensity of atmospheric rivers, in their duration and clustering, and in the occurrence of short-duration (sub-daily) extreme rainfall as well. Major regional landslide events, in which multiple occurrences are recorded in the catalog for the same day, are too rare to allow a statistical characterization of their triggering events, but a case study analysis indicates that a variety of synoptic-scale events can be involved, including not only atmospheric rivers but also broader cold- and warm-front precipitation. That a news-based catalog of landslides is accurate enough to allow the identification of different landslide/ rainfall relationships in the major urban areas along the US West Coast suggests that this technology can potentially be used for other English-language cities and could become an even more powerful tool if expanded to other languages and non-traditional news sources, such as social media.

Modeling the Large-scale Environments of Long-lived Mesoscale Convective Systems Conducive to Heavy Precipitation in the Central United States

NASA Astrophysics Data System (ADS)

Leung, L. R.; Houze, R.; Feng, Z.; Yang, Q.

2017-12-01

Mesoscale convective systems (MCSs) are important precipitation producers that account for 30-70% of warm season rainfall between the Rocky Mountains and Mississippi River and some 50-60% of tropical rainfall. Besides the tendency to produce floods, MCSs also carry with them a variety of attendant severe weather phenomena. Our recent analysis found that observed increases in springtime total and extreme rainfall in the central United States in the past 35 years are dominated by increased frequency and intensity of long-lasting MCSs. Understanding the environmental conditions producing long-lived MCSs is therefore a priority in determining how heavy precipitation events might change in character and location in a changing climate. Continental-scale convection-permitting simulations of the warm seasons using the WRF model reproduce realistic structure and frequency distribution of lifetime and event mean precipitation of MCSs over the central United States. The simulations show that MCSs systematically form over the central Great Plains ahead of a trough in the westerlies in combination with an enhanced low-level moist jet from the Gulf of Mexico. These environmental properties at the time of storm initiation are most prominent for the MCSs that persist for the longest times. MCSs reaching lifetimes of 9 h or more occur closer to the approaching trough than shorter-lived MCSs. These long-lived MCSs exhibit the strongest feedback to the environment through diabatic heating in the trailing regions of the MCSs that helps to maintain them over a long period of time. The identified large-scale and mesoscale ingredients provide a framework for understanding and modeling the potential changes in MCSs and associated hydrometeorological extremes in the future.

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

NASA Astrophysics Data System (ADS)

Johnson, Fiona; Sharma, Ashish

2011-04-01

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

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.

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.

Impact of Extensive Urbanization on Summertime Rainfall in the Beijing Region and the Role of Local Precipitation Recycling

NASA Astrophysics Data System (ADS)

Wang, Jun; Feng, Jinming; Yan, Zhongwei

2018-04-01

In this study, we conducted nested high-resolution simulations using the Weather Research and Forecasting model coupled with a single-layer urban canopy model to investigate the impact of extensive urbanization on regional precipitation over the Beijing-Tianjin-Hebei region in China. The results showed that extensive urbanization decreased precipitation considerably over and downwind of Beijing city. The prevalence of impermeable urban land inhibits local evaporation that feeds moisture into the overlying atmosphere, decreasing relative humidity and atmospheric instability. The dynamic precipitation recycling model was employed to estimate the precipitation that originates from local surface evaporation and large-scale advection of moisture. Results showed that about 11% of the urbanization-induced decrease in total precipitation over the Greater Beijing Region and its surroundings was contributed by the decrease in local recycled precipitation, while the other part (89%) was due to decreasing large-scale advected precipitation. Results suggest that the low evaporation from urban land surfaces not only reduces the supply of water vapor for local recycled precipitation directly but also decreases the convective available potential energy and hence the conversion efficiency of atmospheric moisture into rainfall. The urbanization-induced variations in local recycled precipitation were found to be correlated with the net atmospheric moisture flux on a monthly time scale.

Analysis of the convective timescale during the major floods in the NE Iberian Peninsula since 1871

NASA Astrophysics Data System (ADS)

Pino, David; Reynés, Artur; Mazon, Jordi; Carles Balasch, Josep; Lluis Ruiz-Bellet, Josep; Tuset, Jordi; Barriendos, Mariano; Castelltort, Xavier

2016-04-01

Floods are the most severe natural hazard in the western Mediterranean basin. They cause most of the damages and most of the victims. Some of the selected floods caused more than one hundred casualties each and a large quantity of damages in infrastructures. In a previous work (Balasch, et al., 2015), using the PREDIFLOOD database (Barriendos et al., 2014) we studied the atmospheric conditions that occurred during some of the most important floods occurred in the north-east of the Iberian Peninsula in the last centuries: 1874, 1875, 1894, 1897, 1898, 1901, 1907, 1913, 1919, 1932, 1937, 1940, 1962, 1963, 1977, 1994, 1996, and 2000. We analyzed the atmospheric synoptic situations at the time of each flood from the data provided by NOAA 20th Century Reanalysis and we compared it to the rainfall spatial distributions obtained with the hydrological modeling. In this work we enlarge the previous investigation by analyzing the evolution of a convective index proposed by Done et al. (2006) and modified by Molini et al. (2011). This index, called convective time scale, is obtained from the evolution of CAPE and is used to separate equilibrium and non-equilibrium convection. In the former, CAPE generated by large-scale processes is balanced by the consumption due to convection. In the second case, CAPE is created by large-scale processes over a long time and is rapidly consumed during outbreaks of convection. Both situations produced a totally different evolution of CAPE with low and approximately constant values in the first case and large and variable values in the second. Additionally, from this index it can be estimated the rainfall rate. We use data provided by NOAA 20th Century Reanalysis, to calculate the convective time scale and to analyze its evolution and horizontal distribution. We study the correspondence between the convective timescale, the season when the flood occurred, duration of the rainfall, and the specific peak flow rate of the flood. Finally, for the most recent episodes rainfall rate estimation from the convective timescale is compared with the observations. Balasch, J. C., Ruiz-Bellet, J. L., Tuset, J., Barriendos, M., Mazón, J., Pino, D. and Castelltort, X.: Transdisciplinary and multiscale reconstruction of the major flash floods in NE Iberian Peninsula. EGU General Assembly, 2015. Barriendos, M., Ruiz--Bellet, J. L., Tuset, J., Mazon, J., Balasch, J. C., Pino, D., Ayala, J. L.: The "Prediflood" database of historical floods in Catalonia (NE Iberian Peninsula) AD 1035--2013, and its potential applications in flood analysis, Hydrol. Earth Syst. Sci., 18, 4807-4823, 2014. Done, J. M., Craig, G. C., Gray, S. L., Clark, P. A., and Gray, M. E. B.: Mesoscale simulations of organized convection: Importance of convective equilibrium, Q. J. Roy. Meteor. Soc., 132, 737-756, 2006. Molini, L., Parodi, A., Rebora, N. and Craig, G. C.: Classifying severe rainfall events over Italy by hydrometeorological and dynamical criteria, Q. J. Roy. Meteor. Soc., 137, 148-154, 2011.

Rainfall simulation in education

NASA Astrophysics Data System (ADS)

Peters, Piet; Baartman, Jantiene; Gooren, Harm; Keesstra, Saskia

2016-04-01

Rainfall simulation has become an important method for the assessment of soil erosion and soil hydrological processes. For students, rainfall simulation offers an year-round, attractive and active way of experiencing water erosion, while not being dependent on (outdoors) weather conditions. Moreover, using rainfall simulation devices, they can play around with different conditions, including rainfall duration, intensity, soil type, soil cover, soil and water conservation measures, etc. and evaluate their effect on erosion and sediment transport. Rainfall simulators differ in design and scale. At Wageningen University, both BSc and MSc student of the curriculum 'International Land and Water Management' work with different types of rainfall simulation devices in three courses: - A mini rainfall simulator (0.0625m2) is used in the BSc level course 'Introduction to Land Degradation and Remediation'. Groups of students take the mini rainfall simulator with them to a nearby field location and test it for different soil types, varying from clay to more sandy, slope angles and vegetation or litter cover. The groups decide among themselves which factors they want to test and they compare their results and discuss advantage and disadvantage of the mini-rainfall simulator. - A medium sized rainfall simulator (0.238 m2) is used in the MSc level course 'Sustainable Land and Water Management', which is a field practical in Eastern Spain. In this course, a group of students has to develop their own research project and design their field measurement campaign using the transportable rainfall simulator. - Wageningen University has its own large rainfall simulation laboratory, in which a 15 m2 rainfall simulation facility is available for research. In the BSc level course 'Land and Water Engineering' Student groups will build slopes in the rainfall simulator in specially prepared containers. Aim is to experience the behaviour of different soil types or slope angles when (heavy) rain occurs. The MSc level course 'Fundamentals of Land Management' students carry out a hands-on practical in which they compare soil type and design and evaluate the effect of soil and water conservation measures. Also, MSc thesis research is being carried out using this facility. For instance, the distribution and movement of pesticide Glyphosate with sediment transportation was being quantified using the rainfall simulation facility.

Sub-seasonal behaviour of Asian summer monsoon under a changing climate: assessments using CMIP5 models

NASA Astrophysics Data System (ADS)

Sooraj, K. P.; Terray, Pascal; Xavier, Prince

2016-06-01

Numerous global warming studies show the anticipated increase in mean precipitation with the rising levels of carbon dioxide concentration. However, apart from the changes in mean precipitation, the finer details of daily precipitation distribution, such as its intensity and frequency (so called daily rainfall extremes), need to be accounted for while determining the impacts of climate changes in future precipitation regimes. Here we examine the climate model projections from a large set of Coupled Model Inter-comparison Project 5 models, to assess these future aspects of rainfall distribution over Asian summer monsoon (ASM) region. Our assessment unravels a north-south rainfall dipole pattern, with increased rainfall over Indian subcontinent extending into the western Pacific region (north ASM region, NASM) and decreased rainfall over equatorial oceanic convergence zone over eastern Indian Ocean region (south ASM region, SASM). This robust future pattern is well conspicuous at both seasonal and sub-seasonal time scales. Subsequent analysis, using daily rainfall events defined using percentile thresholds, demonstrates that mean rainfall changes over NASM region are mainly associated with more intense and more frequent extreme rainfall events (i.e. above 95th percentile). The inference is that there are significant future changes in rainfall probability distributions and not only a uniform shift in the mean rainfall over the NASM region. Rainfall suppression over SASM seems to be associated with changes involving multiple rainfall events and shows a larger model spread, thus making its interpretation more complex compared to NASM. Moisture budget diagnostics generally show that the low-level moisture convergence, due to stronger increase of water vapour in the atmosphere, acts positively to future rainfall changes, especially for heaviest rainfall events. However, it seems that the dynamic component of moisture convergence, associated with vertical motion, shows a strong spatial and rainfall category dependency, sometimes offsetting the effect of the water vapour increase. Additionally, we found that the moisture convergence is mainly dominated by the climatological vertical motion acting on the humidity changes and the interplay between all these processes proves to play a pivotal role for regulating the intensities of various rainfall events in the two domains.

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

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

Culture, hydrology, and other situational controls on atoll freshwater availability (Majuro, Republic of the Marshall Islands)

NASA Astrophysics Data System (ADS)

Shuster, W.

2016-12-01

The comparatively uncertain rainfall catch and rising seas in isolated North Pacific atoll communities has presented serious challenges to maintain human communities with freshwater volume. Moreover, the feudal hierarchy, which structures social and economic relationships among local governance and citizens contributes equally to problems and potential solutions. These relationships modulate the availability of critical ecosystem services generated by freshwater, with additional constraints contributed by climate change, rainfall variability (e.g., current El Niño climate pattern), and continuous threat of drought. The major freshwater resources for an atoll are the groundwater freshwater lens, residential and commercial rainwater harvesting, large-scale rainfall catchments (e.g., an airport runway), imported-virtual water, or desalinization subsidies. The significance of each of these resources scale across different atolls according to size, topography, soils, population, infrastructure, and land ownership. The potential integration and coordination of these water resources is largely unrealized due to land ownership, the lack of a contiguous catchment area, uneven and fractured governance. The situational aspects are further characterized by feuding among families and communities (some resource rich, some resource poor), and conflicting land use priorities where agriculture placement and practice can compromise the quality of already limited freshwater resources. This presentation uses the example of Majuro atoll (Republic of the Marshall Islands), field data and other observations, to illustrate sociohydrologic-drivers of freshwater availability, and suggests approaches that may improve on current and ongoing threats to public health and well-being.

Feasibility of Using Elastic Wave Velocity Monitoring for Early Warning of Rainfall-Induced Slope Failure.

PubMed

Chen, Yulong; Irfan, Muhammad; Uchimura, Taro; Zhang, Ke

2018-03-27

Rainfall-induced landslides are one of the most widespread slope instability phenomena posing a serious risk to public safety worldwide so that their temporal prediction is of great interest to establish effective warning systems. The objective of this study is to determine the effectiveness of elastic wave velocities in the surface layer of the slope in monitoring, prediction and early warning of landslide. The small-scale fixed and varied, and large-scale slope model tests were conducted. Analysis of the results has established that the elastic wave velocity continuously decreases in response of moisture content and deformation and there was a distinct surge in the decrease rate of wave velocity when failure was initiated. Based on the preliminary results of this analysis, the method using the change in elastic wave velocity proves superior for landslide early warning and suggests that a warning be issued at switch of wave velocity decrease rate.

Large Scale Meteorological Pattern of Extreme Rainfall in Indonesia

NASA Astrophysics Data System (ADS)

Kuswanto, Heri; Grotjahn, Richard; Rachmi, Arinda; Suhermi, Novri; Oktania, Erma; Wijaya, Yosep

2014-05-01

Extreme Weather Events (EWEs) cause negative impacts socially, economically, and environmentally. Considering these facts, forecasting EWEs is crucial work. Indonesia has been identified as being among the countries most vulnerable to the risk of natural disasters, such as floods, heat waves, and droughts. Current forecasting of extreme events in Indonesia is carried out by interpreting synoptic maps for several fields without taking into account the link between the observed events in the 'target' area with remote conditions. This situation may cause misidentification of the event leading to an inaccurate prediction. Grotjahn and Faure (2008) compute composite maps from extreme events (including heat waves and intense rainfall) to help forecasters identify such events in model output. The composite maps show large scale meteorological patterns (LSMP) that occurred during historical EWEs. Some vital information about the EWEs can be acquired from studying such maps, in addition to providing forecaster guidance. Such maps have robust mid-latitude meteorological patterns (for Sacramento and California Central Valley, USA EWEs). We study the performance of the composite approach for tropical weather condition such as Indonesia. Initially, the composite maps are developed to identify and forecast the extreme weather events in Indramayu district- West Java, the main producer of rice in Indonesia and contributes to about 60% of the national total rice production. Studying extreme weather events happening in Indramayu is important since EWEs there affect national agricultural and fisheries activities. During a recent EWE more than a thousand houses in Indramayu suffered from serious flooding with each home more than one meter underwater. The flood also destroyed a thousand hectares of rice plantings in 5 regencies. Identifying the dates of extreme events is one of the most important steps and has to be carried out carefully. An approach has been applied to identify the dates involving observations from multiple sites (rain gauges). The approach combines the POT (Peaks Over Threshold) with 'declustering' of the data to approximate independence based on the autocorrelation structure of each rainfall series. The cross correlation among sites is considered also to develop the event's criteria yielding a rational choice of the extreme dates given the 'spotty' nature of the intense convection. Based on the identified dates, we are developing a supporting tool for forecasting extreme rainfall based on the corresponding large-scale meteorological patterns (LSMPs). The LSMPs methodology focuses on the larger-scale patterns that the model are better able to forecast, as those larger-scale patterns create the conditions fostering the local EWE. Bootstrap resampling method is applied to highlight the key features that statistically significant with the extreme events. Grotjahn, R., and G. Faure. 2008: Composite Predictor Maps of Extraordinary Weather Events in the Sacramento California Region. Weather and Forecasting. 23: 313-335.

What aspects of future rainfall changes matter for crop yields in West Africa?

NASA Astrophysics Data System (ADS)

Guan, Kaiyu; Sultan, Benjamin; Biasutti, Michela; Baron, Christian; Lobell, David B.

2015-10-01

How rainfall arrives, in terms of its frequency, intensity, the timing and duration of rainy season, may have a large influence on rainfed agriculture. However, a thorough assessment of these effects is largely missing. This study combines a new synthetic rainfall model and two independently validated crop models (APSIM and SARRA-H) to assess sorghum yield response to possible shifts in seasonal rainfall characteristics in West Africa. We find that shifts in total rainfall amount primarily drive the rainfall-related crop yield change, with less relevance to intraseasonal rainfall features. However, dry regions (total annual rainfall below 500 mm/yr) have a high sensitivity to rainfall frequency and intensity, and more intense rainfall events have greater benefits for crop yield than more frequent rainfall. Delayed monsoon onset may negatively impact yields. Our study implies that future changes in seasonal rainfall characteristics should be considered in designing specific crop adaptations in West Africa.

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

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

Decision tree analysis of factors influencing rainfall-related building damage

NASA Astrophysics Data System (ADS)

Spekkers, M. H.; Kok, M.; Clemens, F. H. L. R.; ten Veldhuis, J. A. E.

2014-04-01

Flood damage prediction models are essential building blocks in flood risk assessments. Little research has been dedicated so far to damage of small-scale urban floods caused by heavy rainfall, while there is a need for reliable damage models for this flood type among insurers and water authorities. The aim of this paper is to investigate a wide range of damage-influencing factors and their relationships with rainfall-related damage, using decision tree analysis. For this, district-aggregated claim data from private property insurance companies in the Netherlands were analysed, for the period of 1998-2011. The databases include claims of water-related damage, for example, damages related to rainwater intrusion through roofs and pluvial flood water entering buildings at ground floor. Response variables being modelled are average claim size and claim frequency, per district per day. The set of predictors include rainfall-related variables derived from weather radar images, topographic variables from a digital terrain model, building-related variables and socioeconomic indicators of households. Analyses were made separately for property and content damage claim data. Results of decision tree analysis show that claim frequency is most strongly associated with maximum hourly rainfall intensity, followed by real estate value, ground floor area, household income, season (property data only), buildings age (property data only), ownership structure (content data only) and fraction of low-rise buildings (content data only). It was not possible to develop statistically acceptable trees for average claim size, which suggest that variability in average claim size is related to explanatory variables that cannot be defined at the district scale. Cross-validation results show that decision trees were able to predict 22-26% of variance in claim frequency, which is considerably better compared to results from global multiple regression models (11-18% of variance explained). Still, a large part of the variance in claim frequency is left unexplained, which is likely to be caused by variations in data at subdistrict scale and missing explanatory variables.

The Amazon and climate

NASA Technical Reports Server (NTRS)

Nobre, C. A.

1984-01-01

The climatologies of cloudiness and precipitation for the Amazon, are reviewed and the physical causes of some of the observed features and those which are not well known are explained. The atmospheric circulation over the Amazon is discussed on the large scale tropical circulations forced by deep diabatic heating sources. Weather deforestation which leads to a reduction in evapotranspiration into the atmosphere, and a reduction in precipitation and its implicated for the gobal climate is discussed. It is indicated that a large scale clearing of tropical rainforests there would be a reduction in rainfall which would have global effects on climate and weather both in the tropical and extratropical regions.

Potential Predictability and Prediction Skill for Southern Peru Summertime Rainfall

NASA Astrophysics Data System (ADS)

WU, S.; Notaro, M.; Vavrus, S. J.; Mortensen, E.; Block, P. J.; Montgomery, R. J.; De Pierola, J. N.; Sanchez, C.

2016-12-01

The central Andes receive over 50% of annual climatological rainfall during the short period of January-March. This summertime rainfall exhibits strong interannual and decadal variability, including severe drought events that incur devastating societal impacts and cause agricultural communities and mining facilities to compete for limited water resources. An improved seasonal prediction skill of summertime rainfall would aid in water resource planning and allocation across the water-limited southern Peru. While various underlying mechanisms have been proposed by past studies for the drivers of interannual variability in summertime rainfall across southern Peru, such as the El Niño-Southern Oscillation (ENSO), Madden Julian Oscillation (MJO), and extratropical forcings, operational forecasts continue to be largely based on rudimentary ENSO-based indices, such as NINO3.4, justifying further exploration of predictive skill. In order to bridge this gap between the understanding of driving mechanisms and the operational forecast, we performed systematic studies on the predictability and prediction skill of southern Peru summertime rainfall by constructing statistical forecast models using best available weather station and reanalysis datasets. At first, by assuming the first two empirical orthogonal functions (EOFs) of summertime rainfall are predictable, the potential predictability skill was evaluated for southern Peru. Then, we constructed a simple regression model, based on the time series of tropical Pacific sea-surface temperatures (SSTs), and a more advanced Linear Inverse Model (LIM), based on the EOFs of tropical ocean SSTs and large-scale atmosphere variables from reanalysis. Our results show that the LIM model consistently outperforms the more rudimentary regression models on the forecast skill of domain averaged precipitation index and individual station indices. The improvement of forecast correlation skill ranges from 10% to over 200% for different stations. Further analysis shows that this advantage of LIM is likely to arise from its representation of local zonal winds and the position of Intertropical Convergence Zone (ITCZ).

United States Temperature and Precipitation Extremes: Phenomenology, Large-Scale Organization, Physical Mechanisms and Model Representation

NASA Astrophysics Data System (ADS)

Black, R. X.

2017-12-01

We summarize results from a project focusing on regional temperature and precipitation extremes over the continental United States. Our project introduces a new framework for evaluating these extremes emphasizing their (a) large-scale organization, (b) underlying physical sources (including remote-excitation and scale-interaction) and (c) representation in climate models. Results to be reported include the synoptic-dynamic behavior, seasonality and secular variability of cold waves, dry spells and heavy rainfall events in the observational record. We also study how the characteristics of such extremes are systematically related to Northern Hemisphere planetary wave structures and thus planetary- and hemispheric-scale forcing (e.g., those associated with major El Nino events and Arctic sea ice change). The underlying physics of event onset are diagnostically quantified for different categories of events. Finally, the representation of these extremes in historical coupled climate model simulations is studied and the origins of model biases are traced using new metrics designed to assess the large-scale atmospheric forcing of local extremes.

Water availability as a driver of spatial and temporal variability in vegetation in the La Mancha plain (Spain): Implications for the land-surface energy, water and carbon budget

NASA Astrophysics Data System (ADS)

Los, Sietse

2017-04-01

Vegetation is water limited in large areas of Spain and therefore a close link exists between vegetation greenness observed from satellite and moisture availability. Here we exploit this link to infer spatial and temporal variability in moisture from MODIS NDVI data and thermal data. Discrepancies in the precipitation - vegetation relationship indicate areas with an alternative supply of water (i.e. not rainfall), this can be natural where moisture is supplied by upwelling groundwater, or can be artificial where crops are irrigated. As a result spatial and temporal variability in vegetation in the La Mancha Plain appears closely linked to topography, geology, rainfall and land use. Crop land shows large variability in year-to-year vegetation greenness; for some areas this variability is linked to variability in rainfall but in other cases this variability is linked to irrigation. The differences in irrigation treatment within one plant functional type, in this case crops, will lead to errors in land surface models when ignored. The magnitude of these effects on the energy, carbon and water balance are assessed at the scale of 250 m to 200 km. Estimating the water balance correctly is of particular important since in some areas in Spain more water is used for irrigation than is supplemented by rainfall.

Improving Assimilated Global Data Sets using TMI Rainfall and Columnar Moisture Observations

NASA Technical Reports Server (NTRS)

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

1999-01-01

A global analysis that optimally combine observations from diverse sources with physical models of atmospheric and land processes can provide a comprehensive description of the climate systems. Currently, such data products contain significant errors in primary hydrological fields such as precipitation and evaporation, especially in the tropics. In this study, we show that assimilating precipitation and total precipitable water (TPW) retrievals derived from the TRMM Microwave Imager (TMI) improves not only the hydrological cycle but also key climate parameters such as clouds, radiation, and the large-scale circulation produced by the Goddard Earth Observing System (GEOS) data assimilation system (DAS). In particular, assimilating TMI rain improves clouds and radiation in areas of active convection, as well as the latent heating distribution and the large-scale motion field in the tropics, while assimilating TMI TPW heating distribution and the large-scale motion field in the tropics, while assimilating TMI TPW retrievals leads to reduced moisture biases and improved radiative fluxes in clear-sky regions. The improved analysis also improves short-range forecasts in the tropics. Ensemble forecasts initialized with the GEOS analysis incorporating TMI rain rates and TPW yield smaller biases in tropical precipitation forecasts beyond 1 day and better 500 hPa geopotential height forecasts up to 5 days. Results of this study demonstrate the potential of using high-quality space-borne rainfall and moisture observations to improve the quality of assimilated global data for climate analysis and weather forecasting applications

Temporal evolution of the spatial covariability of rainfall in South America

NASA Astrophysics Data System (ADS)

Ciemer, Catrin; Boers, Niklas; Barbosa, Henrique M. J.; Kurths, Jürgen; Rammig, Anja

2017-10-01

The climate of South America exhibits pronounced differences between rainy and dry seasons, associated with specific synoptic features such as the establishment of the South Atlantic convergence zone. Here, we analyze the spatiotemporal correlation structure and in particular teleconnections of daily rainfall associated with these features by means of evolving complex networks. A modification of Pearson's correlation coefficient is introduced to handle the intricate statistical properties of daily rainfall. On this basis, spatial correlation networks are constructed, and new appropriate network measures are introduced in order to analyze the temporal evolution of the networks' characteristics. We particularly focus on the identification of coherent areas of similar rainfall patterns and previously unknown teleconnection structures between remote areas. We show that the monsoon onset is characterized by an abrupt transition from erratic to organized regional connectivity that prevails during the monsoon season, while only the onset times themselves exhibit anomalous large-scale organization of teleconnections. Furthermore, we reveal that the two mega-droughts in the Amazon basin were already announced in the previous year by an anomalous behavior of the connectivity structure.

Attribution of extreme precipitation in the lower reaches of the Yangtze River during May 2016

NASA Astrophysics Data System (ADS)

Li, Chunxiang; Tian, Qinhua; Yu, Rong; Zhou, Baiquan; Xia, Jiangjiang; Burke, Claire; Dong, Buwen; Tett, Simon F. B.; Freychet, Nicolas; Lott, Fraser; Ciavarella, Andrew

2018-01-01

May 2016 was the third wettest May on record since 1961 over central eastern China based on station observations, with total monthly rainfall 40% more than the climatological mean for 1961-2013. Accompanying disasters such as waterlogging, landslides and debris flow struck part of the lower reaches of the Yangtze River. Causal influence of anthropogenic forcings on this event is investigated using the newly updated Met Office Hadley Centre system for attribution of extreme weather and climate events. Results indicate that there is a significant increase in May 2016 rainfall in model simulations relative to the climatological period, but this increase is largely attributable to natural variability. El Niño years have been found to be correlated with extreme rainfall in the Yangtze River region in previous studies—the strong El Niño of 2015-2016 may account for the extreme precipitation event in 2016. However, on smaller spatial scales we find that anthropogenic forcing has likely played a role in increasing the risk of extreme rainfall to the north of the Yangtze and decreasing it to the south.

The Global Precipitation Climatology Project: First Algorithm Intercomparison Project

NASA Technical Reports Server (NTRS)

Arkin, Phillip A.; Xie, Pingping

1994-01-01

The Global Precipitation Climatology Project (GPCP) was established by the World Climate Research Program to produce global analyses of the area- and time-averaged precipitation for use in climate research. To achieve the required spatial coverage, the GPCP uses simple rainfall estimates derived from IR and microwave satellite observations. In this paper, we describe the GPCP and its first Algorithm Intercomparison Project (AIP/1), which compared a variety of rainfall estimates derived from Geostationary Meteorological Satellite visible and IR observations and Special Sensor Microwave/Imager (SSM/I) microwave observations with rainfall derived from a combination of radar and raingage data over the Japanese islands and the adjacent ocean regions during the June and mid-July through mid-August periods of 1989. To investigate potential improvements in the use of satellite IR data for the estimation of large-scale rainfall for the GPCP, the relationship between rainfall and the fractional coverage of cold clouds in the AIP/1 dataset is examined. Linear regressions between fractional coverage and rainfall are analyzed for a number of latitude-longitude areas and for a range of averaging times. The results show distinct differences in the character of the relationship for different portions of the area. These results suggest that the simple IR-based estimation technique currently used in the GPCP can be used to estimate rainfall for global tropical and subtropical areas, provided that a method for adjusting the proportional coefficient for varying areas and seasons can be determined.

Changing character of rainfall in eastern China, 1951–2007

NASA Astrophysics Data System (ADS)

Day, Jesse A.; Fung, Inez; Liu, Weihan

2018-03-01

The topography and continental configuration of East Asia favor the year-round existence of storm tracks that extend thousands of kilometers from China into the northwestern Pacific Ocean, producing zonally elongated patterns of rainfall that we call “frontal rain events.” In spring and early summer (known as “Meiyu Season”), frontal rainfall intensifies and shifts northward during a series of stages collectively known as the East Asian summer monsoon. Using a technique called the Frontal Rain Event Detection Algorithm, we create a daily catalog of all frontal rain events in east China during 1951–2007, quantify their attributes, and classify all rainfall on each day as either frontal, resulting from large-scale convergence, or nonfrontal, produced by local buoyancy, topography, or typhoons. Our climatology shows that the East Asian summer monsoon consists of a series of coupled changes in frontal rain event frequency, latitude, and daily accumulation. Furthermore, decadal changes in the amount and distribution of rainfall in east China are overwhelmingly due to changes in frontal rainfall. We attribute the “South Flood–North Drought” pattern observed beginning in the 1980s to changes in the frequency of frontal rain events, while the years 1994–2007 witnessed an uptick in event daily accumulation relative to the rest of the study years. This particular signature may reflect the relative impacts of global warming, aerosol loading, and natural variability on regional rainfall, potentially via shifting the East Asian jet stream.

Modeling rainfall infiltration on hillslopes using Flux-concentration relation and time compression approximation

NASA Astrophysics Data System (ADS)

Wang, Jie; Chen, Li; Yu, Zhongbo

2018-02-01

Rainfall infiltration on hillslopes is an important issue in hydrology, which is related to many environmental problems, such as flood, soil erosion, and nutrient and contaminant transport. This study aimed to improve the quantification of infiltration on hillslopes under both steady and unsteady rainfalls. Starting from Darcy's law, an analytical integral infiltrability equation was derived for hillslope infiltration by use of the flux-concentration relation. Based on this equation, a simple scaling relation linking the infiltration times on hillslopes and horizontal planes was obtained which is applicable for both small and large times and can be used to simplify the solution procedure of hillslope infiltration. The infiltrability equation also improved the estimation of ponding time for infiltration under rainfall conditions. For infiltration after ponding, the time compression approximation (TCA) was applied together with the infiltrability equation. To improve the computational efficiency, the analytical integral infiltrability equation was approximated with a two-term power-like function by nonlinear regression. Procedures of applying this approach to both steady and unsteady rainfall conditions were proposed. To evaluate the performance of the new approach, it was compared with the Green-Ampt model for sloping surfaces by Chen and Young (2006) and Richards' equation. The proposed model outperformed the sloping Green-Ampt, and both ponding time and infiltration predictions agreed well with the solutions of Richards' equation for various soil textures, slope angles, initial water contents, and rainfall intensities for both steady and unsteady rainfalls.

Establish susceptibility and risk assessment models for rainfall-induced landslide: A case in Central Taiwan

NASA Astrophysics Data System (ADS)

Wu, Chunhung; Huang, Jyuntai

2017-04-01

Most of the landslide cases in Taiwan were triggered by rainfall or earthquake events. The heavy rainfall in the typhoon seasons, from June to October, causes the landslide hazard more serious. Renai Towhship is of the most large landslide cases after 2009 Typhoon Morakot (from Aug. 5 to Aug. 10, 2009) in Taiwan. Around 2,744 landslides cases with the total landslide area of 21.5 km2 (landslide ratio =1.8%), including 26 large landslide cases, induced after 2009 Typhoon Morakot in Renai Towhship. The area of each large landslides case is more than 0.1 km2, and the area of the largest case is around 0.96 km2. 58% of large landslide cases locate in the area with metamorphosed sandstone. The mean slope of 26 large landslide cases ranges from 15 degree to 56 degree, and the accumulated rainfall during 2009 Typhoon Morakot ranges from 530 mm to 937 mm. Three methods, including frequency ratio method (abbreviated as FR), weights of evidence method (abbreviated as WOE), and logistic regression method (abbreviated as LR), are used in this study to establish the landslides susceptibility in the Renai Township, Nantou County, Taiwan. Eight landslide related-factors, including elevation, slope, aspect, geology, land use, distance to drainage, distance to fault, accumulation rainfall during 2009 Typhoon Morakot, are used to establish the landslide susceptibility models in this study. The landslide inventory after 2009 Typhoon Morakot is also used to test the model performance in this study. The mean accumulated rainfall in Renai Township during 2009 typhoon Morakot was around 735 mm with the maximum 1-hr, 3-hrs, and 6-hrs rainfall intensity of 44 mm/1-hr, 106 mm/3-hrs and 204 mm/6-hrs, respectively. The range of original susceptibility values established by three methods are 4.0 to 20.9 for FR, -33.8 to -16.1 for WOE, and -41.7 to 5.7 for LR, and the mean landslide susceptibility value are 8.0, -24.6 and 0.38, respectively. The AUC values are 0.815 for FR, 0.816 for WOE, and 0.823 for LR. The study normalized the susceptibility value range of three landslide susceptibility models to 0 to 1 to deeply compare the model performance. The normalized landslide susceptibility value > 0.5 and ≦0.5 are regarded as predicted-landslide area and predicted-not-landslide area. The ratio of the area in the predicted-landslide area to the total area is 3.0% for FR, 71.4% for WOE, and 26.5% for LR. And the correct ratio is 65.5% for FR, 61.9% for WOE, 74.5% for LR. The study adopted 14 rainfall stations with more than 20 years daily rainfall data in Renai Township to estimate the 24 hrs accumulated rainfall with different RPYs. Landslide susceptibility map under 24 hrs accumulated rainfall distribution with different RPYs is used to estimate the landslide disaster location and scale. The landslide risk under different RPYs in Renai Township is calculated as 2.62 billion for 5 RPYs, 3.06 billion for 10 RPYs, 4.69 billion for 25 RPYs, 5.97 billion for 50 RPYs, 6.98 billion for 100 RPYs, and 8.23 billion for 200 RPYs, respectively.

Monsoon Rainfall and Landslides in Nepal

NASA Astrophysics Data System (ADS)

Dahal, R. K.; Hasegawa, S.; Bhandary, N. P.; Yatabe, R.

2009-12-01

A large number of human settlements on the Nepal Himalayas are situated either on old landslide mass or on landslide-prone areas. As a result, a great number of people are affected by large- and small-scale landslides all over the Himalayas especially during monsoon periods. In Nepal, only in the half monsoon period (June 10 to August 15), 70, 50 and 68 people were killed from landslides in 2007, 2008 and 2009, respectively. In this context, this paper highlights monsoon rainfall and their implications in the Nepal Himalaya. In Nepal, monsoon is major source of rainfall in summer and approximately 80% of the annual total rainfall occurs from June to September. The measured values of mean annual precipitation in Nepal range from a low of approximately 250 mm at area north of the Himalaya to many areas exceeding 6,000 mm. The mean annual rainfall varying between 1500 mm and 2500 mm predominate over most of the country. In Nepal, the daily distribution of precipitation during rainy season is also uneven. Sometime 10% of the total annual precipitation can occur in a single day. Similarly, 50% total annual rainfall also can occur within 10 days of monsoon. This type of uneven distribution plays an important role in triggering many landslides in Nepal. When spatial distribution of landslides was evaluated from record of more than 650 landslides, it is found that more landslides events were concentrated at central Nepal in the area of high mean annual rainfall. When monsoon rainfall and landslide relationship was taken into consideration, it was noticed that a considerable number of landslides were triggered in the Himalaya by continuous rainfall of 3 to 90 days. It has been noticed that continuous rainfall of few days (5 days or 7 days or 10 days) are usually responsible for landsliding in the Nepal Himalaya. Monsoon rains usually fall with interruptions of 2-3 days and are generally characterized by low intensity and long duration. Thus, there is a strong role of antecedent rainfall in triggering landslides. It is noticed that a moderate correlation exists between the antecedent rainfalls of 3 to 10 days and the daily rainfall at failure in the Nepal Himalaya. The rainfall thresholds are utilized to develop early warning systems. Taking reference of the intensity-duration threshold and normalized rainfall intensity threshold, two proto-type models of early warning systems (RIEWS and N-RIEWS) are proposed. Early warning models show less time for evacuation in the case of short duration and high intensity rainfall, whereas for long duration rainfall, warning time is enough and when warning information disseminate to the people, people will aware to possible landslide risk. In the meantime, they will be mentally ready to tackle with possible disaster of coming hours or days and will avoid the consequences. On the basis of coarse hydro-meteorological data of developing country like Nepal, this simple and rather easy model of early warning will certainly help to reduce fatalities from landslides.

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.

What rainfall events trigger landslides on the West Coast US?

NASA Astrophysics Data System (ADS)

Biasutti, Michela; Seager, Richard; Kirschbaum, Dalia

2016-04-01

A dataset of landslide occurrences compiled by collating google news reports covers 9 full years of data. We show that, while this compilation cannot provide consistent and widespread monitoring everywhere, it is adequate to capture the distribution of events in the major urban areas of the West Coast US and it can be used to provide a quantitative relationship between landslides and rainfall events. The case of the Seattle metropolitan area is presented as an example. The landslide dataset shows a clear seasonality in landslide occurrence, corresponding to the seasonality of rainfall, modified by the accumulation of soil moisture as winter progresses. Interannual variability of landslide occurrences is also linked to interannual variability of monthly rainfall. In most instances, landslides are clustered on consecutive days or at least within the same pentad and correspond to days of large rainfall accumulation at the regional scale. A joint analysis of the landslide data and of the high-resolution PRISM daily rainfall accumulation shows that on days when landslides occurred, the distribution of rainfall was shifted, with rainfall accumulation higher than 10mm/day being more common. Accumulations above 50mm/day much increase the probability of landslides, including the possibility of a major landslide event (one with multiple landslides in a day). The synoptic meteorological conditions associated with these major events show a mid-tropospheric ridge to the south of the target area steering a surface low and bringing enhanced precipitable water towards the Pacific North West. The interaction of the low-level flow with the local orography results in instances of a strong Puget Sound Convergence Zone, with widespread rainfall accumulation above 30mm/day and localized maxima as high as 100mm/day or more.

Influence of climate variability versus change at multi-decadal time scales on hydrological extremes

NASA Astrophysics Data System (ADS)

Willems, Patrick

2014-05-01

Recent studies have shown that rainfall and hydrological extremes do not randomly occur in time, but are subject to multidecadal oscillations. In addition to these oscillations, there are temporal trends due to climate change. Design statistics, such as intensity-duration-frequency (IDF) for extreme rainfall or flow-duration-frequency (QDF) relationships, are affected by both types of temporal changes (short term and long term). This presentation discusses these changes, how they influence water engineering design and decision making, and how this influence can be assessed and taken into account in practice. The multidecadal oscillations in rainfall and hydrological extremes were studied based on a technique for the identification and analysis of changes in extreme quantiles. The statistical significance of the oscillations was evaluated by means of a non-parametric bootstrapping method. Oscillations in large scale atmospheric circulation were identified as the main drivers for the temporal oscillations in rainfall and hydrological extremes. They also explain why spatial phase shifts (e.g. north-south variations in Europe) exist between the oscillation highs and lows. Next to the multidecadal climate oscillations, several stations show trends during the most recent decades, which may be attributed to climate change as a result of anthropogenic global warming. Such attribution to anthropogenic global warming is, however, uncertain. It can be done based on simulation results with climate models, but it is shown that the climate model results are too uncertain to enable a clear attribution. Water engineering design statistics, such as extreme rainfall IDF or peak or low flow QDF statistics, obviously are influenced by these temporal variations (oscillations, trends). It is shown in the paper, based on the Brussels 10-minutes rainfall data, that rainfall design values may be about 20% biased or different when based on short rainfall series of 10 to 15 years length, and still 8% for series of 25 years lengths. Methods for bias correction are demonstrated. The definition of "bias" depends on a number of factors, which needs further debate in the hydrological and water engineering community. References: Willems P. (2013), 'Multidecadal oscillatory behaviour of rainfall extremes in Europe', Climatic Change, 120(4), 931-944 Willems, P. (2013). 'Adjustment of extreme rainfall statistics accounting for multidecadal climate oscillations', Journal of Hydrology, 490, 126-133 Willems, P., Olsson, J., Arnbjerg-Nielsen, K., Beecham, S., Pathirana, A., Bülow Gregersen, I., Madsen, H., Nguyen, V-T-V. (2012), 'Impacts of climate change on rainfall extremes and urban drainage', IWA Publishing, 252p., Paperback Print ISBN 9781780401256; Ebook ISBN 9781780401263

Rainfall From Resolved Rather Than Parameterized Processes Better Represents the Present‐Day and Climate Change Response of Moderate Rates in the Community Atmosphere Model

PubMed Central

Pritchard, Michael S.; O'Brien, Travis A.; Timmermans, Ben W.

2018-01-01

Abstract Deficiencies in the parameterizations of convection used in global climate models often lead to a distorted representation of the simulated rainfall intensity distribution (i.e., too much rainfall from weak rain rates). While encouraging improvements in high percentile rainfall intensity have been found as the horizontal resolution of the Community Atmosphere Model is increased to ∼25 km, we demonstrate no corresponding improvement in the moderate rain rates that generate the majority of accumulated rainfall. Using a statistical framework designed to emphasize links between precipitation intensity and accumulated rainfall beyond just the frequency distribution, we show that CAM cannot realistically simulate moderate rain rates, and cannot capture their intensification with climate change, even as resolution is increased. However, by separating the parameterized convective and large‐scale resolved contributions to total rainfall, we find that the intensity, geographic pattern, and climate change response of CAM's large‐scale rain rates are more consistent with observations (TRMM 3B42), superparameterization, and theoretical expectations, despite issues with parameterized convection. Increasing CAM's horizontal resolution does improve the representation of total rainfall intensity, but not due to changes in the intensity of large‐scale rain rates, which are surprisingly insensitive to horizontal resolution. Rather, improvements occur through an increase in the relative contribution of the large‐scale component to the total amount of accumulated rainfall. Analysis of sensitivities to convective timescale and entrainment rate confirm the importance of these parameters in the possible development of scale‐aware parameterizations, but also reveal unrecognized trade‐offs from the entanglement of precipitation frequency and total amount. PMID:29861837

Satellite-based Flood Modeling Using TRMM-based Rainfall Products

PubMed Central

Harris, Amanda; Rahman, Sayma; Hossain, Faisal; Yarborough, Lance; Bagtzoglou, Amvrossios C.; Easson, Greg

2007-01-01

Increasingly available and a virtually uninterrupted supply of satellite-estimated rainfall data is gradually becoming a cost-effective source of input for flood prediction under a variety of circumstances. However, most real-time and quasi-global satellite rainfall products are currently available at spatial scales ranging from 0.25° to 0.50° and hence, are considered somewhat coarse for dynamic hydrologic modeling of basin-scale flood events. This study assesses the question: what are the hydrologic implications of uncertainty of satellite rainfall data at the coarse scale? We investigated this question on the 970 km2 Upper Cumberland river basin of Kentucky. The satellite rainfall product assessed was NASA's Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) product called 3B41RT that is available in pseudo real time with a latency of 6-10 hours. We observed that bias adjustment of satellite rainfall data can improve application in flood prediction to some extent with the trade-off of more false alarms in peak flow. However, a more rational and regime-based adjustment procedure needs to be identified before the use of satellite data can be institutionalized among flood modelers. PMID:28903302

Fast Adjustments of the Asian Summer Monsoon to Anthropogenic Aerosols

NASA Astrophysics Data System (ADS)

Li, Xiaoqiong; Ting, Mingfang; Lee, Dong Eun

2018-01-01

Anthropogenic aerosols are a major factor contributing to human-induced climate change, particularly over the densely populated Asian monsoon region. Understanding the physical processes controlling the aerosol-induced changes in monsoon rainfall is essential for reducing the uncertainties in the future projections of the hydrological cycle. Here we use multiple coupled and atmospheric general circulation models to explore the physical mechanisms for the aerosol-driven monsoon changes on different time scales. We show that anthropogenic aerosols induce an overall reduction in monsoon rainfall and circulation, which can be largely explained by the fast adjustments over land north of 20∘N. This fast response occurs before changes in sea surface temperature (SST), largely driven by aerosol-cloud interactions. However, aerosol-induced SST feedbacks (slow response) cause substantial changes in the monsoon meridional circulation over the oceanic regions. Both the land-ocean asymmetry and meridional temperature gradient are key factors in determining the overall monsoon circulation response.

Enhanced Orographic Tropical Rainfall: An Study of the Colombia's rainfall

NASA Astrophysics Data System (ADS)

Peñaranda, V. M.; Hoyos Ortiz, C. D.; Mesa, O. J.

2015-12-01

Convection in tropical regions may be enhanced by orographic barriers. The orographic enhancement is an intensification of rain rates caused by the forced lifting of air over a mountainous structure. Orographic heavy rainfall events, occasionally, comes along by flooding, debris flow and substantial amount of looses, either economics or human lives. Most of the heavy convective rainfall events, occurred in Colombia, have left a lot of victims and material damages by flash flooding. An urgent action is required by either scientific communities or society, helping to find preventive solutions against these kind of events. Various scientific literature reports address the feedback process between the convection and the local orographic structures. The orographic enhancement could arise by several physical mechanism: precipitation transport on leeward side, convection triggered by the forcing of air over topography, the seeder-feeder mechanism, among others. The identification of the physical mechanisms for orographic enhancement of rainfall has not been studied over Colombia. As far as we know, orographic convective tropical rainfall is just the main factor for the altitudinal belt of maximum precipitation, but the lack of detailed hydro-meteorological measurements have precluded a complete understanding of the tropical rainfall in Colombia and its complex terrain. The emergence of the multifractal theory for rainfall has opened a field of research which builds a framework for parsimonious modeling of physical process. Studies about the scaling behavior of orographic rainfall have found some modulating functions between the rainfall intensity probability distribution and the terrain elevation. The overall objective is to advance in the understanding of the orographic influence over the Colombian tropical rainfall based on observations and scaling-analysis techniques. We use rainfall maps, weather radars scans and ground-based rainfall data. The research strategy is the analysis of rainfall fields via first-order statistical properties, scaling functions, structure functions and spectral analysis, taking into account cloud-motion directions over mountainous slopes (windward/leeward side) and timing of the diurnal cycle. The analysis is developed for some Colombia's locations.

Large Scale Water Vapor Sources Relative to the October 2000 Piedmont Flood

NASA Technical Reports Server (NTRS)

Turato, Barbara; Reale, Oreste; Siccardi, Franco

2003-01-01

Very intense mesoscale or synoptic-scale rainfall events can occasionally be observed in the Mediterranean region without any deep cyclone developing over the areas affected by precipitation. In these perplexing cases the synoptic situation can superficially look similar to cases in which very little precipitation occurs. These situations could possibly baffle the operational weather forecasters. In this article, the major precipitation event that affected Piedmont (Italy) between 13 and 16 October 2000 is investigated. This is one of the cases in which no intense cyclone was observed within the Mediterranean region at any time, only a moderate system was present, and yet exceptional rainfall and flooding occurred. The emphasis of this study is on the moisture origin and transport. Moisture and energy balances are computed on different space- and time-scales, revealing that precipitation exceeds evaporation over an area inclusive of Piedmont and the northwestern Mediterranean region, on a time-scale encompassing the event and about two weeks preceding it. This is suggestive of an important moisture contribution originating from outside the region. A synoptic and dynamic analysis is then performed to outline the potential mechanisms that could have contributed to the large-scale moisture transport. The central part of the work uses a quasi-isentropic water-vapor back trajectory technique. The moisture sources obtained by this technique are compared with the results of the balances and with the synoptic situation, to unveil possible dynamic mechanisms and physical processes involved. It is found that moisture sources on a variety of atmospheric scales contribute to this event. First, an important contribution is caused by the extratropical remnants of former tropical storm Leslie. The large-scale environment related to this system allows a significant amount of moisture to be carried towards Europe. This happens on a time- scale of about 5-15 days preceding the Piedmont event. Second, water-vapor intrusions from the African Inter-Tropical Convergence Zone and evaporation from the eastern Atlantic contribute on the 2-5 day time-scale. The large-scale moist dynamics appears therefore to be one important factor enabling a moderate Mediterranean cyclone to produce heavy precipitation. Finally, local evaporation from the Mediterranean, water-vapor recycling, and orographically-induced low-level convergence enhance and concentrate the moisture over the area where heavy precipitation occurs. This happens on a 12-72 hour time-scale.

Effects of Increased Horizontal Resolution on Simulation of the North American Monsoon in the NCAR CAM3: An Evaluation based on Surface, Satellite, and Reanalysis Data

NASA Astrophysics Data System (ADS)

Collier, J. C.; Zhang, G. J.

2006-05-01

Simulation of the North American monsoon system by the National Center for Atmospheric Research (NCAR) Community Atmosphere Model (CAM3) is evaluated in its sensitivity to increasing horizontal resolution. For two resolutions, T42 and T85, rainfall is compared to TRMM satellite-derived and surface gauge-based rainfall rates over the U.S. and northern Mexico as well as rainfall accumulations in gauges of the North American Monsoon Experiment (NAME) Enhanced Rain Gauge Network (NERN) in the Sierra Madre Occidental mountains. Simulated upper-tropospheric mass and wind fields are compared to those from NCEP-NCAR reanalyses. The comparison presented herein demonstrates that tropospheric motions associated with the North American monsoon system are sensitive to increasing the horizontal resolution of the model. An increase in resolution from T42 to T85 results in changes to a region of large-scale mid-tropospheric descent found north and east of the monsoon anticyclone. Relative to its simulation at T42, this region extends farther south and west at T85. Additionally, at T85, the subsidence is stronger. Consistent with the differences in large-scale descent, the T85 simulation of CAM3 is anomalously dry over Texas and northeastern Mexico during the peak monsoon months. Meanwhile, the geographic distribution of rainfall over the Sierra Madre Occidental region of Mexico is more satisfactorily simulated at T85 than at T42 for July and August. Moisture import into this region is greater at T85 than at T42 during these months. A focused study of the Sierra Madre Occidental region in particular shows that, in the regional average sense, the timing of the peak of the monsoon is relatively insensitive to the horizontal resolution of the model, while a phase bias in the diurnal cycle of monsoon-season precipitation is somewhat reduced in the higher-resolution run. At both resolutions, CAM3 poorly simulates the month-to-month evolution of monsoon rainfall over extreme northwestern Mexico and Arizona, though biases are considerably improved at T85.

A Quantitative Analysis of the Effects of Human Activities and Climate Change on Rainfall-Runoff in Xiaoqing River Basin

NASA Astrophysics Data System (ADS)

Yang, Y.; Cao, S.; Liu, C.; Liu, Y.

2017-12-01

It is a hot topic to study the effects of human activities on the rainfall-runoff relationship and quantitatively analyze the influencing factors. According to the flexibility of Copula function to capture multivariate interdependent structure, the Copula structure between rainfall and runoff was analyzed by using the rainfall-runoff variation test method based on Archimedean Copula function to diagnose the variation of rainfall-runoff relationship. The correlation of rainfall-runoff relationship could be directly analyzed by Copula function, which could intuitively display the change of runoff in the same rainfall before and after the mutation period. The statistical method was used to simulate the underlying surface conditions before the abrupt point, and the effects of climate change and human activities on runoff changes were calculated. It can finally figure out the effects of human activities on the rainfall-runoff relationship. Taking xiaoqing river for example, the results showed that the rainfall-runoff relationship in the Xiaoqing River Basin variated in 1996 mainly due to the continuous increase of water consumption in the watershed and the change of the runoff attenuation caused by the large-scale water conservancy projects. And interannual or annual change of rainfall was not obvious; compared with the year before the variation , the runoff capacity of the basin was weakened under the same rainfall conditions after the variation ; Rainfall and runoff distribution were significantly changed and the same magnitude of rainfall and probability of runoff change were significantly different in different periods; The statistical method was used to simulate the runoff from 1996 to 2016. Compared with that from 1960 to 1995, the result showed that the contribution rate of human activities to runoff reduction was 46.8% and that of climate change was 53.2%. By relevant reference, rainfall-runoff correlation and analysis of human activities, the result was verified to be reasonable. The study can be applied to other watersheds, or used to diagnose the variation of the relationship between meteorological elements and hydrological elements so as to provide scientific basis for rational exploitation and utilization of river water resources, as well as soil and water conservation.

Using integrated modeling for generating watershed-scale dynamic flood maps for Hurricane Harvey

NASA Astrophysics Data System (ADS)

Saksena, S.; Dey, S.; Merwade, V.; Singhofen, P. J.

2017-12-01

Hurricane Harvey, which was categorized as a 1000-year return period event, produced unprecedented rainfall and flooding in Houston. Although the expected rainfall was forecasted much before the event, there was no way to identify which regions were at higher risk of flooding, the magnitude of flooding, and when the impacts of rainfall would be highest. The inability to predict the location, duration, and depth of flooding created uncertainty over evacuation planning and preparation. This catastrophic event highlighted that the conventional approach to managing flood risk using 100-year static flood inundation maps is inadequate because of its inability to predict flood duration and extents for 500-year or 1000-year return period events in real-time. The purpose of this study is to create models that can dynamically predict the impacts of rainfall and subsequent flooding, so that necessary evacuation and rescue efforts can be planned in advance. This study uses a 2D integrated surface water-groundwater model called ICPR (Interconnected Channel and Pond Routing) to simulate both the hydrology and hydrodynamics for Hurricane Harvey. The methodology involves using the NHD stream network to create a 2D model that incorporates rainfall, land use, vadose zone properties and topography to estimate streamflow and generate dynamic flood depths and extents. The results show that dynamic flood mapping captures the flood hydrodynamics more accurately and is able to predict the magnitude, extent and time of occurrence for extreme events such as Hurricane Harvey. Therefore, integrated modeling has the potential to identify regions that are more susceptible to flooding, which is especially useful for large-scale planning and allocation of resources for protection against future flood risk.

State of the Art in Large-Scale Soil Moisture Monitoring

NASA Technical Reports Server (NTRS)

Ochsner, Tyson E.; Cosh, Michael Harold; Cuenca, Richard H.; Dorigo, Wouter; Draper, Clara S.; Hagimoto, Yutaka; Kerr, Yan H.; Larson, Kristine M.; Njoku, Eni Gerald; Small, Eric E.;

Discharge prediction in the Upper Senegal River using remote sensing data

NASA Astrophysics Data System (ADS)

Ceccarini, Iacopo; Raso, Luciano; Steele-Dunne, Susan; Hrachowitz, Markus; Nijzink, Remko; Bodian, Ansoumana; Claps, Pierluigi

2017-04-01

The Upper Senegal River, West Africa, is a poorly gauged basin. Nevertheless, discharge predictions are required in this river for the optimal operation of the downstream Manantali reservoir, flood forecasting, development plans for the entire basin and studies for adaptation to climate change. Despite the need for reliable discharge predictions, currently available rainfall-runoff models for this basin provide only poor performances, particularly during extreme regimes, both low-flow and high-flow. In this research we develop a rainfall-runoff model that combines remote-sensing input data and a-priori knowledge on catchment physical characteristics. This semi-distributed model, is based on conceptual numerical descriptions of hydrological processes at the catchment scale. Because of the lack of reliable input data from ground observations, we use the Tropical Rainfall Measuring Mission (TRMM) remote-sensing data for precipitation and the Global Land Evaporation Amsterdam Model (GLEAM) for the terrestrial potential evaporation. The model parameters are selected by a combination of calibration, by match of observed output and considering a large set of hydrological signatures, as well as a-priori knowledge on the catchment. The Generalized Likelihood Uncertainty Estimation (GLUE) method was used to choose the most likely range in which the parameter sets belong. Analysis of different experiments enhances our understanding on the added value of distributed remote-sensing data and a-priori information in rainfall-runoff modelling. Results of this research will be used for decision making at different scales, contributing to a rational use of water resources in this river.

Scale effect challenges in urban hydrology highlighted with a Fully Distributed Model and High-resolution rainfall data

NASA Astrophysics Data System (ADS)

Ichiba, Abdellah; Gires, Auguste; Tchiguirinskaia, Ioulia; Schertzer, Daniel; Bompard, Philippe; Ten Veldhuis, Marie-Claire

2017-04-01

Nowadays, there is a growing interest on small-scale rainfall information, provided by weather radars, to be used in urban water management and decision-making. Therefore, an increasing interest is in parallel devoted to the development of fully distributed and grid-based models following the increase of computation capabilities, the availability of high-resolution GIS information needed for such models implementation. However, the choice of an appropriate implementation scale to integrate the catchment heterogeneity and the whole measured rainfall variability provided by High-resolution radar technologies still issues. This work proposes a two steps investigation of scale effects in urban hydrology and its effects on modeling works. In the first step fractal tools are used to highlight the scale dependency observed within distributed data used to describe the catchment heterogeneity, both the structure of the sewer network and the distribution of impervious areas are analyzed. Then an intensive multi-scale modeling work is carried out to understand scaling effects on hydrological model performance. Investigations were conducted using a fully distributed and physically based model, Multi-Hydro, developed at Ecole des Ponts ParisTech. The model was implemented at 17 spatial resolutions ranging from 100 m to 5 m and modeling investigations were performed using both rain gauge rainfall information as well as high resolution X band radar data in order to assess the sensitivity of the model to small scale rainfall variability. Results coming out from this work demonstrate scale effect challenges in urban hydrology modeling. In fact, fractal concept highlights the scale dependency observed within distributed data used to implement hydrological models. Patterns of geophysical data change when we change the observation pixel size. The multi-scale modeling investigation performed with Multi-Hydro model at 17 spatial resolutions confirms scaling effect on hydrological model performance. Results were analyzed at three ranges of scales identified in the fractal analysis and confirmed in the modeling work. The sensitivity of the model to small-scale rainfall variability was discussed as well.

Remote Sensing Contributions to Prediction and Risk Assessment of Natural Diasters Caused by Large Scale Rift Valley fever Outbreaks

USDA-ARS?s Scientific Manuscript database

Remotely sensed vegetation measurements for the last 30 years combined with other climate data sets such as rainfall and sea surface temperatures have come to play an important role in the study of the ecology of vector-borne diseases. We show that episodic outbreaks of Rift Valley fever are influen...

Can the Southern annular mode influence the Korean summer monsoon rainfall?

NASA Astrophysics Data System (ADS)

Prabhu, Amita; Kripalani, Ramesh; Oh, Jaiho; Preethi, Bhaskar

2017-05-01

We demonstrate that a large-scale longitudinally symmetric global phenomenon in the Southern Hemisphere sub-polar region can transmit its influence over a remote local region of the Northern Hemisphere traveling more than 100° of latitudes (from 70°S to 40°N). This is illustrated by examining the relationship between the Southern Annular Mode (SAM) and the Korean Monsoon Rainfall (KMR) based on the data period 1983-2013. Results reveal that the May-June SAM (MJSAM) has a significant in-phase relationship with the subsequent KMR. A positive MJSAM is favorable for the summer monsoon rainfall over the Korean peninsula. The impact is relayed through the central Pacific Ocean. When a negative phase of MJSAM occurs, it gives rise to an anomalous meridional circulation in a longitudinally locked air-sea coupled system over the central Pacific that propagates from sub-polar to equatorial latitudes and is associated with the central Pacific warming. The ascending motion over the central Pacific descends over the Korean peninsula during peak-boreal summer resulting in weakening of monsoon rainfall. The opposite features prevail during a positive phase of SAM. Thus, the extreme modes of MJSAM could possibly serve as a predictor for ensuing Korean summer monsoon rainfall.

Rainfall seasonality on the Indian subcontinent during the Cretaceous greenhouse.

PubMed

Ghosh, Prosenjit; Prasanna, K; Banerjee, Yogaraj; Williams, Ian S; Gagan, Michael K; Chaudhuri, Atanu; Suwas, Satyam

2018-05-31

The Cretaceous greenhouse climate was accompanied by major changes in Earth's hydrological cycle, but seasonally resolved hydroclimatic reconstructions for this anomalously warm period are rare. We measured the δ 18 O and CO 2 clumped isotope Δ 47 of the seasonal growth bands in carbonate shells of the mollusc Villorita cyprinoides (Black Clam) growing in the Cochin estuary, in southern India. These tandem records accurately reconstruct seasonal changes in sea surface temperature (SST) and seawater δ 18 O, allowing us to document freshwater discharge into the estuary, and make inferences about rainfall amount. The same analytical approach was applied to well-preserved fossil remains of the Cretaceous (Early Maastrichtian) mollusc Phygraea (Phygraea) vesicularis from the nearby Kallankuruchchi Formation in the Cauvery Basin of southern India. The palaeoenvironmental record shows that, unlike present-day India, where summer rainfall predominates, most rainfall in Cretaceous India occurred in winter. During the Early Maastrichtian, the Indian plate was positioned at ~30°S latitude, where present-day rainfall and storm activity is also concentrated in winter. The good match of the Cretaceous climate and present-day climate at ~30°S suggests that the large-scale atmospheric circulation and seasonal hydroclimate patterns were similar to, although probably more intense than, those at present.

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

NASA Astrophysics Data System (ADS)

Selvam, A. M.

2014-06-01

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

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

Tao, Wei-Kuo; Takayabu, Yukari N.; Lang, Steve

Yanai et al. (1973) utilized the meteorological data collected from a sounding network to present a pioneering work on thermodynamic budgets, which are referred to as the apparent heat source (Q1) and apparent moisture sink (Q2). Latent heating (LH) is one of the most dominant terms in Q1. Yanai’s paper motivated the development of satellite-based LH algorithms and provided a theoretical background for imposing large-scale advective forcing into cloud-resolving models (CRMs). These CRM-simulated LH and Q1 data have been used to generate the look-up tables in Tropical Rainfall Measuring Mission (TRMM) LH algorithms. A set of algorithms developed for retrievingmore » LH profiles from TRMM-based rainfall profiles are described and evaluated, including details concerning their intrinsic space-time resolutions. Included in the paper are results from a variety of validation analyses that define the uncertainty of the LH profile estimates. Also, examples of how TRMM-retrieved LH profiles have been used to understand the lifecycle of the MJO and improve the predictions of global weather and climate models as well as comparisons with large-scale analyses are provided. Areas for further improvement of the TRMM products are discussed.« less

The spatial return level of aggregated hourly extreme rainfall in Peninsular Malaysia

NASA Astrophysics Data System (ADS)

Shaffie, Mardhiyyah; Eli, Annazirin; Wan Zin, Wan Zawiah; Jemain, Abdul Aziz

2015-07-01

This paper is intended to ascertain the spatial pattern of extreme rainfall distribution in Peninsular Malaysia at several short time intervals, i.e., on hourly basis. Motivation of this research is due to historical records of extreme rainfall in Peninsular Malaysia, whereby many hydrological disasters at this region occur within a short time period. The hourly periods considered are 1, 2, 3, 6, 12, and 24 h. Many previous hydrological studies dealt with daily rainfall data; thus, this study enables comparison to be made on the estimated performances between daily and hourly rainfall data analyses so as to identify the impact of extreme rainfall at a shorter time scale. Return levels based on the time aggregate considered are also computed. Parameter estimation using L-moment method for four probability distributions, namely, the generalized extreme value (GEV), generalized logistic (GLO), generalized Pareto (GPA), and Pearson type III (PE3) distributions were conducted. Aided with the L-moment diagram test and mean square error (MSE) test, GLO was found to be the most appropriate distribution to represent the extreme rainfall data. At most time intervals (10, 50, and 100 years), the spatial patterns revealed that the rainfall distribution across the peninsula differ for 1- and 24-h extreme rainfalls. The outcomes of this study would provide additional information regarding patterns of extreme rainfall in Malaysia which may not be detected when considering only a higher time scale such as daily; thus, appropriate measures for shorter time scales of extreme rainfall can be planned. The implementation of such measures would be beneficial to the authorities to reduce the impact of any disastrous natural event.

Relations between rainfall–runoff-induced erosion and aeolian deposition at archaeological sites in a semi-arid dam-controlled river corridor

USGS Publications Warehouse

Collins, Brian D.; Bedford, David; Corbett, Skye C.; Fairley, Helen C.; Cronkite-Ratcliff, Collin

2016-01-01

Process dynamics in fluvial-based dryland environments are highly complex with fluvial, aeolian, and alluvial processes all contributing to landscape change. When anthropogenic activities such as dam-building affect fluvial processes, the complexity in local response can be further increased by flood- and sediment-limiting flows. Understanding these complexities is key to predicting landscape behavior in drylands and has important scientific and management implications, including for studies related to paleoclimatology, landscape ecology evolution, and archaeological site context and preservation. Here we use multi-temporal LiDAR surveys, local weather data, and geomorphological observations to identify trends in site change throughout the 446-km-long semi-arid Colorado River corridor in Grand Canyon, Arizona, USA, where archaeological site degradation related to the effects of upstream dam operation is a concern. Using several site case studies, we show the range of landscape responses that might be expected from concomitant occurrence of dam-controlled fluvial sand bar deposition, aeolian sand transport, and rainfall-induced erosion. Empirical rainfall-erosion threshold analyses coupled with a numerical rainfall–runoff–soil erosion model indicate that infiltration-excess overland flow and gullying govern large-scale (centimeter- to decimeter-scale) landscape changes, but that aeolian deposition can in some cases mitigate gully erosion. Whereas threshold analyses identify the normalized rainfall intensity (defined as the ratio of rainfall intensity to hydraulic conductivity) as the primary factor governing hydrologic-driven erosion, assessment of false positives and false negatives in the dataset highlight topographic slope as the next most important parameter governing site response. Analysis of 4+ years of high resolution (four-minute) weather data and 75+ years of low resolution (daily) climate records indicates that dryland erosion is dependent on short-term, storm-driven rainfall intensity rather than cumulative rainfall, and that erosion can occur outside of wet seasons and even wet years. These results can apply to other similar semi-arid landscapes where process complexity may not be fully understood.

Prediction of spatially explicit rainfall intensity-duration thresholds for post-fire debris-flow generation in the western United States

NASA Astrophysics Data System (ADS)

Staley, Dennis; Negri, Jacquelyn; Kean, Jason

2016-04-01

Population expansion into fire-prone steeplands has resulted in an increase in post-fire debris-flow risk in the western United States. Logistic regression methods for determining debris-flow likelihood and the calculation of empirical rainfall intensity-duration thresholds for debris-flow initiation represent two common approaches for characterizing hazard and reducing risk. Logistic regression models are currently being used to rapidly assess debris-flow hazard in response to design storms of known intensities (e.g. a 10-year recurrence interval rainstorm). Empirical rainfall intensity-duration thresholds comprise a major component of the United States Geological Survey (USGS) and the National Weather Service (NWS) debris-flow early warning system at a regional scale in southern California. However, these two modeling approaches remain independent, with each approach having limitations that do not allow for synergistic local-scale (e.g. drainage-basin scale) characterization of debris-flow hazard during intense rainfall. The current logistic regression equations consider rainfall a unique independent variable, which prevents the direct calculation of the relation between rainfall intensity and debris-flow likelihood. Regional (e.g. mountain range or physiographic province scale) rainfall intensity-duration thresholds fail to provide insight into the basin-scale variability of post-fire debris-flow hazard and require an extensive database of historical debris-flow occurrence and rainfall characteristics. Here, we present a new approach that combines traditional logistic regression and intensity-duration threshold methodologies. This method allows for local characterization of both the likelihood that a debris-flow will occur at a given rainfall intensity, the direct calculation of the rainfall rates that will result in a given likelihood, and the ability to calculate spatially explicit rainfall intensity-duration thresholds for debris-flow generation in recently burned areas. Our approach synthesizes the two methods by incorporating measured rainfall intensity into each model variable (based on measures of topographic steepness, burn severity and surface properties) within the logistic regression equation. This approach provides a more realistic representation of the relation between rainfall intensity and debris-flow likelihood, as likelihood values asymptotically approach zero when rainfall intensity approaches 0 mm/h, and increase with more intense rainfall. Model performance was evaluated by comparing predictions to several existing regional thresholds. The model, based upon training data collected in southern California, USA, has proven to accurately predict rainfall intensity-duration thresholds for other areas in the western United States not included in the original training dataset. In addition, the improved logistic regression model shows promise for emergency planning purposes and real-time, site-specific early warning. With further validation, this model may permit the prediction of spatially-explicit intensity-duration thresholds for debris-flow generation in areas where empirically derived regional thresholds do not exist. This improvement would permit the expansion of the early-warning system into other regions susceptible to post-fire debris flow.

SUBPIXEL-SCALE RAINFALL VARIABILITY AND THE EFFECTS ON SEPARATION OF RADAR AND GAUGE RAINFALL ERRORS

EPA Science Inventory

One of the primary sources of the discrepancies between radar-based rainfall estimates and rain gauge measurements is the point-area difference, i.e., the intrinsic difference in the spatial dimensions of the rainfall fields that the respective data sets are meant to represent. ...

Impact of Synoptic-Scale Factors on Rainfall Forecast in Different Stages of a Persistent Heavy Rainfall Event in South China

NASA Astrophysics Data System (ADS)

Zhang, Murong; Meng, Zhiyong

2018-04-01

This study investigates the stage-dependent rainfall forecast skills and the associated synoptic-scale features in a persistent heavy rainfall event in south China, Guangdong Province, during 29-31 March 2014, using operational global ensemble forecasts from the European Centre for Medium-Range Weather Forecasts. This persistent rainfall was divided into two stages with a better precipitation forecast skill in Stage 2 (S2) than Stage 1 (S1) although S2 had a longer lead time. Using ensemble-based sensitivity analysis, key synoptic-scale factors that affected the rainfall were diagnosed by correlating the accumulated precipitation of each stage to atmospheric state variables in the middle of respective stage. The precipitation in both stages was found to be significantly correlated with midlevel trough, low-level vortex, and particularly the low-level jet on the southeast flank of the vortex and its associated moisture transport. The rainfall forecast skill was mainly determined by the forecast accuracy in the location of the low-level jet, which was possibly related to the different juxtapositions between the direction of the movement of the low-level vortex and the orientation of the low-level jet. The uncertainty in rainfall forecast in S1 was mainly from the location uncertainty of the low-level jet, while the uncertainty in rainfall forecast in S2 was mainly from the width uncertainty of the low-level jet with the relatively accurate location of the low-level jet.

Distant Influence of Kuroshio Eddies on North Pacific Weather Patterns?

PubMed Central

Ma, Xiaohui; Chang, Ping; Saravanan, R.; Montuoro, Raffaele; Hsieh, Jen-Shan; Wu, Dexing; Lin, Xiaopei; Wu, Lixin; Jing, Zhao

2015-01-01

High-resolution satellite measurements of surface winds and sea-surface temperature (SST) reveal strong coupling between meso-scale ocean eddies and near-surface atmospheric flow over eddy-rich oceanic regions, such as the Kuroshio and Gulf Stream, highlighting the importance of meso-scale oceanic features in forcing the atmospheric planetary boundary layer (PBL). Here, we present high-resolution regional climate modeling results, supported by observational analyses, demonstrating that meso-scale SST variability, largely confined in the Kuroshio-Oyashio confluence region (KOCR), can further exert a significant distant influence on winter rainfall variability along the U.S. Northern Pacific coast. The presence of meso-scale SST anomalies enhances the diabatic conversion of latent heat energy to transient eddy energy, intensifying winter cyclogenesis via moist baroclinic instability, which in turn leads to an equivalent barotropic downstream anticyclone anomaly with reduced rainfall. The finding points to the potential of improving forecasts of extratropical winter cyclones and storm systems and projections of their response to future climate change, which are known to have major social and economic impacts, by improving the representation of ocean eddy–atmosphere interaction in forecast and climate models. PMID:26635077

Design of a reliable and operational landslide early warning system at regional scale

NASA Astrophysics Data System (ADS)

Calvello, Michele; Piciullo, Luca; Gariano, Stefano Luigi; Melillo, Massimo; Brunetti, Maria Teresa; Peruccacci, Silvia; Guzzetti, Fausto

2017-04-01

Landslide early warning systems at regional scale are used to warn authorities, civil protection personnel and the population about the occurrence of rainfall-induced landslides over wide areas, typically through the prediction and measurement of meteorological variables. A warning model for these systems must include a regional correlation law and a decision algorithm. A regional correlation law can be defined as a functional relationship between rainfall and landslides; it is typically based on thresholds of rainfall indicators (e.g., cumulated rainfall, rainfall duration) related to different exceedance probabilities of landslide occurrence. A decision algorithm can be defined as a set of assumptions and procedures linking rainfall thresholds to warning levels. The design and the employment of an operational and reliable early warning system for rainfall-induced landslides at regional scale depend on the identification of a reliable correlation law as well as on the definition of a suitable decision algorithm. Herein, a five-step process chain addressing both issues and based on rainfall thresholds is proposed; the procedure is tested in a landslide-prone area of the Campania region in southern Italy. To this purpose, a database of 96 shallow landslides triggered by rainfall in the period 2003-2010 and rainfall data gathered from 58 rain gauges are used. First, a set of rainfall thresholds are defined applying a frequentist method to reconstructed rainfall conditions triggering landslides in the test area. In the second step, several thresholds at different exceedance probabilities are evaluated, and different percentile combinations are selected for the activation of three warning levels. Subsequently, within steps three and four, the issuing of warning levels is based on the comparison, over time and for each combination, between the measured rainfall and the pre-defined warning level thresholds. Finally, the optimal percentile combination to be employed in the regional early warning system is selected evaluating the model performance in terms of success and error indicators by means of the "event, duration matrix, performance" (EDuMaP) method.

Understanding green roof spatial dynamics: results from a scale based hydrologic study and introduction of a low-cost method for wide-range monitoring

NASA Astrophysics Data System (ADS)

Hakimdavar, Raha; Culligan, Patricia J.; Guido, Aida

2014-05-01

Green roofs have the potential, if implemented on a wide scale and with proper foresight, to become an important supplement to traditional urban water management infrastructure, while also helping to change the face of cities from concrete draped, highly modified environments, to hybrid places where nature is more closely integrated into designs rather than pushed out of them. The ability of these systems to act as a decentralized rainwater handling network has been the topic of many recent studies. While these studies have attempted to quantify the hydrologic performance of green roofs, it's clear that they are dynamic systems whose responses are difficult to generalize. What also seems to be lacking from many studies is a discussion on the effects of green roof scale, spatial planning and configuration. This research aims to understand how rainfall characteristics and green roof scale impact its hydrologic performance. Three extensive green roof systems in New York City, with the same engineered components, age and regional climatic conditions, but different drainage areas, are analyzed. We find that rainfall volume and event duration are two of the parameters that most affect green roof performance, while rainfall intensity and antecedent dry weather period are less significant. We also find that green roof scale does in fact affect hydrologic performance, but mainly in reducing runoff peaks, with rainfall retention and lag time being much less affected by drainage area. We also introduce a low-cost monitoring method, termed the Soil Water Apportioning (SWA) method, which uses a water balance approach to analytically link precipitation to substrate moisture, and enable inference of green runoff and evapotranspiration from information on substrate moisture changes over time. Twelve months of in situ rainfall and soil moisture observations from three different green roof systems - extensive vegetated mat, semi-intensive vegetated mat, and semi-intensive tray - are used to test the reliability of the proposed approach using two different low-cost soil moisture probes. The estimates of runoff are compared with observed runoff data for durations ranging between 6 months to 1 year. Preliminary results indicate that this can be an effective low-cost and low-maintenance alternative to the custom made weir and lysimeter systems frequently used to quantify runoff during green roof studies. By significantly reducing the cost and labor associated with typical monitoring efforts, the SWA method makes large scale studies of green roof hydrologic performance more feasible.

Hydrological performance of extensive green roofs in New York City: observations and multi-year modeling of three full-scale systems

NASA Astrophysics Data System (ADS)

Carson, T. B.; Marasco, D. E.; Culligan, P. J.; McGillis, W. R.

2013-06-01

Green roofs can be an attractive strategy for adding perviousness in dense urban environments where rooftops are a high fraction of the impervious land area. As a result, green roofs are being increasingly implemented as part of urban stormwater management plans in cities around the world. In this study, three full-scale green roofs in New York City (NYC) were monitored, representing the three extensive green roof types most commonly constructed: (1) a vegetated mat system installed on a Columbia University residential building, referred to as W118; (2) a built-in-place system installed on the United States Postal Service (USPS) Morgan general mail facility; and (3) a modular tray system installed on the ConEdison (ConEd) Learning Center. Continuous rainfall and runoff data were collected from each green roof between June 2011 and June 2012, resulting in 243 storm events suitable for analysis ranging from 0.25 to 180 mm in depth. Over the monitoring period the W118, USPS, and ConEd roofs retained 36%, 47%, and 61% of the total rainfall respectively. Rainfall attenuation of individual storm events ranged from 3 to 100% for W118, 9 to 100% for USPS, and 20 to 100% for ConEd, where, generally, as total rainfall increased the per cent of rainfall attenuation decreased. Seasonal retention behavior also displayed event size dependence. For events of 10-40 mm rainfall depth, median retention was highest in the summer and lowest in the winter, whereas median retention for events of 0-10 mm and 40 +mm rainfall depth did not conform to this expectation. Given the significant influence of event size on attenuation, the total per cent retention during a given monitoring period might not be indicative of annual rooftop retention if the distribution of observed event sizes varies from characteristic annual rainfall. To account for this, the 12 months of monitoring data were used to develop a characteristic runoff equation (CRE), relating runoff depth and event size, for each green roof. When applied to Central Park, NYC precipitation records from 1971 to 2010, the CRE models estimated total rainfall retention over the 40 year period to be 45%, 53%, and 58% for the W118, USPS, and ConEd green roofs respectively. Differences between the observed and modeled rainfall retention for W118 and USPS were primarily due to an abnormally high frequency of large events, 50 mm of rainfall or more, during the monitoring period compared to historic precipitation patterns. The multi-year retention rates are a more reliable estimate of annual rainfall capture and highlight the importance of long-term evaluations when reporting green roof performance.

Comparison of different types of medium scale field rainfall simulators

NASA Astrophysics Data System (ADS)

Dostál, Tomáš; Strauss, Peter; Schindewolf, Marcus; Kavka, Petr; Schmidt, Jürgen; Bauer, Miroslav; Neumann, Martin; Kaiser, Andreas; Iserloh, Thomas

2015-04-01

Rainfall simulators are used in numerous experiments to study runoff and soil erosion characteristics. However, they usually differ in their construction details, rainfall generation, plot size and other technical parameters. As field experiments using medium to large scale rainfall simulators (plot length 3 - 8 m) are very much time and labor consuming, close cooperation of individual teams and comparability of results is highly desirable to enlarge the database of results. Two experimental campaigns were organized to compare three field rainfall simulators of similar scale (plot size), but with different technical parameters. The results were then compared, to identify parameters that are crucial for soil loss and surface runoff formation and test if results from individual devices can be reliably compared. The rainfall simulators compared were: field rainfall simulator of CTU Prague (the Czech Republic) (Kavka et al., 2012; EGU2015-11025), field simulator of BAW (Austria) (Strauss et al., 2002) and field simulator of TU Bergakademie Freiberg (Germany) (Schindewolf & Schmidt 2012). The device of CTU Prague is usually applied to a plot size of 9,5 x 2 m employing 4 nozzles SS Full Jet 40WSQ mounted on folding arm, working pressure is 0.8 bar, height of nozzles is 2.65 m. The intensity of rainfall is regulated electronically, which leaves the nozzle opened only for certain time. The rainfall simulator of BAW is constructed as a modular system, which is usually applied for a length of 5 m (area 2 x 5 m), using 6 nozzles SS Full Jet 40WSQ. Usual working pressure is 0.25 bar. Elevation of nozzles is 2.6 m. The intensity of rainfall is regulated electronically, which leaves the nozzle opened only for certain time. The device of TU Bergakademie Freiberg is also standard modular system, working usually with a plot size of 3 x 1 m, using 3 oscillating VeeJet 80/100 nozzles with an usual operating pressure of 0.5 bar. Intensity is regulated by the frequency of sweeps above the experimental plot. Comparison was done during two independent campaigns, where always two devices were present. Rainfall intensity for the experiments varied between 40 to 60 mm/h. Mutual comparison was carried out between the CTU Prague and TU Freiberg RSs at plot size of 3 x 1 m and Between CTU Prague and BAW RSs at plot size of 5 x 2 m. In general, the experiments revealed a significant effect of potential heterogeneities at the experimental plots and an effect of raindrop energy on both surface runoff formation and mainly soil loss. Therefore, coordination of methodology of the experiments and careful control of initial conditions seem to be a crucial point for comparability of results from individual devices. Detailed results will be presented on the poster. The research has been supported by the research grants SGS14/180/OHK1/3T/11, QJ1230056 and 7AMB14AT020. References Kavka, P., Davidová, T., Janotová, B., Bauer, M. a Dostál, T. 2012. Mobilní dešťový simulátor.(in Czech), Stavební obzor. 8, 2012. Schindewolf, M. & J. Schmidt (2012): Parameterization of the EROSION 2D/3D soil erosion model using a small-scale rainfall simulator and upstream runoff simulation, Catena 91, pp. 47-55, DOI: 10.1016/j.catena.2011.01.007 Strauss P., J.Pitty, M.Pfeffer, A. Mentler (2000): Rainfall Simulation for Outdoor Experiments. In: P. Jamet, J. Cornejo(eds.): Current research methods to assess the environmental fate of pesticides. pp. 329-333, INRA Editions.

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

NASA Astrophysics Data System (ADS)

Nduwayezu, Emmanuel; Kanevski, Mikhail; Jaboyedoff, Michel

2013-04-01

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

Land-Climate Feedbacks in Indian Summer Monsoon Rainfall

NASA Astrophysics Data System (ADS)

Asharaf, Shakeel; Ahrens, Bodo

2016-04-01

In an attempt to identify how land surface states such as soil moisture influence the monsoonal precipitation climate over India, a series of numerical simulations including soil moisture sensitivity experiments was performed. The simulations were conducted with a nonhydrostatic regional climate model (RCM), the Consortium for Small-Scale Modeling (COSMO) in climate mode (CCLM) model, which was driven by the European Center for Medium-Range Weather Forecasts (ECMWF) Interim reanalysis (ERA-Interim) data. Results showed that pre-monsoonal soil moisture has a significant impact on monsoonal precipitation formation and large-scale atmospheric circulations. The analysis revealed that even a small change in the processes that influence precipitation via changes in local evapotranspiration was able to trigger significant variations in regional soil moisture-precipitation feedback. It was observed that these processes varied spatially from humid to arid regions in India, which further motivated an examination of soil-moisture memory variation over these regions and determination of the ISM seasonal forecasting potential. A quantitative analysis indicated that the simulated soil-moisture memory lengths increased with soil depth and were longer in the western region than those in the eastern region of India. Additionally, the subsequent precipitation variance explained by soil moisture increased from east to west. The ISM rainfall was further analyzed in two different greenhouse gas emission scenarios: the Special Report on Emissions Scenario (SRES: B1) and the new Representative Concentration Pathways (RCPs: RCP4.5). To that end, the CCLM and its driving global-coupled atmospheric-oceanic model (GCM), ECHAM/MPIOM were used in order to understand the driving processes of the projected inter-annual precipitation variability and associated trends. Results inferred that the projected rainfall changes were the result of two largely compensating processes: increase of remotely induced precipitation and decrease of precipitation efficiency. However, the complementing precipitation components and their simulation uncertainties rendered climate projections of the Indian summer monsoon rainfall as an ongoing, highly ambiguous challenge for both the GCM and the RCM.

Insights in nutrient sources and transport from high-frequency monitoring at the outlet pumping station of an agricultural lowland polder catchment

NASA Astrophysics Data System (ADS)

Rozemeijer, J.; Van der Grift, B.; Broers, H. P.; Berendrecht, W.; Oste, L.; Griffioen, J.

2015-12-01

In this study, we present new insights in nutrient sources and transport processes in an agricultural-dominated lowland water system based on high-frequency monitoring technology. Starting in October 2014, we have collected semi-continuous measurements of the TP and NO3 concentrations, conductivity and water temperature at a large scale pumping station at the outlet of a 576 km2 polder catchment. The semi-continuous measurements complement a water quality monitoring program at six locations within the drainage area based on conventional monthly or biweekly grab sampling. The NO3 and TP concentrations at the pumping station varied between 0.5 and 10 mgN/L and 0.1 and 0.5 mgP/L. The seasonal trends and short scale concentration dynamics clearly indicated that most of the NO3 loads at the pumping station originated from subsurface drain tubes that were active after intensive rainfall events during the winter months. A transfer function-noise model of hourly NO3 concentrations reveals that a large part of the dynamics in NO3 concentrations during the winter months can be predicted using rainfall data. In February however, NO3 concentrations were higher than predicted due to direct losses after the first manure application. The TP concentration almost doubled during operation of the pumping station. This highlights resuspension of particulate P from channel bed sediments induced by the higher flow velocities during pumping. Rainfall events that caused peaks in NO3 concentrations did not result in TP concentration peaks. Direct effects of run-off, with an association increase in the TP concentration and decrease of the NO3concentration, was only observed during rainfall event at the end of a freeze-thaw cycle. The high-frequency monitoring at the outlet of an agricultural-dominated lowland water system in combination with low-frequency monitoring within the area provided insight in nutrient sources and transport processes that are highly relevant for water quality management.

Variability of temperature sensitivity of extreme precipitation from a regional-to-local impact scale perspective

NASA Astrophysics Data System (ADS)

Schroeer, K.; Kirchengast, G.

2016-12-01

Relating precipitation intensity to temperature is a popular approach to assess potential changes of extreme events in a warming climate. Potential increases in extreme rainfall induced hazards, such as flash flooding, serve as motivation. It has not been addressed whether the temperature-precipitation scaling approach is meaningful on a regional to local level, where the risk of climate and weather impact is dealt with. Substantial variability of temperature sensitivity of extreme precipitation has been found that results from differing methodological assumptions as well as from varying climatological settings of the study domains. Two aspects are consistently found: First, temperature sensitivities beyond the expected consistency with the Clausius-Clapeyron (CC) equation are a feature of short-duration, convective, sub-daily to sub-hourly high-percentile rainfall intensities at mid-latitudes. Second, exponential growth ceases or reverts at threshold temperatures that vary from region to region, as moisture supply becomes limited. Analyses of pooled data, or of single or dispersed stations over large areas make it difficult to estimate the consequences in terms of local climate risk. In this study we test the meaningfulness of the scaling approach from an impact scale perspective. Temperature sensitivities are assessed using quantile regression on hourly and sub-hourly precipitation data from 189 stations in the Austrian south-eastern Alpine region. The observed scaling rates vary substantially, but distinct regional and seasonal patterns emerge. High sensitivity exceeding CC-scaling is seen on the 10-minute scale more than on the hourly scale, in storms shorter than 2 hours duration, and in shoulder seasons, but it is not necessarily a significant feature of the extremes. To be impact relevant, change rates need to be linked to absolute rainfall amounts. We show that high scaling rates occur in lower temperature conditions and thus have smaller effect on absolute precipitation intensities. While reporting of mere percentage numbers can be misleading, scaling studies can add value to process understanding on the local scale, if the factors that influence scaling rates are considered from both a methodological and a physical perspective.

Two types of flash drought over China and their connections with sub-seasonal to seasonal soil moisture drought

NASA Astrophysics Data System (ADS)

Wang, L.; Yuan, X.; Xie, Z.

2017-12-01

Flash drought has been receiving attention recently due to its rapid development and vast damage on crops in the growing season. Accompanied with heatwave and rainfall deficit, the soil moisture decreased rapidly in a short time and may lead to the failure of root water uptake and large-scale crops wither. There are two types of flash droughts according to the causes (Mo and Lettenmaier, 2016), i.e., heat wave flash drought and rainfall deficit flash drought. Here, based on pentad-mean surface air temperature and precipitation observations from over two thousand meteorological stations as well as soil moisture and ET estimations from three global reanalysis products, the characteristics and evolution of the two types of flash droughts over China are being explored. Heat wave flash drought is more likely to occur in humid and semi-humid areas, such as southern China, while rainfall deficit flash drought is more likely to occur in northern China. Unlike the traditional drought that persists for a few months to decades, the mean durations of both types of flash droughts are very short. We use monthly mean soil moisture to calculate sub-seasonal to seasonal (S2S) soil moisture drought, and compare its characteristics and preferred conditions such as the large-scale atmospheric circulation and oceanic anomaly for both types of flash droughts. The percentages of flash drought in different periods of S2S drought are also being explored to see the potential relationship between flash drought and S2S drought over different regions.

Rainfall extremes from TRMM data and the Metastatistical Extreme Value Distribution

NASA Astrophysics Data System (ADS)

Zorzetto, Enrico; Marani, Marco

2017-04-01

A reliable quantification of the probability of weather extremes occurrence is essential for designing resilient water infrastructures and hazard mitigation measures. However, it is increasingly clear that the presence of inter-annual climatic fluctuations determines a substantial long-term variability in the frequency of occurrence of extreme events. This circumstance questions the foundation of the traditional extreme value theory, hinged on stationary Poisson processes or on asymptotic assumptions to derive the Generalized Extreme Value (GEV) distribution. We illustrate here, with application to daily rainfall, a new approach to extreme value analysis, the Metastatistical Extreme Value Distribution (MEVD). The MEVD relaxes the above assumptions and is based on the whole distribution of daily rainfall events, thus allowing optimal use of all available observations. Using a global dataset of rain gauge observations, we show that the MEVD significantly outperforms the Generalized Extreme Value distribution, particularly for long average recurrence intervals and when small samples are available. The latter property suggests MEVD to be particularly suited for applications to satellite rainfall estimates, which only cover two decades, thus making extreme value estimation extremely challenging. Here we apply MEVD to the TRMM TMPA 3B42 product, an 18-year dataset of remotely-sensed daily rainfall providing a quasi-global coverage. Our analyses yield a global scale mapping of daily rainfall extremes and of their distributional tail properties, bridging the existing large gaps in ground-based networks. Finally, we illustrate how our global-scale analysis can provide insight into how properties of local rainfall regimes affect tail estimation uncertainty when using the GEV or MEVD approach. We find a dependence of the estimation uncertainty, for both the GEV- and MEV-based approaches, on the average annual number and on the inter-annual variability of rainy days. In particular, estimation uncertainty decreases 1) as the mean annual number of wet days increases, and 2) as the variability in the number of rainy days, expressed by its coefficient of variation, decreases. We tentatively explain this behavior in terms of the assumptions underlying the two approaches.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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.

Identification of MJO Signal on Various Elevation Station Rainfall in Southern Papua, Indonesia

NASA Astrophysics Data System (ADS)

Sakya, A. E.; Permana, D.; Makmur, E. E. S.; Handayani, A. S.; Hanggoro, W.; Setyadi, G.

2016-12-01

The Madden-Julian Oscillation (MJO) is the dominant mode of intraseasonal variability in tropical rainfall on the large scale, but its signal is often obscured in individual station data, where effects are most directly felt at the local level. The characteristic of the MJO during its propagation through the Maritime Continent has always been a challenge to comprehend despite decades of research attempts in that region. Unique topography over the Maritime Continent is believed to act as one of the vanguard of precipitation triggered by the MJO. Such condition leads to a maximize amplitude of the diurnal cycle of precipitation over land on phase 2 and 5, even before the arrival of the MJO. Papua in Indonesia is one of the wettest regions on Earth and is at the heart of the MJO envelope. Aiming to investigate the effect of topography and coastline distance on MJO in southern Papua, 14 years of rainfall data from 12 stations in PTFI AWS network at various elevations (9 meters to 4400 meters above sea level) have been utilized. The results show a strong MJO modulation in rainfall variability with variance of 30 - 100 days in the region. These results suggest a strong impact of MJO on rainfall at various elevations in southern Papua which confirm the previous studies. The peak rainfall rates were observed at phase 3 at lower elevation and coastline stations and phase 4 at middle and high elevation stations. The study also investigated the relationship between MJO phases and diurnal precipitation cycle at all stations. At low elevation and coastline stations, diurnal rainfall variation is more variable with high rainfall observed at afternoon to midnight and after midnight. This is due to the local effect of land-sea breeze system. While in middle and high elevation stations, rainfall peak was observed at afternoon to midnight. The results show the impact of MJO in diurnal rainfall variation at all stations.

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 characteristics and thresholds for periglacial debris flows in the Parlung Zangbo Basin, southeast Tibetan Plateau

NASA Astrophysics Data System (ADS)

Deng, Mingfeng; Chen, Ningsheng; Ding, Haitao

2018-02-01

The Parlung Zangbo Basin in the southeastern Tibet Plateau is affected by the summer monsoon from the Indian Ocean, which produces large rainfall gradients in the basin. Rainfall data during 2012-2015 from five new meteorological stations are used to analyse the rainfall characteristics. The daily rainfall, rainfall duration, mean rainfall intensity, and peak rainfall intensity are consistent, but sometimes contrasting. For example, these values decrease with increasing altitude, and the gradient is large downstream and small upstream, respectively. Moreover, the rainfall intensity peaks between 01:00 and 06:00 and increases during the afternoon. Based on the analysis of 14 debris flow cases in the basin, differences in the rainfall threshold differ depending on the location as sediment varieties. The sediment in the middle portions of the basin is wet and well structured; thus, long-duration, high-intensity rainfall is required to generate debris flows. Ravels in the upstream area are arid and not well structured, and short-duration rainfall is required to trigger debris flows. Between the above two locations, either long-duration, low-intensity rainfall or short-duration, high-intensity rainfall could provoke debris flows. Clearly, differences in rainfall characteristics and rainfall thresholds that are associated with the location must be considered in debris flow monitoring and warnings.

Precipitation Estimation from Remotely Sensed Information using Artificial Neural Network-Cloud Classification System

NASA Astrophysics Data System (ADS)

Hong, Yang

Precipitation estimation from satellite information (VISIBLE , IR, or microwave) is becoming increasingly imperative because of its high spatial/temporal resolution and board coverage unparalleled by ground-based data. After decades' efforts of rainfall estimation using IR imagery as basis, it has been explored and concluded that the limitations/uncertainty of the existing techniques are: (1) pixel-based local-scale feature extraction; (2) IR temperature threshold to define rain/no-rain clouds; (3) indirect relationship between rain rate and cloud-top temperature; (4) lumped techniques to model high variability of cloud-precipitation processes; (5) coarse scales of rainfall products. As continuing studies, a new version of Precipitation Estimation from Remotely Sensed Information using Artificial Neural Network (PERSIANN), called Cloud Classification System (CCS), has been developed to cope with these limitations in this dissertation. CCS includes three consecutive components: (1) a hybrid segmentation algorithm, namely Hierarchically Topographical Thresholding and Stepwise Seeded Region Growing (HTH-SSRG), to segment satellite IR images into separated cloud patches; (2) a 3D feature extraction procedure to retrieve both pixel-based local-scale and patch-based large-scale features of cloud patch at various heights; (3) an ANN model, Self-Organizing Nonlinear Output (SONO) network, to classify cloud patches into similarity-based clusters, using Self-Organizing Feature Map (SOFM), and then calibrate hundreds of multi-parameter nonlinear functions to identify the relationship between every cloud types and their underneath precipitation characteristics using Probability Matching Method and Multi-Start Downhill Simplex optimization techniques. The model was calibrated over the Southwest of United States (100°--130°W and 25°--45°N) first and then adaptively adjusted to the study region of North America Monsoon Experiment (65°--135°W and 10°--50°N) using observations from Geostationary Operational Environmental Satellite (GOES) IR imagery, Next Generation Radar (NEXRAD) rainfall network, and Tropical Rainfall Measurement Mission (TRMM) microwave rain rate estimates. CCS functions as a distributed model that first identifies cloud patches and then dispatches different but the best matching cloud-precipitation function for each cloud patch to estimate instantaneous rain rate at high spatial resolution (4km) and full temporal resolution of GOES IR images (every 30-minute). Evaluated over a range of spatial and temporal scales, the performance of CCS compared favorably with GOES Precipitation Index (GPI), Universal Adjusted GPI (UAGPI), PERSIANN, and Auto-Estimator (AE) algorithms, consistently. Particularly, the large number of nonlinear functions and optimum IR-rain rate thresholds of CCS model are highly variable, reflecting the complexity of dominant cloud-precipitation processes from cloud patch to cloud patch over various regions. As a result, CCS can more successfully capture variability in rain rate at small scales than existing algorithms and potentially provides rainfall product from GOES IR-NEXARD-TRMM TMI (SSM/I) at 0.12° x 0.12° and 3-hour resolution with relative low standard error (˜=3.0mm/hr) and high correlation coefficient (˜=0.65).

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

NASA Astrophysics Data System (ADS)

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

2015-04-01

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

The Tropical Rainfall Measuring Mission and Vern Suomi 's Vital Role

NASA Technical Reports Server (NTRS)

Simpson, Joanne; Kummerow, Christian

1999-01-01

The Tropical Rainfall Measuring Mission was a new concept of measuring rainfall over the global tropics using a combination of instruments, including the first weather radar to be flown in space. An important objective of the mission was to obtain profiles of latent heat in order to initialize large-scale circulation models and to understand the relationship between short-term climate changes in relation to rainfall variability. The idea originated in the early 1980's from scientists at the Goddard Space Flight Center/NASA who had been involved with attempts to measure rain with a passive microwave instrument on Nimbus 5 and had compared its results with rain falling in the area covered by the GATE1 radar ships. Using an imaginary satellite flying over the GATE ships, scientists showed that a satellite with an inclined orbit of 30-35 degrees could obtain monthly rainfalls with a sampling error of less than 10 percent over 5 degree by 5 degree areas. The Japanese proposed that they could build a nadir-scanning rain radar for the satellite. Vern Suomi was excited by this mission from the outset, since he recognized the great importance of adequate rainfall measurements over the tropical oceans. He was a charter member of the Science Steering Team and prepared a large part of the Report. While the mission attracted strong support in the science community, it was opposed by some of the high-level NASA management who feared its competition for funds with some much larger Earth Science satellites. Vern was able to overcome this opposition and to generate Congressional support, so that the Project finally got underway on both sides of the Pacific in 1991. The paper will discuss the design of the satellite, its data system and ground validation program. TP.NM was successfully launched in late 1997. Early results will be described. 1 GATE stands for GARP Atlantic Tropical Experiment and GARP stands for Global Atmospheric Research Program.

A Tibetan lake sediment record of Holocene Indian summer monsoon variability

NASA Astrophysics Data System (ADS)

Bird, Broxton W.; Polisar, Pratigya J.; Lei, Yanbin; Thompson, Lonnie G.; Yao, Tandong; Finney, Bruce P.; Bain, Daniel J.; Pompeani, David P.; Steinman, Byron A.

2014-08-01

Sedimentological data and hydrogen isotopic measurements of leaf wax long-chain n-alkanes (δDwax) from an alpine lake sediment archive on the southeastern Tibetan Plateau (Paru Co) provide a Holocene perspective of Indian summer monsoon (ISM) activity. The sedimentological data reflect variations in lake level and erosion related to local ISM rainfall over the Paru Co catchment, whereas δDwax reflects integrated, synoptic-scale ISM dynamics. Our results indicate that maximum ISM rainfall occurred between 10.1 and ˜5.2 ka, during which time there were five century-scale high and low lake stands. After 5.2 ka, the ISM trended toward drier conditions to the present, with the exception of a pluvial event centered at 0.9 ka. The Paru Co results share similarities with paleoclimate records from across the Tibetan Plateau, suggesting millennial-scale ISM dynamics were expressed coherently. These millennial variations largely track gradual decreases in orbital insolation, the southward migration of the Intertropical Convergence Zone (ITCZ), decreasing zonal Pacific sea surface temperature (SST) gradients and cooling surface air temperatures on the Tibetan Plateau. Centennial ISM and lake-level variability at Paru Co closely track reconstructed surface air temperatures on the Tibetan Plateau, but may also reflect Indian Ocean Dipole events, particularly during the early Holocene when ENSO variability was attenuated. Variations in the latitude of the ITCZ during the early and late Holocene also appear to have exerted an influence on centennial ISM rainfall.

Possible Influences of Air Pollution, Dust and Sandstorms on the Indian Monsoon

NASA Technical Reports Server (NTRS)

Lau, William K. M.; Kim, Kyu-Myong; Hsu, Christina N.; Holben, Brent N.

2010-01-01

In Asian monsoon countries, such as China and India, human health and safety problems caused by air pollution are becoming increasingly serious, due to the increased loading of atmospheric pollutants from waste gas emissions and from rising energy demand associated with the rapid pace of industrialization and modernization. Meanwhile, uneven distribution of monsoon rain associated with flash floods or prolonged drought, has caused major loss of human life and damage to crops and.property with devastating societal impacts. Historically, air-pollution and monsoons research are treated as separate problems. However recent studies have suggested that the two problems may be intrinsically linked and need to be studied jointly. Fundamentally, aerosols can affect precipitation through radiative effects cif suspended particles in the atmosphere (direct effect) and/or by interfering and changing: the cloud and precipitation formation processes (indirect effect). Based on their optical properties, aerosols can be classified into two types.: those that absorb solar radiation, and those that do not. Both types of aerosols scatter sunlight and reduce the amount of solar radiation from reaching the Earth's surface, causing it to cool. The surface cooling increases atmospheric stability and reduces convection potential, Absorbing aerosols, however, in addition to cooling the surface, can heat the atmosphere. The heating of the atmosphere may reduce the amount of low clouds by increased evaporation in cloud drops. The heating, however, may induce rising motion, enhance low-level moisture, convergence and, hence, increases rainfall, The latent heating from enhanced rainfall may excite feedback processes in the large-scale circulation, further amplify.the initial response to aerosol heating and producing more rain. Additionally, aerosols can increase the concentration of cloud condensation nuclei (CCN), increase cloud amount and decrease coalescence and collision rates, leading to reduced precipitation. However, in the presence of increasing moist and warm air, the reduced coalescence/collision may lead to supercooled drops at higher altitudes where ice precipitation falls and melts. The latent heat release from freezing aloft and melting below implies greater upward heat transport in polluted clouds and invigorate deep convection. In this way, aerosols may lead to increased local convection. Hence, depending on the ambient large-scale conditions and dynamical feedback processes, aerosols' effect on precipitation can be positive, negative or mixed. In the Asian monsoon and adjacent regions, the aerosol forcing and responses of the water cycle are even more complex, Both direct and indirect effects may take place locally and simultaneously, interacting with each other. in addition to local effects, monsoon rainfall may be affected by aerosols transported from other regions and intensified through large-scale circulation and moisture feedback. Thus, dust transported by the large-scale circulation from the adjacent deserts to northern India may affect rainfall over the Bay of Bengal; sulphate and black carbon front industrial pollution in central, southern China and northern India may affect the rainfall regime over the Korean peninsula and Japan; organic and black carbon front biomass burning from Indo-China may modulate the pre-monsoon rainfall regime over southern China and coastal regions, contributing to variability in differential heating and cooling of the atmosphere and to the land-sea thermal contrast. During the pre-monsoon season and monsoon breaks, it has been suggested that radiative forcing by absorbing aerosols have nearly the same order of magnitude as the forcing due to latent heating from convection and surface fluxes. The magnitude of the total aerosol radiative cooling due to sulphates and soot is of the order of 20-40 W/m2 over the Asian monsoon land region in the pre-monsoon season, compared to about 1-2 W/m2 for global warng. However, the combined forcing at the surface and in the atmosphere, including all species. if aerosols, and details of aerosol mixing, and impacts on the energy and water cycles in the monsoon land regions, are not well known.

Internally Generated and Externally Forced Multidecadal Oceanic Modes and their Influence on the Summer Rainfall over East Asia

NASA Astrophysics Data System (ADS)

Si, D.; Hu, A.

2017-12-01

The interdecadal oceanic variabilities can be generated from both internal and external processes, and these variabilities can significantly modulate our climate on global and regional scale, such as the warming slowdown in the early 21st century, and the rainfall in East Asia. By analyzing simulations from a unique Community Earth System Model (CESM) Large Ensemble (CESM_LE) project, we show that the Interdecadal Pacific Oscillation (IPO) is primarily an internally generated oceanic variability, while the Atlantic Multidecadal Oscillation (AMO) may be an oceanic variability generated by internal oceanic processes and modulated by external forcings in the 20th century. Although the observed relationship between IPO and the Yangtze-Huaihe River valley (YHRV) summer rainfall in China is well simulated in both the preindustrial control and 20th century ensemble, none of the 20th century ensemble members can reproduce the observed time evolution of both IPO and YHRV due to the unpredictable nature of IPO on multidecade timescale. On the other hand, although CESM_LE cannot reproduce the observed relationship between AMO and Huanghe River valley (HRV) summer rainfall of China in the preindustrial control simulation, this relationship in the 20th century simulations is well reproduced, and the chance to reproduce the observed time evolution of both AMO and HRV rainfall is about 30%, indicating the important role of the interaction between the internal processes and the external forcing to realistically simulate the AMO and HRV rainfall.

A Development of Nonstationary Regional Frequency Analysis Model with Large-scale Climate Information: Its Application to Korean Watershed

NASA Astrophysics Data System (ADS)

Kim, Jin-Young; Kwon, Hyun-Han; Kim, Hung-Soo

2015-04-01

The existing regional frequency analysis has disadvantages in that it is difficult to consider geographical characteristics in estimating areal rainfall. In this regard, this study aims to develop a hierarchical Bayesian model based nonstationary regional frequency analysis in that spatial patterns of the design rainfall with geographical information (e.g. latitude, longitude and altitude) are explicitly incorporated. This study assumes that the parameters of Gumbel (or GEV distribution) are a function of geographical characteristics within a general linear regression framework. Posterior distribution of the regression parameters are estimated by Bayesian Markov Chain Monte Carlo (MCMC) method, and the identified functional relationship is used to spatially interpolate the parameters of the distributions by using digital elevation models (DEM) as inputs. The proposed model is applied to derive design rainfalls over the entire Han-river watershed. It was found that the proposed Bayesian regional frequency analysis model showed similar results compared to L-moment based regional frequency analysis. In addition, the model showed an advantage in terms of quantifying uncertainty of the design rainfall and estimating the area rainfall considering geographical information. Finally, comprehensive discussion on design rainfall in the context of nonstationary will be presented. KEYWORDS: Regional frequency analysis, Nonstationary, Spatial information, Bayesian Acknowledgement This research was supported by a grant (14AWMP-B082564-01) from Advanced Water Management Research Program funded by Ministry of Land, Infrastructure and Transport of Korean government.

Seasonal forecasting of fire over Kalimantan, Indonesia

NASA Astrophysics Data System (ADS)

Spessa, A. C.; Field, R. D.; Pappenberger, F.; Langner, A.; Englhart, S.; Weber, U.; Stockdale, T.; Siegert, F.; Kaiser, J. W.; Moore, J.

2015-03-01

Large-scale fires occur frequently across Indonesia, particularly in the southern region of Kalimantan and eastern Sumatra. They have considerable impacts on carbon emissions, haze production, biodiversity, health, and economic activities. In this study, we demonstrate that severe fire and haze events in Indonesia can generally be predicted months in advance using predictions of seasonal rainfall from the ECMWF System 4 coupled ocean-atmosphere model. Based on analyses of long, up-to-date series observations on burnt area, rainfall, and tree cover, we demonstrate that fire activity is negatively correlated with rainfall and is positively associated with deforestation in Indonesia. There is a contrast between the southern region of Kalimantan (high fire activity, high tree cover loss, and strong non-linear correlation between observed rainfall and fire) and the central region of Kalimantan (low fire activity, low tree cover loss, and weak, non-linear correlation between observed rainfall and fire). The ECMWF seasonal forecast provides skilled forecasts of burnt and fire-affected area with several months lead time explaining at least 70% of the variance between rainfall and burnt and fire-affected area. Results are strongly influenced by El Niño years which show a consistent positive bias. Overall, our findings point to a high potential for using a more physical-based method for predicting fires with several months lead time in the tropics rather than one based on indexes only. We argue that seasonal precipitation forecasts should be central to Indonesia's evolving fire management policy.

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

NASA Astrophysics Data System (ADS)

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

2017-08-01

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

Synthetic generation of spatially high resolution extreme rainfall in Japan using Monte Carlo simulation with AMeDAS analyzed rainfall data sets

NASA Astrophysics Data System (ADS)

Haruki, W.; Iseri, Y.; Takegawa, S.; Sasaki, O.; Yoshikawa, S.; Kanae, S.

2016-12-01

Natural disasters caused by heavy rainfall occur every year in Japan. Effective countermeasures against such events are important. In 2015, a catastrophic flood occurred in Kinu river basin, which locates in the northern part of Kanto region. The remarkable feature of this flood event was not only in the intensity of rainfall but also in the spatial characteristics of heavy rainfall area. The flood was caused by continuous overlapping of heavy rainfall area over the Kinu river basin, suggesting consideration of spatial extent is quite important to assess impacts of heavy rainfall events. However, the spatial extent of heavy rainfall events cannot be properly measured through rainfall measurement by rain gauges at observation points. On the other hand, rainfall measurements by radar observations provide spatially and temporarily high resolution rainfall data which would be useful to catch the characteristics of heavy rainfall events. For long term effective countermeasure, extreme heavy rainfall scenario considering rainfall area and distribution is required. In this study, a new method for generating extreme heavy rainfall events using Monte Carlo Simulation has been developed in order to produce extreme heavy rainfall scenario. This study used AMeDAS analyzed precipitation data which is high resolution grid precipitation data made by Japan Meteorological Agency. Depth area duration (DAD) analysis has been conducted to extract extreme rainfall events in the past, considering time and spatial scale. In the Monte Carlo Simulation, extreme rainfall event is generated based on events extracted by DAD analysis. Extreme heavy rainfall events are generated in specific region in Japan and the types of generated extreme heavy rainfall events can be changed by varying the parameter. For application of this method, we focused on Kanto region in Japan. As a result, 3000 years rainfall data are generated. 100 -year probable rainfall and return period of flood in Kinu River Basin (2015) are obtained using generated data. We compared 100-year probable rainfall calculated by this method with other traditional method. New developed method enables us to generate extreme rainfall events considering time and spatial scale and produce extreme rainfall scenario.

Improving rainfall representation for large-scale hydrological modelling of tropical mountain basins

NASA Astrophysics Data System (ADS)

Zulkafli, Zed; Buytaert, Wouter; Onof, Christian; Lavado, Waldo; Guyot, Jean-Loup

2013-04-01

Errors in the forcing data are sometimes overlooked in hydrological studies even when they could be the most important source of uncertainty. The latter particularly holds true in tropical countries with short historical records of rainfall monitoring and remote areas with sparse rain gauge network. In such instances, alternative data such as the remotely sensed precipitation from the TRMM (Tropical Rainfall Measuring Mission) satellite have been used. These provide a good spatial representation of rainfall processes but have been established in the literature to contain volumetric biases that may impair the results of hydrological modelling or worse, are compensated during model calibration. In this study, we analysed precipitation time series from the TMPA (TRMM Multiple Precipitation Algorithm, version 6) against measurements from over 300 gauges in the Andes and Amazon regions of Peru and Ecuador. We found moderately good monthly correlation between the pixel and gauge pairs but a severe underestimation of rainfall amounts and wet days. The discrepancy between the time series pairs is particularly visible over the east side of the Andes and may be attributed to localized and orographic-driven high intensity rainfall, which the satellite product may have limited skills at capturing due to technical and scale issues. This consequently results in a low bias in the simulated streamflow volumes further downstream. In comparison, with the recently released TMPA, version 7, the biases reduce. This work further explores several approaches to merge the two sources of rainfall measurements, each of a different spatial and temporal support, with the objective of improving the representation of rainfall in hydrological simulations. The methods used are (1) mean bias correction (2) data assimilation using Kalman filter Bayesian updating. The results are evaluated by means of (1) a comparison of runoff ratios (the ratio of the total runoff and the total precipitation over an extended period) in multiple basins, and (2) a comparison of the outcome of hydrological modelling using the distributed JULES (Joint-UK Land Environment Simulator) land surface model. First results indicate an improvement in the water balance that directly translates into an increased hydrological performance. The more interesting aspect of the study, however, will be the insights into the nature of satellite precipitation errors in this extreme environment and the optimal means of improving the data to generate increased confidence in hydrological predictions.

Regional trends in short-duration precipitation extremes: a flexible multivariate monotone quantile regression approach

NASA Astrophysics Data System (ADS)

Cannon, Alex

2017-04-01

Estimating historical trends in short-duration rainfall extremes at regional and local scales is challenging due to low signal-to-noise ratios and the limited availability of homogenized observational data. In addition to being of scientific interest, trends in rainfall extremes are of practical importance, as their presence calls into question the stationarity assumptions that underpin traditional engineering and infrastructure design practice. Even with these fundamental challenges, increasingly complex questions are being asked about time series of extremes. For instance, users may not only want to know whether or not rainfall extremes have changed over time, they may also want information on the modulation of trends by large-scale climate modes or on the nonstationarity of trends (e.g., identifying hiatus periods or periods of accelerating positive trends). Efforts have thus been devoted to the development and application of more robust and powerful statistical estimators for regional and local scale trends. While a standard nonparametric method like the regional Mann-Kendall test, which tests for the presence of monotonic trends (i.e., strictly non-decreasing or non-increasing changes), makes fewer assumptions than parametric methods and pools information from stations within a region, it is not designed to visualize detected trends, include information from covariates, or answer questions about the rate of change in trends. As a remedy, monotone quantile regression (MQR) has been developed as a nonparametric alternative that can be used to estimate a common monotonic trend in extremes at multiple stations. Quantile regression makes efficient use of data by directly estimating conditional quantiles based on information from all rainfall data in a region, i.e., without having to precompute the sample quantiles. The MQR method is also flexible and can be used to visualize and analyze the nonlinearity of the detected trend. However, it is fundamentally a univariate technique, and cannot incorporate information from additional covariates, for example ENSO state or physiographic controls on extreme rainfall within a region. Here, the univariate MQR model is extended to allow the use of multiple covariates. Multivariate monotone quantile regression (MMQR) is based on a single hidden-layer feedforward network with the quantile regression error function and partial monotonicity constraints. The MMQR model is demonstrated via Monte Carlo simulations and the estimation and visualization of regional trends in moderate rainfall extremes based on homogenized sub-daily precipitation data at stations in Canada.

Freshwater monsoon related inputs in the Japan Sea: a diatom record from IODP core U1427

NASA Astrophysics Data System (ADS)

Ventura, C. P. L.; Lopes, C.

2016-12-01

Monsoon rainfall is the life-blood of more than half the world's population. Extensive research is being conducted in order to refine projections regarding the impact of anthropogenic climate change on these systems. The East Asian monsoon (EAM) plays a significant role in large-scale climate variability. Due to its importance to global climate and world's population, there is an urgent need for greater understanding of this system, especially during past climate changes. The input of freshwater from the monsoon precipitation brings specific markers, such as freshwater diatoms and specific diatom ecological assemblages that are preserved in marine sediments. Freshwater diatoms are easily identifiable and have been used in the North Pacific to reconstruct environmental conditions (Lopes et al 2006) and flooding episodes (Lopes and Mix, 2009). Here we show preliminary results of freshwater diatoms records that are linked with river discharge due to increase land rainfall that can be derived from Monsoon rainfall. We extend our preliminary study to the past 400ky.

A framework for nowcasting and forecasting of rainfall-triggered landslide activity using remotely sensed data

NASA Astrophysics Data System (ADS)

Kirschbaum, Dalia; Stanley, Thomas

2016-04-01

Remote sensing data offers the unique perspective to provide situational awareness of hydrometeorological hazards over large areas in a way that is impossible to achieve with in situ data. Recent work has shown that rainfall-triggered landslides, while typically local hazards that occupy small spatial areas, can be approximated over regional or global scales in near real-time. This work presents a regional and global approach to approximating potential landslide activity using the landslide hazard assessment for situational awareness (LHASA) model. This system couples remote sensing data, including Global Precipitation Measurement rainfall data, Shuttle Radar Topography Mission and other surface variables to estimate where and when landslide activity may be likely. This system also evaluates the effectiveness of quantitative precipitation estimates from the Goddard Earth Observing System Model, Version 5 to provide a 24 forecast of potential landslide activity. Preliminary results of the LHASA model and implications for are presented for a regional version of this system in Central America as well as a prototype global approach.

Scaling laws for testing of high lift airfoils under heavy rainfall

NASA Technical Reports Server (NTRS)

Bilanin, A. J.

1985-01-01

The results of studies regarding the effect of rainfall about aircraft are briefly reviewed. It is found that performance penalties on airfoils have been identified in subscale tests. For this reason, it is of great importance that scaling laws be dveloped to aid in the extrapolation of these data to fullscale. The present investigation represents an attempt to develop scaling laws for testing subscale airfoils under heavy rain conditions. Attention is given to rain statistics, airfoil operation in heavy rain, scaling laws, thermodynamics of condensation and/or evaporation, rainfall and airfoil scaling, aspects of splash back, film thickness, rivulets, and flap slot blockage. It is concluded that the extrapolation of airfoil performance data taken at subscale under simulated heavy rain conditions to fullscale must be undertaken with caution.

Sensitivity of Rainfall Extremes Under Warming Climate in Urban India

NASA Astrophysics Data System (ADS)

Ali, H.; Mishra, V.

2017-12-01

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

Historical climate controls soil respiration responses to current soil moisture.

PubMed

Hawkes, Christine V; Waring, Bonnie G; Rocca, Jennifer D; Kivlin, Stephanie N

2017-06-13

Ecosystem carbon losses from soil microbial respiration are a key component of global carbon cycling, resulting in the transfer of 40-70 Pg carbon from soil to the atmosphere each year. Because these microbial processes can feed back to climate change, understanding respiration responses to environmental factors is necessary for improved projections. We focus on respiration responses to soil moisture, which remain unresolved in ecosystem models. A common assumption of large-scale models is that soil microorganisms respond to moisture in the same way, regardless of location or climate. Here, we show that soil respiration is constrained by historical climate. We find that historical rainfall controls both the moisture dependence and sensitivity of respiration. Moisture sensitivity, defined as the slope of respiration vs. moisture, increased fourfold across a 480-mm rainfall gradient, resulting in twofold greater carbon loss on average in historically wetter soils compared with historically drier soils. The respiration-moisture relationship was resistant to environmental change in field common gardens and field rainfall manipulations, supporting a persistent effect of historical climate on microbial respiration. Based on these results, predicting future carbon cycling with climate change will require an understanding of the spatial variation and temporal lags in microbial responses created by historical rainfall.

Large-scale atmospheric conditions associated with heavy rainfall episodes in Southeast Brazil

NASA Astrophysics Data System (ADS)

Lima, Kellen Carla; Satyamurty, Prakki; Fernández, Júlio Pablo Reyes

2010-07-01

Heavy rainfall events in austral summer are responsible for almost all the natural disasters in Southeast Brazil. They are mostly associated with two types of atmospheric perturbations: Cold Front (53%) and the South Atlantic Convergence Zone (47%). The important question of what synoptic characteristics distinguish a heavy rainfall event (HRE) from a normal rainfall event (NRE) is addressed in this study. Here, the evolutions of such characteristics are identified through the anomalies with respect to climatology of the composite fields of atmospheric variables. The anomalies associated with HRE are significantly more intense than those associated with NRE in all fundamental atmospheric variables such as outgoing long-wave radiation, sea-level pressure, 500-hPa geopotential, lower and upper tropospheric winds. The moisture flux convergence over Southeast Brazil in the HRE composites is 60% larger than in the NRE composites. The energetics calculations for the HRE that occurred in the beginning of February 1988 strongly suggest that the barotropic instability played an important role in the intensification of the perturbation. These results, especially the intensities of the wind, pressure anomalies, and the moisture convergence are useful for the meteorologists of the Southeast Brazil for forecasting heavy precipitation.

Characteristics of pulsed runoff-erosion events under typical rainstorms in a small watershed on the Loess Plateau of China.

PubMed

Wu, Lei; Jiang, Jun; Li, Gou-Xia; Ma, Xiao-Yi

2018-02-27

The pulsed events of rainstorm erosion on the Loess Plateau are well-known, but little information is available concerning the characteristics of superficial soil erosion processes caused by heavy rainstorms at the watershed scale. This study statistically evaluated characteristics of pulsed runoff-erosion events based on 17 observed rainstorms from 1997-2010 in a small loess watershed on the Loess Plateau of China. Results show that: 1) Rainfall is the fundamental driving force of soil erosion on hillslopes, but the correlations of rainfall-runoff and rainfall-sediment in different rainstorms are often scattered due to infiltration-excess runoff and soil conservation measures. 2) Relationships between runoff and sediment for each rainstorm event can be regressed by linear, power, logarithmic and exponential functions. Cluster Analysis is helpful in classifying runoff-erosion events and formulating soil conservation strategies for rainstorm erosion. 3) Response characteristics of sediment yield are different in different levels of pulsed runoff-erosion events. Affected by rainfall intensity and duration, large changes may occur in the interactions between flow and sediment for different flood events. Results provide new insights into runoff-erosion processes and will assist soil conservation planning in the loess hilly region.

Sensitivity of convective precipitation to soil moisture and vegetation during break spell of Indian summer monsoon

NASA Astrophysics Data System (ADS)

Kutty, Govindan; Sandeep, S.; Vinodkumar; Nhaloor, Sreejith

2017-07-01

Indian summer monsoon rainfall is characterized by large intra-seasonal fluctuations in the form of active and break spells in rainfall. This study investigates the role of soil moisture and vegetation on 30-h precipitation forecasts during the break monsoon period using Weather Research and Forecast (WRF) model. The working hypothesis is that reduced rainfall, clear skies, and wet soil condition during the break monsoon period enhance land-atmosphere coupling over central India. Sensitivity experiments are conducted with modified initial soil moisture and vegetation. The results suggest that an increase in antecedent soil moisture would lead to an increase in precipitation, in general. The precipitation over the core monsoon region has increased by enhancing forest cover in the model simulations. Parameters such as Lifting Condensation Level, Level of Free Convection, and Convective Available Potential Energy indicate favorable atmospheric conditions for convection over forests, when wet soil conditions prevail. On spatial scales, the precipitation is more sensitive to soil moisture conditions over northeastern parts of India. Strong horizontal gradient in soil moisture and orographic uplift along the upslopes of Himalaya enhanced rainfall over the east of Indian subcontinent.

Regimes of Diurnal Variation of Summer Rainfall over Subtropical East Asia

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

Yuan W.; Lin W.; Yu, R.

2012-05-01

Using hourly rain gauge records and Tropical Rainfall Measuring Mission 3B42 from 1998 to 2006, the authors present an analysis of the diurnal characteristics of summer rainfall over subtropical East Asia. The study shows that there are four different regimes of distinct diurnal variation of rainfall in both the rain gauge and the satellite data. They are located over the Tibetan Plateau with late-afternoon and midnight peaks, in the western China plain with midnight to early-morning peaks, in the eastern China plain with double peaks in late afternoon and early morning, and over the East China Sea with an early-morningmore » peak. No propagation of diurnal phases is found from the land to the ocean across the coastlines. The different diurnal regimes are highly correlated with the inhomogeneous underlying surface, such as the plateau, plain, and ocean, with physical mechanisms consistent with the large-scale 'mountain-valley' and 'land-sea' breezes and convective instability. These diurnal characteristics over subtropical East Asia can be used as diagnostic metrics to evaluate the physical parameterization and hydrological cycle of climate models over East Asia.« less

Precipitation variability in the winter rainfall zone of South Africa during the last 1400 yr linked to the austral westerlies

NASA Astrophysics Data System (ADS)

Stager, J. C.; Mayewski, P. A.; White, J.; Chase, B. M.; Neumann, F. H.; Meadows, M. E.; King, C. D.; Dixon, D. A.

2011-12-01

The austral westerlies strongly influence precipitation and ocean circulation in the southern temperate zone, with important consequences for cultures and ecosystems. Global climate models anticipate poleward contraction of the austral westerlies with future warming, but the available paleoclimate records that might test these models have been largely limited to South America, are not fully consistent with each other, and may be complicated by influences from other climatic factors. Here we present the first fine-interval diatom and sedimentological records from the winter rainfall region of South Africa, representing precipitation during the last 1400 yr. Inferred rainfall increased ~1400-1200 cal yr BP and most notably during the Little Ice Age with pulses centered on ~600, 530, 470, 330, 200, and 90 cal yr BP. Synchronous fluctuations in Antarctic ice core chemistry strongly suggest that these variations are linked to changes in the westerlies. Partial inconsistencies among South African and South American records warn against the simplistic application of local-scale histories to the Southern Hemisphere as a whole. Nonetheless, these findings in general do support model projections of increasing aridity in austral winter rainfall zones with future warming.

The analysis of dependence between extreme rainfall and storm surge in the coastal zone

NASA Astrophysics Data System (ADS)

Zheng, F.; Westra, S.

2012-12-01

Flooding in coastal catchments can be caused by runoff generated by an extreme rainfall event, elevated sea levels due to an extreme storm surge event, or the combination of both processes occurring simultaneously or in close succession. Dependence in extreme rainfall and storm surge arises because common meteorological forcings often drive both variables; for example, cyclonic systems may produce extreme rainfall, strong onshore winds and an inverse barometric effect simultaneously, which the former factor influencing catchment discharge and the latter two factors influencing storm surge. Nevertheless there is also the possibility that only one of the variables is extreme at any given time, so that the dependence between rainfall and storm surge is not perfect. Quantification of the strength of dependence between these processes is critical in evaluating the magnitude of flood risk in the coastal zone. This may become more important in the future as the majority of the coastal areas are threatened by the sea level rise due to the climate change. This research uses the most comprehensive record of rainfall and storm surge along the coastline of Australia collected to-date to investigate the strength of dependence between the extreme rainfall and storm surge along the Australia coastline. A bivariate logistic threshold-excess model was employed to this end to carry out the dependence analysis. The strength of the estimated dependence is then evaluated as a function of several factors including: the distance between the tidal gauge and the rain gauge; the lag between the extreme precipitation event and extreme surge event; and the duration of the maximum storm burst. The results show that the dependence between the extreme rainfall and storm surge along the Australia coastline is statistically significant, although some locations clearly exhibit stronger dependence than others. We hypothesize that this is due to a combination of large-scale meteorological effects as well as local scale bathymetry. Additionally, significant dependence can be observed over spatial distances of up to several hundred kilometers, implying that meso-scale meteorological forcings may play an important role in driving the dependence. This is also consistent with the result which shows that significant dependence often remaining for lags of up to one or two days between extremal rainfall and storm surge events. The influence of storm burst duration can also be observed, with rainfall extremes lasting more than several hours typically being more closely associated with storm surge compared with sub-hourly rainfall extremes. These results will have profound implications for how flood risk is evaluated along the coastal zone in Australia, with the strength of dependence varying depending on: (1) the dominant meteorological conditions; (2) the local estuary configuration, influencing the strength of the surge; and (3) the catchment attributes, influencing the duration of the storm burst that will deliver the peak flood events. Although a strong random component remains, we show that the probability of an extreme storm surge during an extreme rainfall event (or vice versa) can be up to ten times greater than under the situation under which there is no dependence, suggesting that failure to account for these interactions can result in a substantial underestimation of flood risk.

Validation and evaluation of epistemic uncertainty in rainfall thresholds for regional scale landslide forecasting

NASA Astrophysics Data System (ADS)

Gariano, Stefano Luigi; Brunetti, Maria Teresa; Iovine, Giulio; Melillo, Massimo; Peruccacci, Silvia; Terranova, Oreste Giuseppe; Vennari, Carmela; Guzzetti, Fausto

2015-04-01

Prediction of rainfall-induced landslides can rely on empirical rainfall thresholds. These are obtained from the analysis of past rainfall events that have (or have not) resulted in slope failures. Accurate prediction requires reliable thresholds, which need to be validated before their use in operational landslide warning systems. Despite the clear relevance of validation, only a few studies have addressed the problem, and have proposed and tested robust validation procedures. We propose a validation procedure that allows for the definition of optimal thresholds for early warning purposes. The validation is based on contingency table, skill scores, and receiver operating characteristic (ROC) analysis. To establish the optimal threshold, which maximizes the correct landslide predictions and minimizes the incorrect predictions, we propose an index that results from the linear combination of three weighted skill scores. Selection of the optimal threshold depends on the scope and the operational characteristics of the early warning system. The choice is made by selecting appropriately the weights, and by searching for the optimal (maximum) value of the index. We discuss weakness in the validation procedure caused by the inherent lack of information (epistemic uncertainty) on landslide occurrence typical of large study areas. When working at the regional scale, landslides may have occurred and may have not been reported. This results in biases and variations in the contingencies and the skill scores. We introduce two parameters to represent the unknown proportion of rainfall events (above and below the threshold) for which landslides occurred and went unreported. We show that even a very small underestimation in the number of landslides can result in a significant decrease in the performance of a threshold measured by the skill scores. We show that the variations in the skill scores are different for different uncertainty of events above or below the threshold. This has consequences in the ROC analysis. We applied the proposed procedure to a catalogue of rainfall conditions that have resulted in landslides, and to a set of rainfall events that - presumably - have not resulted in landslides, in Sicily, in the period 2002-2012. First, we determined regional event duration-cumulated event (ED) rainfall thresholds for shallow landslide occurrence using 200 rainfall conditions that have resulted in 223 shallow landslides in Sicily in the period 2002-2011. Next, we validated the thresholds using 29 rainfall conditions that have triggered 42 shallow landslides in Sicily in 2012, and 1250 rainfall events that presumably have not resulted in landslides in the same year. We performed a back analysis simulating the use of the thresholds in a hypothetical landslide warning system operating in 2012.

Correcting satellite-based precipitation products through SMOS soil moisture data assimilation in two land-surface models of different complexity: API and SURFEX

USDA-ARS?s Scientific Manuscript database

Real-time rainfall accumulation estimates at the global scale is useful for many applications. However, the real-time versions of satellite-based rainfall products are known to contain errors relative to real rainfall observed in situ. Recent studies have demonstrated how information about rainfall ...

Feasibility of Using Elastic Wave Velocity Monitoring for Early Warning of Rainfall-Induced Slope Failure

PubMed Central

Chen, Yulong; Irfan, Muhammad; Uchimura, Taro; Zhang, Ke

2018-01-01

Rainfall-induced landslides are one of the most widespread slope instability phenomena posing a serious risk to public safety worldwide so that their temporal prediction is of great interest to establish effective warning systems. The objective of this study is to determine the effectiveness of elastic wave velocities in the surface layer of the slope in monitoring, prediction and early warning of landslide. The small-scale fixed and varied, and large-scale slope model tests were conducted. Analysis of the results has established that the elastic wave velocity continuously decreases in response of moisture content and deformation and there was a distinct surge in the decrease rate of wave velocity when failure was initiated. Based on the preliminary results of this analysis, the method using the change in elastic wave velocity proves superior for landslide early warning and suggests that a warning be issued at switch of wave velocity decrease rate. PMID:29584699

Evaluating the influence of gully erosion on landslide hazard analysis triggered by heavy rainfall

NASA Astrophysics Data System (ADS)

Ruljigaljig, Tjuku; Tsai, Ching-Jun; Peng, Wen-Fei; Yu, Teng-To

2017-04-01

During the rainstorm period such as typhoon or heavy rain, the development of gully will induce a large-scale landslide. The purpose of this study is to assess and quantify the existence and development of gully for the purpose of triggering landslides by analyzing the landslides hazard. Firstly, based on multi-scale DEM data, this study uses wavelet transform to construct an automatic algorithm. The 1-meter DEM is used to evaluate the location and type of gully, and to establish an evaluation model for predicting erosion development.In this study, routes in the Chai-Yi were studied to clarify the damage potential of roadways from local gully. The local of gully is regarded as a parameter to reduce the strength parameter. The distribution of factor of safe (F.S.) is compared with the landslide inventory map. The result of this research could be used to increase the prediction accuracy of landslide hazard analysis due to heavy rainfalls.

Three millennia of heavy rainfalls in Western Mediterranean: frequency, seasonality and atmospheric drivers

PubMed Central

Corella, J. P.; Valero-Garcés, B. L.; Vicente- Serrano, S. M.; Brauer, A.; Benito, G.

2016-01-01

Documenting subdecadal-scale heavy rainfall (HR) variability over several millennia can rarely be accomplished due to the paucity of high resolution, homogeneous and continuous proxy records. Here, using a unique, seasonally resolved lake record from southern Europe, we quantify temporal changes in extreme HR events for the last 2,800 years in this region and their correlation with negative phases of the Mediterranean Oscillation (MO). Notably, scarce HR dominated by a persistent positive MO mode characterizes the so-called Migration period (CE 370–670). Large hydroclimatic variability, particularly between CE 1012 and 1164, singles out the Medieval Climatic Anomaly, whereas more stationary HR conditions occurred between CE 1537 and 1805 coinciding with the Little Ice Age. This exceptional paleohydrological record highlights that the present-day trend towards strengthened hydrological deficit and less HR in the western Mediterranean is neither acute nor unusual in the context of Late Holocene hydrometeorological variability at centennial to decadal time scales. PMID:27910953

Three millennia of heavy rainfalls in Western Mediterranean: frequency, seasonality and atmospheric drivers

NASA Astrophysics Data System (ADS)

Corella, J. P.; Valero-Garcés, B. L.; Vicente-Serrano, S. M.; Brauer, A.; Benito, G.

2016-12-01

Documenting subdecadal-scale heavy rainfall (HR) variability over several millennia can rarely be accomplished due to the paucity of high resolution, homogeneous and continuous proxy records. Here, using a unique, seasonally resolved lake record from southern Europe, we quantify temporal changes in extreme HR events for the last 2,800 years in this region and their correlation with negative phases of the Mediterranean Oscillation (MO). Notably, scarce HR dominated by a persistent positive MO mode characterizes the so-called Migration period (CE 370-670). Large hydroclimatic variability, particularly between CE 1012 and 1164, singles out the Medieval Climatic Anomaly, whereas more stationary HR conditions occurred between CE 1537 and 1805 coinciding with the Little Ice Age. This exceptional paleohydrological record highlights that the present-day trend towards strengthened hydrological deficit and less HR in the western Mediterranean is neither acute nor unusual in the context of Late Holocene hydrometeorological variability at centennial to decadal time scales.

Effect of Spatio-Temporal Variability of Rainfall on Stream flow Prediction of Birr Watershed

NASA Astrophysics Data System (ADS)

Demisse, N. S.; Bitew, M. M.; Gebremichael, M.

2012-12-01

The effect of rainfall variability on our ability to forecast flooding events was poorly studied in complex terrain region of Ethiopia. In order to establish relation between rainfall variability and stream flow, we deployed 24 rain gauges across Birr watershed. Birr watershed is a medium size mountainous watershed with an area of 3000 km2 and elevation ranging between 1435 m.a.s.l and 3400 m.a.s.l in the central Ethiopia highlands. One summer monsoon rainfall of 2012 recorded at high temporal scale of 15 minutes interval and stream flow recorded at an hourly interval in three sub-watershed locations representing different scales were used in this study. Based on the data obtained from the rain gauges and stream flow observations, we quantify extent of temporal and spatial variability of rainfall across the watershed using standard statistical measures including mean, standard deviation and coefficient of variation. We also establish rainfall-runoff modeling system using a physically distributed hydrological model: the Soil and Water Assessment Tool (SWAT) and examine the effect of rainfall variability on stream flow prediction. The accuracy of predicted stream flow is measured through direct comparison with observed flooding events. The results demonstrate the significance of relation between stream flow prediction and rainfall variability in the understanding of runoff generation mechanisms at watershed scale, determination of dominant water balance components, and effect of variability on accuracy of flood forecasting activities.

Exploratory analysis of rainfall events in Coimbra, Portugal: variability of raindrop characteristics

NASA Astrophysics Data System (ADS)

Carvalho, S. C. P.; de Lima, M. I. P.; de Lima, J. L. M. P.

2012-04-01

Laser disdrometers can monitor efficiently rainfall characteristics at small temporal scales, providing data on rain intensity, raindrop diameter and fall speed, and raindrop counts over time. This type of data allows for the increased understanding of the rainfall structure at small time scales. Of particular interest for many hydrological applications is the characterization of the properties of extreme events, including the intra-event variability, which are affected by different factors (e.g. geographical location, rainfall generating mechanisms). These properties depend on the microphysical, dynamical and kinetic processes that interact to produce rain. In this study we explore rainfall data obtained during two years with a laser disdrometer installed in the city of Coimbra, in the centre region of mainland Portugal. The equipment was developed by Thies Clima. The data temporal resolution is one-minute. Descriptive statistics of time series of raindrop diameter (D), fall speed, kinetic energy, and rain rate were studied at the event scale; for different variables, the average, maximum, minimum, median, variance, standard deviation, quartile, coefficient of variation, skewness and kurtosis were determined. The empirical raindrop size distribution, N(D), was also calculated. Additionally, the parameterization of rainfall was attempted by investigating the applicability of different theoretical statistical distributions to fit the empirical data (e.g. exponential, gamma and lognormal distributions). As expected, preliminary results show that rainfall properties and structure vary with rainfall type and weather conditions over the year. Although only two years were investigated, already some insight into different rain events' structure was obtained.

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

On the consideration of scaling properties of extreme rainfall in Madrid (Spain) for developing a generalized intensity-duration-frequency equation and assessing probable maximum precipitation estimates

NASA Astrophysics Data System (ADS)

Casas-Castillo, M. Carmen; Rodríguez-Solà, Raúl; Navarro, Xavier; Russo, Beniamino; Lastra, Antonio; González, Paula; Redaño, Angel

2018-01-01

The fractal behavior of extreme rainfall intensities registered between 1940 and 2012 by the Retiro Observatory of Madrid (Spain) has been examined, and a simple scaling regime ranging from 25 min to 3 days of duration has been identified. Thus, an intensity-duration-frequency (IDF) master equation of the location has been constructed in terms of the simple scaling formulation. The scaling behavior of probable maximum precipitation (PMP) for durations between 5 min and 24 h has also been verified. For the statistical estimation of the PMP, an envelope curve of the frequency factor ( k m ) based on a total of 10,194 station-years of annual maximum rainfall from 258 stations in Spain has been developed. This curve could be useful to estimate suitable values of PMP at any point of the Iberian Peninsula from basic statistical parameters (mean and standard deviation) of its rainfall series. [Figure not available: see fulltext.

Water Isotope Proxy-Proxy and Proxy-Model Convergence for Late Pleistocene East Asian Monsoon Rainfall Reconstructions

NASA Astrophysics Data System (ADS)

Clemens, S. C.; Holbourn, A.; Kubota, Y.; Lee, K. E.; Liu, Z.; Chen, G.

2017-12-01

Confidence in reconstruction of East Asian paleomonsoon rainfall using precipitation isotope proxies is a matter of considerable debate, largely due to the lack of correlation between precipitation amount and isotopic composition in the present climate. We present four new, very highly resolved records spanning the past 300,000 years ( 200 year sample spacing) from IODP Site U1429 in the East China Sea. We demonstrate that all the orbital- and millennial-scale variance in the onshore Yangtze River Valley speleothem δ18O record1 is also embedded in the offshore Site U1429 seawater δ18O record (derived from the planktonic foraminifer Globigerinoides ruber and sea surface temperature reconstructions). Signal replication in these two independent terrestrial and marine archives, both controlled by the same monsoon system, uniquely identifies δ18O of precipitation as the primary driver of the precession-band variance in both records. This proxy-proxy convergence also eliminates a wide array of other drivers that have been called upon as potential contaminants to the precipitation δ18O signal recorded by these proxies. We compare East Asian precipitation isotope proxy records to precipitation amount from a CCSM3 transient climate model simulation of the past 300,000 years using realistic insolation, ice volume, greenhouse gasses, and sea level boundary conditions. This model-proxy comparison suggests that both Yangtze River Valley precipitation isotope proxies (seawater and speleothem δ18O) track changes in summer-monsoon rainfall amount at orbital time scales, as do precipitation isotope records from the Pearl River Valley2 (leaf wax δ2H) and Borneo3 (speleothem δ18O). Notably, these proxy records all have significantly different spectral structure indicating strongly regional rainfall patterns that are also consistent with model results. Transient, isotope-enabled model simulations will be necessary to more thoroughly evaluate these promising results, and to evaluate potentially distinct regional mechanisms linking rainfall amount to precipitation isotopes at orbital and millennial time scales in other monsoon regions. 1 Cheng et al., 10.1038/nature18591 2 Thomas et al., 10.1130/G36289.1 3 Carolin et al., 10.1016/j.epsl.2016.01.028

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

NASA Technical Reports Server (NTRS)

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

2000-01-01

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

Assessing the statistical relationships among water-derived climate variables, rainfall, and remotely sensed features of vegetation: implications for evaluating the habitat of ticks.

PubMed

Alonso-Carné, J; García-Martín, A; Estrada-Peña, A

2015-01-01

Ticks are sensitive to changes in relative humidity and saturation deficit at the microclimate scale. Trends and changes in rainfall are commonly used as descriptors of field observations of tick populations, to capture the climate niche of ticks or to predict the climate suitability for ticks under future climate scenarios. We evaluated daily and monthly relationships between rainfall, relative humidity and saturation deficit over different ecosystems in Europe using daily climate values from 177 stations over a period of 10 years. We demonstrate that rainfall is poorly correlated with both relative humidity and saturation deficit in any of the ecological domains studied. We conclude that the amount of rainfall recorded in 1 day does not correlate with the values of humidity or saturation deficit recorded 24 h later: rainfall is not an adequate surrogate for evaluating the physiological processes of ticks at regional scales. We compared the Normalized Difference Vegetation Index (NDVI), a descriptor of photosynthetic activity, at a spatial resolution of 0.05°, with monthly averages of relative humidity and saturation deficit and also determined a lack of significant correlation. With the limitations of spatial scale and habitat coverage of this study, we suggest that the rainfall or NDVI cannot replace relative humidity or saturation deficit as descriptors of tick processes.

Radar-raingauge data combination techniques: a revision and analysis of their suitability for urban hydrology.

PubMed

Wang, Li-Pen; Ochoa-Rodríguez, Susana; Simões, Nuno Eduardo; Onof, Christian; Maksimović, Cedo

2013-01-01

The applicability of the operational radar and raingauge networks for urban hydrology is insufficient. Radar rainfall estimates provide a good description of the spatiotemporal variability of rainfall; however, their accuracy is in general insufficient. It is therefore necessary to adjust radar measurements using raingauge data, which provide accurate point rainfall information. Several gauge-based radar rainfall adjustment techniques have been developed and mainly applied at coarser spatial and temporal scales; however, their suitability for small-scale urban hydrology is seldom explored. In this paper a review of gauge-based adjustment techniques is first provided. After that, two techniques, respectively based upon the ideas of mean bias reduction and error variance minimisation, were selected and tested using as case study an urban catchment (∼8.65 km(2)) in North-East London. The radar rainfall estimates of four historical events (2010-2012) were adjusted using in situ raingauge estimates and the adjusted rainfall fields were applied to the hydraulic model of the study area. The results show that both techniques can effectively reduce mean bias; however, the technique based upon error variance minimisation can in general better reproduce the spatial and temporal variability of rainfall, which proved to have a significant impact on the subsequent hydraulic outputs. This suggests that error variance minimisation based methods may be more appropriate for urban-scale hydrological applications.

Hydro-Geological Hazard Temporal Evolution during the last seven decades in the Solofrana River Basin—Southern Italy

NASA Astrophysics Data System (ADS)

Longobardi, Antonia; Diodato, Nazzareno; Mobilia, Mirka

2017-04-01

Extremes precipitation events are frequently associated to natural disasters falling within the broad spectrum of multiple damaging hydrological events (MDHEs), defined as the simultaneously triggering of different types of phenomena, such as landslides and floods. The power of the rainfall (duration, magnitude, intensity), named storm erosivity, is an important environmental indicator of multiple damaging hydrological phenomena. At the global scale, research interest is actually devoted to the investigation of non-stationary features of extreme events, and consequently of MDHEs, which appear to be increasing in frequency and severity. The Mediterranean basin appears among the most vulnerable regions with an expected increase in occurring damages of about 100% by the end of the century. A high concentration of high magnitude and short duration rainfall events are, in fact, responsible for the largest rainfall erosivity and erosivity density values within Europe. The aim of the reported work is to investigate the relationship between the temporal evolution of severe geomorphological events and combined precipitation indices as a tool to improve understanding the hydro-geological hazard at the catchment scale. The case study is the Solofrana river basin, Southern Italy, which has been seriously and consistently in time affected by natural disasters. Data for about 45 MDH events, spanning on a decadal scale 1951-2014, have been collected and analyzed for this purpose. A preliminary monthly scale analysis of event occurrences highlights a pronounced seasonal characterization of the phenomenon, as about 60% of the total number of reported events take place during the period from September to November. Following, a statistical analysis clearly indicates a significant increase in the frequency of occurrences of MDHEs during the last decades. Such an increase appears to be related to non-stationary features of an average catchment scale rainfall-runoff erosivity index, which combines maximum monthly, maximum daily, and a proxy of maximum hourly precipitation data. The main findings of the reported study relate to the fact that climate evolving tendencies do not appear significant in most of the cases and that MDHEs occurred within the studied catchment also for rainfall events of very moderate intensity and/or severity. The illustrated results seems to indicate that climate variability has not assumed the main role in the large number of damaging event, and that the relative increase hazardous hydro-geological events in the last decade, is instead most likely caused by incorrect urban planning policies.

Water and salt balance modelling to predict the effects of land-use changes in forested catchments. 3. The large catchment model

NASA Astrophysics Data System (ADS)

Sivapalan, Murugesu; Viney, Neil R.; Jeevaraj, Charles G.

1996-03-01

This paper presents an application of a long-term, large catchment-scale, water balance model developed to predict the effects of forest clearing in the south-west of Western Australia. The conceptual model simulates the basic daily water balance fluxes in forested catchments before and after clearing. The large catchment is divided into a number of sub-catchments (1-5 km2 in area), which are taken as the fundamental building blocks of the large catchment model. The responses of the individual subcatchments to rainfall and pan evaporation are conceptualized in terms of three inter-dependent subsurface stores A, B and F, which are considered to represent the moisture states of the subcatchments. Details of the subcatchment-scale water balance model have been presented earlier in Part 1 of this series of papers. The response of any subcatchment is a function of its local moisture state, as measured by the local values of the stores. The variations of the initial values of the stores among the subcatchments are described in the large catchment model through simple, linear equations involving a number of similarity indices representing topography, mean annual rainfall and level of forest clearing.The model is applied to the Conjurunup catchment, a medium-sized (39·6 km2) catchment in the south-west of Western Australia. The catchment has been heterogeneously (in space and time) cleared for bauxite mining and subsequently rehabilitated. For this application, the catchment is divided into 11 subcatchments. The model parameters are estimated by calibration, by comparing observed and predicted runoff values, over a 18 year period, for the large catchment and two of the subcatchments. Excellent fits are obtained.

Assessing the radar rainfall estimates in watershed-scale water quality model

USDA-ARS?s Scientific Manuscript database

Watershed-scale water quality models are effective science-based tools for interpreting change in complex environmental systems that affect hydrology cycle, soil erosion and nutrient fate and transport in watershed. Precipitation is one of the primary input data to achieve a precise rainfall-runoff ...

Using damage data to estimate the risk from summer convective precipitation extremes

NASA Astrophysics Data System (ADS)

Schroeer, Katharina; Tye, Mari

2017-04-01

This study explores the potential added value from including loss and damage data to understand the risks from high-intensity short-duration convective precipitation events. Projected increases in these events are expected even in regions that are likely to become more arid. Such high intensity precipitation events can trigger hazardous flash floods, debris flows, and landslides that put people and local assets at risk. However, the assessment of local scale precipitation extremes is hampered by its high spatial and temporal variability. In addition to this, not only are extreme events rare, but such small-scale events are likely to be underreported where they do not coincide with the observation network. Reports of private loss and damage on a local administrative unit scale (LAU 2 level) are used to explore the relationship between observed rainfall events and damages reportedly related to hydro-meteorological processes. With 480 Austrian municipalities located within our south-eastern Alpine study region, the damage data are available on a much smaller scale than the available rainfall data. Precipitation is recorded daily at 185 gauges and 52% of these stations additionally deliver sub-hourly rainfall information. To obtain physically plausible information, damage and rainfall data are grouped and analyzed on a catchment scale. The data indicate that rainfall intensities are higher on days that coincide with a damage claim than on days for which no damage was reported. However, approximately one third of the damages related to hydro-meteorological hazards were claimed on days for which no rainfall was recorded at any gauge in the respective catchment. Our goal is to assess whether these events indicate potential extreme events missing in the observations. Damage always is a consequence of an asset being exposed and susceptible to a hazardous process, and naturally, many factors influence whether an extreme rainfall event causes damage. We set up a statistical model to test whether the relationship between extreme rainfall events and damages is robust enough to estimate a potential underrepresentation of high intensity rainfall events in ungauged areas. Risk-relevant factors of socio-economic vulnerability, land cover, streamflow data, and weather type information are included to improve and sharpen the analysis. Within this study, we first aim to identify which rainfall events are most damaging and which factors affect the damages - seen as a proxy for the vulnerability - related to summer convective rainfall extremes in different catchment types. Secondly, we aim to detect potentially unreported damaging rainfall events and estimate the likelihood of such cases. We anticipate this damage perspective on summertime extreme convective precipitation to be beneficial for risk assessment, uncertainty management, and decision making with respect to weather and climate extremes on the regional-to-local level.

Normalizing rainfall/debris-flow thresholds along the U.S. Pacific coast for long-term variations in precipitation climate

USGS Publications Warehouse

Wilson, Raymond C.

1997-01-01

Broad-scale variations in long-term precipitation climate may influence rainfall/debris-flow threshold values along the U.S. Pacific coast, where both the mean annual precipitation (MAP) and the number of rainfall days (#RDs) are controlled by topography, distance from the coastline, and geographic latitude. Previous authors have proposed that rainfall thresholds are directly proportional to MAP, but this appears to hold only within limited areas (< 1?? latitude), where rainfall frequency (#RDs) is nearly constant. MAP-normalized thresholds underestimate the critical rainfall when applied to areas to the south, where the #RDs decrease, and overestimate threshold rainfall when applied to areas to the north, where the #RDs increase. For normalization between climates where both MAP and #RDs vary significantly, thresholds may best be described as multiples of the rainy-day normal, RDN = MAP/#RDs. Using data from several storms that triggered significant debris-flow activity in southern California, the San Francisco Bay region, and the Pacific Northwest, peak 24-hour rainfalls were plotted against RDN values, displaying a linear relationship with a lower bound at about 14 RDN. RDN ratios in this range may provide a threshold for broad-scale regional forecasting of debris-flow activity.

Tool to address green roof widespread implementation effect in flood characteristics for water management planning

NASA Astrophysics Data System (ADS)

Tassi, R.; Lorenzini, F.; Allasia, D. G.

2015-06-01

In the last decades, new approaches were adopted to manage stormwater as close to its source as possible through technologies and devices that preserve and recreate natural landscape features. Green Roofs (GR) are examples of these devices that are also incentivized by city's stormwater management plans. Several studies show that GR decreases on-site runoff from impervious surfaces, however, the analysis of the effect of widespread implementation of GR in the flood characteristics at the urban basin scale in subtropical areas are little discussed, mainly because of the absence of data. Thereby, this paper shows results related to the monitoring of an extensive modular GR under subtropical weather conditions, the development of a rainfall-runoff model based on the modified Curve Number (CN) and SCS Triangular Unit Hydrograph (TUH) methods and the analysis of large-scale impact of GR by modelling different basins. The model was calibrated against observed data and showed that GR absorbed almost all the smaller storms and reduced runoff even during the most intense rainfall. The overall CN was estimated in 83 (consistent with available literature) with the shape of hydrographs well reproduced. Large-scale modelling (in basins ranging from 0.03 ha to several square kilometers) showed that the widespread use of GRs reduced peak flows (volumes) around 57% (48%) at source and 38% (32%) at the basin scale. Thus, this research validated a tool for the assessment of structural management measures (specifically GR) to address changes in flood characteristics in the city's water management planning. From the application of this model it was concluded that even if the efficiency of GR decreases as the basin scale increase they still provide a good option to cope with urbanization impact.

Classification of mechanisms, climatic context, areal scaling, and synchronization of floods: the hydroclimatology of floods in the Upper Paraná River basin, Brazil

NASA Astrophysics Data System (ADS)

Lima, Carlos H. R.; AghaKouchak, Amir; Lall, Upmanu

2017-12-01

Floods are the main natural disaster in Brazil, causing substantial economic damage and loss of life. Studies suggest that some extreme floods result from a causal climate chain. Exceptional rain and floods are determined by large-scale anomalies and persistent patterns in the atmospheric and oceanic circulations, which influence the magnitude, extent, and duration of these extremes. Moreover, floods can result from different generating mechanisms. These factors contradict the assumptions of homogeneity, and often stationarity, in flood frequency analysis. Here we outline a methodological framework based on clustering using self-organizing maps (SOMs) that allows the linkage of large-scale processes to local-scale observations. The methodology is applied to flood data from several sites in the flood-prone Upper Paraná River basin (UPRB) in southern Brazil. The SOM clustering approach is employed to classify the 6-day rainfall field over the UPRB into four categories, which are then used to classify floods into four types based on the spatiotemporal dynamics of the rainfall field prior to the observed flood events. An analysis of the vertically integrated moisture fluxes, vorticity, and high-level atmospheric circulation revealed that these four clusters are related to known tropical and extratropical processes, including the South American low-level jet (SALLJ); extratropical cyclones; and the South Atlantic Convergence Zone (SACZ). Persistent anomalies in the sea surface temperature fields in the Pacific and Atlantic oceans are also found to be associated with these processes. Floods associated with each cluster present different patterns in terms of frequency, magnitude, spatial variability, scaling, and synchronization of events across the sites and subbasins. These insights suggest new directions for flood risk assessment, forecasting, and management.

An Assessment of the Impact of the 1997-98 El Nino on the Asian-Australian Monsoon

NASA Technical Reports Server (NTRS)

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

1999-01-01

Using state-of-the-art satellite-gauge monthly rainfall estimate and optimally interpolated sea surface temperature (SST) data, we have assessed the 1997-98 AA-monsoon anomalies in terms of three basic causal factors: basin-scale SST, regional coupling, and internal variability. Singular Value Decomposition analyses of rainfall and SST are carried out globally over the entire tropics and regionally over the AA-monsoon domain. Contributions to monsoon rainfall predictability by various factors are evaluated from cumulative anomaly correlation with dominant regional SVD modes. Results reveal a dominant, large-scale monsoon-El Nino coupled mode with well-defined centers of action in the near-equatorial monsoon regions during the boreal summer and winter respectively. The observed 1997-98 AA-monsoon anomalies are found to be very complex with approximately 34% of the anomalies of the Asian (boreal) summer monsoon and 74% of the Australia (austral) monsoon attributable to basin-scale SST influence associated with El Nino. Regional coupled processes contribute an additional 19% and 10%, leaving about 47% and 16% due to internal dynamics for the boreal and austral monsoon respectively. For the boreal summer monsoon, it is noted that the highest monsoon predictability is not necessary associated with major El Nino events (e.g. 1997, 1982) but rather in non-El Nino years (e.g. 1980, 1988) when contributions from the regional coupled modes far exceed those from the basin-scale SST. The results suggest that in order to improve monsoon seasonal-to-interannual predictability, there is a need to exploit not only monsoon-El Nino relationship, but also intrinsic monsoon regional coupled processes.

Assessment of the 1997-1998 Asian Monsoon Anomalies

NASA Technical Reports Server (NTRS)

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

1999-01-01

Using State-of-the-art satellite-gauge monthly rainfall estimate and optimally interpolated sea surface temperature (SST) data, we have assessed the 1997-98 Asian monsoon anomalies in terms of three basic causal factors: basin-scale SST, regional coupling, and internal variability. Singular Value Decomposition analysis of rainfall and SST are carried out globally over the entire tropics and regionally over the Asian monsoon domain. Contributions to monsoon rainfall predictability by various factors are evaluated from cumulative anomaly correlation with dominant regional SVD modes. Results reveal a dominant, large-scale monsoon-El Nino coupled mode with well-defined centers of action in the near-equatorial monsoon regions. it is noted that some subcontinental regions such as all-India, or arbitrarily chosen land regions over East Asia, while important socio-economically, are not near the centers of influence from El Nino, hence are not necessarily representative of the response of the entire monsoon region to El Nino. The observed 1997-98 Asian monsoon anomalies are found to be very complex with approximately 34% of the anomalies attributable to basin- scale SST influence associated with El Nino. Regional coupled processes contribute an additional 19%, leaving about 47% due to internal dynamics. Also noted is that the highest monsoon predictability is not necessary associated with major El Nino events (e.g. 1997, 1982) but rather in non-El Nino years (e.g. 1980, 1988) when contributions from the regional coupled modes far exceed those from the basin-scale SST. The results suggest that in order to improve monsoon seasonal-to-interannual predictability, there is a need to exploit not only monsoon-El Nino relationship, but also monsoon regional coupled processes and their modulation by long-term climate change.

Large Scale Processes and Extreme Floods in Brazil

NASA Astrophysics Data System (ADS)

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

2016-12-01

Persistent large scale anomalies in the atmospheric circulation and ocean state have been associated with heavy rainfall and extreme floods in water basins of different sizes across the world. Such studies have emerged in the last years as a new tool to improve the traditional, stationary based approach in flood frequency analysis and flood prediction. Here we seek to advance previous studies by evaluating the dominance of large scale processes (e.g. atmospheric rivers/moisture transport) over local processes (e.g. local convection) in producing floods. We consider flood-prone regions in Brazil as case studies and the role of large scale climate processes in generating extreme floods in such regions is explored by means of observed streamflow, reanalysis data and machine learning methods. The dynamics of the large scale atmospheric circulation in the days prior to the flood events are evaluated based on the vertically integrated moisture flux and its divergence field, which are interpreted in a low-dimensional space as obtained by machine learning techniques, particularly supervised kernel principal component analysis. In such reduced dimensional space, clusters are obtained in order to better understand the role of regional moisture recycling or teleconnected moisture in producing floods of a given magnitude. The convective available potential energy (CAPE) is also used as a measure of local convection activities. We investigate for individual sites the exceedance probability in which large scale atmospheric fluxes dominate the flood process. Finally, we analyze regional patterns of floods and how the scaling law of floods with drainage area responds to changes in the climate forcing mechanisms (e.g. local vs large scale).

Requirements for future development of small scale rainfall simulators

NASA Astrophysics Data System (ADS)

Iserloh, Thomas; Ries, Johannes B.; Seeger, Manuel

2013-04-01

Rainfall simulation with small scale simulators is a method used worldwide to assess the generation of overland flow, soil erosion, infiltration and interrelated processes such as soil sealing, crusting, splash and redistribution of solids and solutes. Following the outcomes of the project "Comparability of simulation results of different rainfall simulators as input data for soil erosion modelling (Deutsche Forschungsgemeinschaft - DFG, Project No. Ri 835/6-1)" and the "International Rainfall Simulator Workshop 2011" in Trier, the necessity for further technical improvements of simulators and strategies towards an adaption of designs and methods becomes obvious. Uniform measurements of artificially generated rainfall and comparative measurements on a prepared bare fallow with rainfall simulators used by European research groups showed limitations of the comparability of the results. The following requirements, essential for small portable rainfall simulators, were identified: (I) Low and efficient water consumption for use in areas with water shortage, (II) easy handling and control of test conditions, (III) homogeneous spatial rainfall distribution, (IV) best possible drop spectrum (physically), (V) reproducibility and knowledge of spatial distribution and drop spectrum, (VI) easy and fast training of operators to obtain reproducible experiments and (VII) good mobility and easy installation for use in remote areas and in regions where highly erosive rainfall events are rare or irregular. The presentation discusses possibilities for a common use of identical plot designs, rainfall intensities and nozzles.

Some Precipitation Studies over Andhra Pradesh and the Bay of Bengal using TRMM and SSMI data

NASA Astrophysics Data System (ADS)

Rao, S. Ramalingeswara; Krishna, K. Muni; Kumar, Bhanu

2007-07-01

One of the most difficult issues in modeling the global atmosphere and climate by General Circulation Models is the simulation and initialization of precipitation processes and at the same time rainfall is most important meteorological parameter that effects India's economy. An attempt is made in the present study to evaluate diurnal variation of rain rates over the Bay of Bengal (BoB) for the months June through December during 1999-2002. TMI rainfall product of Wentz and Spencer and SSMI data sets were used in this study. Mean hourly rain rates were calculated over the BoB (10°-15° N and 85°-95°E) and discussed; this study highlights that maximum rain rates are observed in the afternoons during summer monsoon seasons. Secondly mean monthly annual cycle of rainfall is prepared using 3B42RT merged rain product and compared with mean monthly India Meteorological Department (IMD) data for the study period over Andhra Pradesh (A.P). Time series of daily variations of 3B42RT precipitation and observed real time rainfall data over A.P. for the study period is validated and the relationship between them is statistically significant at 1% level. Similarly mean monthly data prepared from the daily analysis and compared with the IMD mean monthly rainfall maps. The comparison suggests that even with only available real time data from 3B42RT and rain gauge, it is possible to construct usable large-scale rainfall maps on regular latitude-longitude grids. This analysis, which uses a high resolution and more local rain gauge data, is able to produce realistic details of Indian summer monsoon rainfall over the study period.

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

NASA Astrophysics Data System (ADS)

Woodborne, Stephan; Hall, Grant; Zhang, Qiong

2016-04-01

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

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.

Scaling properties of Polish rain series

NASA Astrophysics Data System (ADS)

Licznar, P.

2009-04-01

Scaling properties as well as multifractal nature of precipitation time series have not been studied for local Polish conditions until recently due to lack of long series of high-resolution data. The first Polish study of precipitation time series scaling phenomena was made on the base of pluviograph data from the Wroclaw University of Environmental and Life Sciences meteorological station located at the south-western part of the country. The 38 annual rainfall records from years 1962-2004 were converted into digital format and transformed into a standard format of 5-minute time series. The scaling properties and multifractal character of this material were studied by means of several different techniques: power spectral density analysis, functional box-counting, probability distribution/multiple scaling and trace moment methods. The result proved the general scaling character of time series at the range of time scales ranging form 5 minutes up to at least 24 hours. At the same time some characteristic breaks at scaling behavior were recognized. It is believed that the breaks were artificial and arising from the pluviograph rain gauge measuring precision limitations. Especially strong limitations at the precision of low-intensity precipitations recording by pluviograph rain gauge were found to be the main reason for artificial break at energy spectra, as was reported by other authors before. The analysis of co-dimension and moments scaling functions showed the signs of the first-order multifractal phase transition. Such behavior is typical for dressed multifractal processes that are observed by spatial or temporal averaging on scales larger than the inner-scale of those processes. The fractal dimension of rainfall process support derived from codimension and moments scaling functions geometry analysis was found to be 0.45. The same fractal dimension estimated by means of the functional box-counting method was equal to 0.58. At the final part of the study implementation of double trace moment method allowed for estimation of local universal multifractal rainfall parameters (α=0.69; C1=0.34; H=-0.01). The research proved the fractal character of rainfall process support and multifractal character of the rainfall intensity values variability among analyzed time series. It is believed that scaling of local Wroclaw's rainfalls for timescales at the range from 24 hours up to 5 minutes opens the door for future research concerning for example random cascades implementation for daily precipitation totals disaggregation for smaller time intervals. The results of such a random cascades functioning in a form of 5 minute artificial rainfall scenarios could be of great practical usability for needs of urban hydrology, and design and hydrodynamic modeling of storm water and combined sewage conveyance systems.

Spatial and temporal variability of rainfall and their effects on hydrological response in urban areas - a review

NASA Astrophysics Data System (ADS)

Cristiano, Elena; ten Veldhuis, Marie-claire; van de Giesen, Nick

2017-07-01

In urban areas, hydrological processes are characterized by high variability in space and time, making them sensitive to small-scale temporal and spatial rainfall variability. In the last decades new instruments, techniques, and methods have been developed to capture rainfall and hydrological processes at high resolution. Weather radars have been introduced to estimate high spatial and temporal rainfall variability. At the same time, new models have been proposed to reproduce hydrological response, based on small-scale representation of urban catchment spatial variability. Despite these efforts, interactions between rainfall variability, catchment heterogeneity, and hydrological response remain poorly understood. This paper presents a review of our current understanding of hydrological processes in urban environments as reported in the literature, focusing on their spatial and temporal variability aspects. We review recent findings on the effects of rainfall variability on hydrological response and identify gaps where knowledge needs to be further developed to improve our understanding of and capability to predict urban hydrological response.

Large-scale precipitation tracking and the MJO over the Maritime Continent and Indo-Pacific warm pool

NASA Astrophysics Data System (ADS)

Kerns, Brandon W.; Chen, Shuyi S.

2016-08-01

A large-scale precipitation tracking (LPT) method is developed to track convection and precipitation associated with the Madden-Julian oscillation (MJO) using the Tropical Rainfall Measurement Mission 3B42 rainfall data from October to March 1998-2015. LPT uses spatially smoothed 3 day rainfall accumulation to identify and track precipitation features in time with a minimum size of 300,000 km2 and time continuity at least 10 days. While not all LPT systems (LPTs) are attributable to the MJO, among the 199 LPTs, there were 42 with a mean eastward propagation of at least 2 m s-1, which are considered to be MJO convective initiation events. These LPTs capture the diversity of the MJO convection, which is not well depicted by the Real-time Multivariate MJO (RMM) index or the outgoing longwave radiation MJO index. During the 17 years, there were 17 instances out of 45 with a MJO signature in the RMM without eastward propagating LPTs. Among the 42 eastward propagating LPTs, 24 propagated across the Maritime Continent (MC), which confirms the MC barrier effect. Among the cases that crossed the MC from the Indian Ocean to the western Pacific (MC crossing), 18 (75%) had a significant MJO signature in the RMM index. In contrast, only six (33%) of the non-MC-crossing cases occurred with a RMM MJO signal. There is a significant seasonal and interannual variability with MC-crossing LPTs occurring in December more commonly than other months. More MC-crossing events were observed during La Niña than El Niño, which is consistent with the observations of stronger and more frequent MJO events identified by RMM during La Niña years.

Application of Clustering Algorithms to Observed and Simulated Daily Precipitation over the Tropical and Southern Pacific Ocean

NASA Astrophysics Data System (ADS)

Pike, M.; Lintner, B. R.

2017-12-01

We apply two data organization methods, self-organizing maps (SOMs) and k-means clustering with linear unidimensional scaling (k-means+LUS), to identify and organize the spatial patterns inherent in daily austral summer (December-January-February or DJF) rainfall over the tropical and southern Pacific Ocean basins from Tropical Rainfall Measuring Mission (TRMM) satellite observations. For either a 2x2 SOM or k = 4 clustering of all available DJFs from 1998-2013, we find an El Niño/Southern Oscillation (ENSO) signature, with pairs of maps reflecting either El Niño or La Niña phase conditions. Within each of the ENSO-phase pairs, one map favors Intertropical Convergence Zone (ITCZ)-active conditions, in which precipitation is more intense over the ITCZ region compared to the South Pacific Convergence Zone (SPCZ) region, while the remaining one is SPCZ-active. The SPCZ-active maps show a spatial translation of the principal SPCZ diagonal consistent with the impacts of El Niño/Southern Oscillation (ENSO) or analogous low-frequency modes of variability on the SPCZ as shown in prior studies. Because of the dominant impact of ENSO, we further apply these methods separately on subsets of rainfall data for each ENSO phase. While the overall position of the SPCZ is sensitive to the phase of ENSO, within each phase, more- or less-steeply sloped SPCZ diagonals may occur. Thus, while the mean position of the SPCZ is largely controlled by ENSO phase, the distinct orientations of the SPCZ within the same ENSO phase point to higher-frequency modulation of SPCZ slope. To investigate the nature of these further, we construct composites of pressure-level winds and specific humidity from the Climate Forecast System Reanalysis (CFSR) associated with the rainfall patterns. For either SOM or kmeans-based composites, we find large-scale dynamics and moisture signatures that are consistent with the rainfall patterns and which we interpret in terms of previously described mechanisms of SPCZ variability. By progressively increasing the number of clusters, patterns reminiscent of Rossby wave propagation begin to emerge. To further investigate the connection to propagation, we examine upper air vorticity composites in relationship to the periodic enhancements of SPCZ precipitation which appear to be independent of ENSO.

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

NASA Astrophysics Data System (ADS)

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

2017-05-01

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

Intensity-Duration-Frequency curves from remote sensing datasets: direct comparison of weather radar and CMORPH over the Eastern Mediterranean

NASA Astrophysics Data System (ADS)

Morin, Efrat; Marra, Francesco; Peleg, Nadav; Mei, Yiwen; Anagnostou, Emmanouil N.

2017-04-01

Rainfall frequency analysis is used to quantify the probability of occurrence of extreme rainfall and is traditionally based on rain gauge records. The limited spatial coverage of rain gauges is insufficient to sample the spatiotemporal variability of extreme rainfall and to provide the areal information required by management and design applications. Conversely, remote sensing instruments, even if quantitative uncertain, offer coverage and spatiotemporal detail that allow overcoming these issues. In recent years, remote sensing datasets began to be used for frequency analyses, taking advantage of increased record lengths and quantitative adjustments of the data. However, the studies so far made use of concepts and techniques developed for rain gauge (i.e. point or multiple-point) data and have been validated by comparison with gauge-derived analyses. These procedures add further sources of uncertainty and prevent from isolating between data and methodological uncertainties and from fully exploiting the available information. In this study, we step out of the gauge-centered concept presenting a direct comparison between at-site Intensity-Duration-Frequency (IDF) curves derived from different remote sensing datasets on corresponding spatial scales, temporal resolutions and records. We analyzed 16 years of homogeneously corrected and gauge-adjusted C-Band weather radar estimates, high-resolution CMORPH and gauge-adjusted high-resolution CMORPH over the Eastern Mediterranean. Results of this study include: (a) good spatial correlation between radar and satellite IDFs ( 0.7 for 2-5 years return period); (b) consistent correlation and dispersion in the raw and gauge adjusted CMORPH; (c) bias is almost uniform with return period for 12-24 h durations; (d) radar identifies thicker tail distributions than CMORPH and the tail of the distributions depends on the spatial and temporal scales. These results demonstrate the potential of remote sensing datasets for rainfall frequency analysis for management (e.g. warning and early-warning systems) and design (e.g. sewer design, large scale drainage planning)

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

NASA Astrophysics Data System (ADS)

Pineda, Luis E.; Willems, Patrick

2017-04-01

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

The canopy interception-landslide initiation conundrum: insight from a tropical secondary forest in northern Thailand

NASA Astrophysics Data System (ADS)

Sidle, Roy C.; Ziegler, Alan D.

2017-01-01

The interception and smoothing effect of forest canopies on pulses of incident rainfall and its delivery to the soil has been suggested as a factor in moderating peak pore water pressure in soil mantles, thus reducing the risk of shallow landslides. Here we provide 3 years of rainfall and throughfall data in a tropical secondary dipterocarp forest characterized by few large trees in northern Thailand, along with selected soil moisture dynamics, to address this issue. Throughfall was an estimated 88 % of rainfall, varying from 86 to 90 % in individual years. Data from 167 events demonstrate that canopy interception was only weakly associated (via a nonlinear relationship) with total event rainfall, but not significantly correlated with duration, mean intensity, or antecedent 2-day precipitation (API2). Mean interception during small events (≤ 35 mm) was 17 % (n = 135 events) compared with only 7 % for large events (> 35 mm; n = 32). Examining small temporal intervals within the largest and highest intensity events that would potentially trigger landslides revealed complex patterns of interception. The tropical forest canopy had little smoothing effect on incident rainfall during the largest events. During events with high peak intensities, high wind speeds, and/or moderate-to-high pre-event wetting, measured throughfall was occasionally higher than rainfall during large event peaks, demonstrating limited buffering. However, in events with little wetting and low-to-moderate wind speed, early event rainfall peaks were buffered by the canopy. As rainfall continued during most large events, there was little difference between rainfall and throughfall depths. A comparison of both rainfall and throughfall depths to conservative mean intensity-duration thresholds for landslide initiation revealed that throughfall exceeded the threshold in 75 % of the events in which rainfall exceeded the threshold for both wet and dry conditions. Throughfall intensity for the 11 largest events (rainfall = 65-116 mm) plotted near or above the intensity-duration threshold for landslide initiation during wet conditions; 5 of the events were near or above the threshold for dry conditions. Soil moisture responses during large events were heavily and progressively buffered at depths of 1 to 2 m, indicating that the timescale of any short-term smoothing of peak rainfall inputs (i.e., ≤ 1 h) has little influence on peak pore water pressure at depths where landslides would initiate in this area. Given these findings, we conclude that canopy interception would have little effect on mitigating shallow landslide initiation during the types of monsoon rainfall conditions in this and similar tropical secondary forest sites.

Monsoon rainfall over India in June and link with northwest tropical pacific - June ISMR and link with northwest tropical pacific

NASA Astrophysics Data System (ADS)

Surendran, Sajani; Gadgil, Sulochana; Rajendran, Kavirajan; Varghese, Stella Jes; Kitoh, Akio

2018-03-01

Recent years have witnessed large interannual variation of all-India rainfall (AIR) in June, with intermittent large deficits and excesses. Variability of June AIR is found to have the strongest link with variation of rainfall over northwest tropical Pacific (NWTP), with AIR deficit (excess) associated with enhancement (suppression) of NWTP rainfall. This association is investigated using high-resolution Meteorological Research Institute model which shows high skill in simulating important features of Asian summer monsoon, its variability and the inverse relationship between NWTP rainfall and AIR. Analysis of the variation of NWTP rainfall shows that it is associated with a change in the latitudinal position of subtropical westerly jet over the region stretching from West of Tibetan Plateau (WTP) to NWTP and the phase of Rossby wave steered in it with centres over NWTP and WTP. In years with large rainfall excess/deficit, the strong link between AIR and NWTP rainfall exists through differences in Rossby wave phase steered in the jet. The positive phase of the WTP-NWTP pattern, with troughs over WTP and west of NWTP, tends to be associated with increased rainfall over NWTP and decreased AIR. This scenario is reversed in the opposite phase. Thus, the teleconnection between NWTP rainfall and AIR is a manifestation of the difference in the phase of Rossby wave between excess and deficit years, with centres over WTP and NWTP. This brings out the importance of prediction of phase of Rossby waves over WTP and NWTP in advance, for prediction of June rainfall over India.

CMIP5 ensemble-based spatial rainfall projection over homogeneous zones of India

NASA Astrophysics Data System (ADS)

Akhter, Javed; Das, Lalu; Deb, Argha

2017-09-01

Performances of the state-of-the-art CMIP5 models in reproducing the spatial rainfall patterns over seven homogeneous rainfall zones of India viz. North Mountainous India (NMI), Northwest India (NWI), North Central India (NCI), Northeast India (NEI), West Peninsular India (WPI), East Peninsular India (EPI) and South Peninsular India (SPI) have been assessed using different conventional performance metrics namely spatial correlation (R), index of agreement (d-index), Nash-Sutcliffe efficiency (NSE), Ratio of RMSE to the standard deviation of the observations (RSR) and mean bias (MB). The results based on these indices revealed that majority of the models are unable to reproduce finer-scaled spatial patterns over most of the zones. Thereafter, four bias correction methods i.e. Scaling, Standardized Reconstruction, Empirical Quantile Mapping and Gamma Quantile Mapping have been applied on GCM simulations to enhance the skills of the GCM projections. It has been found that scaling method compared to other three methods shown its better skill in capturing mean spatial patterns. Multi-model ensemble (MME) comprising 25 numbers of better performing bias corrected (Scaled) GCMs, have been considered for developing future rainfall patterns over seven zones. Models' spread from ensemble mean (uncertainty) has been found to be larger in RCP 8.5 than RCP4.5 ensemble. In general, future rainfall projections from RCP 4.5 and RCP 8.5 revealed an increasing rainfall over seven zones during 2020s, 2050s, and 2080s. The maximum increase has been found over southwestern part of NWI (12-30%), northwestern part of WPI (3-30%), southeastern part of NEI (5-18%) and northern and eastern part of SPI (6-24%). However, the contiguous region comprising by the southeastern part of NCI and northeastern part of EPI, may experience slight decreasing rainfall (about 3%) during 2020s whereas the western part of NMI may also receive around 3% reduction in rainfall during both 2050s and 2080s.

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

Evaluation of quantitative precipitation forecasts by TIGGE ensembles for south China during the presummer rainy season

NASA Astrophysics Data System (ADS)

Huang, Ling; Luo, Yali

2017-08-01

Based on The Observing System Research and Predictability Experiment Interactive Grand Global Ensemble (TIGGE) data set, this study evaluates the ability of global ensemble prediction systems (EPSs) from the European Centre for Medium-Range Weather Forecasts (ECMWF), U.S. National Centers for Environmental Prediction, Japan Meteorological Agency (JMA), Korean Meteorological Administration, and China Meteorological Administration (CMA) to predict presummer rainy season (April-June) precipitation in south China. Evaluation of 5 day forecasts in three seasons (2013-2015) demonstrates the higher skill of probability matching forecasts compared to simple ensemble mean forecasts and shows that the deterministic forecast is a close second. The EPSs overestimate light-to-heavy rainfall (0.1 to 30 mm/12 h) and underestimate heavier rainfall (>30 mm/12 h), with JMA being the worst. By analyzing the synoptic situations predicted by the identified more skillful (ECMWF) and less skillful (JMA and CMA) EPSs and the ensemble sensitivity for four representative cases of torrential rainfall, the transport of warm-moist air into south China by the low-level southwesterly flow, upstream of the torrential rainfall regions, is found to be a key synoptic factor that controls the quantitative precipitation forecast. The results also suggest that prediction of locally produced torrential rainfall is more challenging than prediction of more extensively distributed torrential rainfall. A slight improvement in the performance is obtained by shortening the forecast lead time from 30-36 h to 18-24 h to 6-12 h for the cases with large-scale forcing, but not for the locally produced cases.

Divergent ecological effects of oceanographic anomalies on terrestrial ecosystems of the Mexican Pacific coast

PubMed Central

Caso, Margarita; González-Abraham, Charlotte; Ezcurra, Exequiel

2007-01-01

Precipitation pulses are essential for the regeneration of drylands and have been shown to be related to oceanographic anomalies. However, whereas some studies report increased precipitation in drylands in northern Mexico during El Niño years, others report increased drought in the southern drylands. To elucidate the effect of oceanographic/atmospheric anomalies on moisture pulses along the whole Pacific coast of Mexico, we correlated the average Southern Oscillation Index values with total annual precipitation for 117 weather stations. We also analyzed this relationship for three separate rainfall signals: winter-spring, summer monsoon, and fall precipitation. The results showed a distinct but divergent seasonal pattern: El Niño events tend to bring increased rainfall in the Mexican northwest but tend to increase aridity in the ecosystems of the southern tropical Pacific slope. The analysis for the separated rainfall seasons showed that El Niño conditions produce a marked increase in winter rainfall above 22° latitude, whereas La Niña conditions tend to produce an increase in the summer monsoon-type rainfall that predominates in the tropical south. Because these dryland ecosystems are dependent on rainfall pulses for their renewal, understanding the complex effect of ocean conditions may be critical for their management in the future. Restoration ecology, grazing regimes, carrying capacities, fire risks, and continental runoff into the oceans could be predicted from oceanographic conditions. Monitoring the coupled atmosphere–ocean system may prove to be important in managing and mitigating the effects of large-scale climatic change on coastal drylands in the future. PMID:17563355

Application of a process-based shallow landslide hazard model over a broad area in Central Italy

USGS Publications Warehouse

Gioia, Eleonora; Speranza, Gabriella; Ferretti, Maurizio; Godt, Jonathan W.; Baum, Rex L.; Marincioni, Fausto

2015-01-01

Process-based models are widely used for rainfall-induced shallow landslide forecasting. Previous studies have successfully applied the U.S. Geological Survey’s Transient Rainfall Infiltration and Grid-Based Regional Slope-Stability (TRIGRS) model (Baum et al. 2002) to compute infiltration-driven changes in the hillslopes’ factor of safety on small scales (i.e., tens of square kilometers). Soil data input for such models are difficult to obtain across larger regions. This work describes a novel methodology for the application of TRIGRS over broad areas with relatively uniform hydrogeological properties. The study area is a 550-km2 region in Central Italy covered by post-orogenic Quaternary sediments. Due to the lack of field data, we assigned mechanical and hydrological property values through a statistical analysis based on literature review of soils matching the local lithologies. We calibrated the model using rainfall data from 25 historical rainfall events that triggered landslides. We compared the variation of pressure head and factor of safety with the landslide occurrence to identify the best fitting input conditions. Using calibrated inputs and a soil depth model, we ran TRIGRS for the study area. Receiver operating characteristic (ROC) analysis, comparing the model’s output with a shallow landslide inventory, shows that TRIGRS effectively simulated the instability conditions in the post-orogenic complex during historical rainfall scenarios. The implication of this work is that rainfall-induced landslides over large regions may be predicted by a deterministic model, even where data on geotechnical and hydraulic properties as well as temporal changes in topography or subsurface conditions are not available.

Climate change and the impact of increased rainfall variability on sediment transport and catchment scale water quality

NASA Astrophysics Data System (ADS)

Hancock, G. R.; Willgoose, G. R.; Cohen, S.

2009-12-01

Recently there has been recognition that changing climate will affect rainfall and storm patterns with research directed to examine how the global hydrological cycle will respond to climate change. This study investigates the effect of different rainfall patterns on erosion and resultant water quality for a well studied tropical monsoonal catchment that is undisturbed by Europeans in the Northern Territory, Australia. Water quality has a large affect on a range of aquatic flora and fauna and a significant change in sediment could have impacts on the aquatic ecosystems. There have been several studies of the effect of climate change on rainfall patterns in the study area with projections indicating a significant increase in storm activity. Therefore it is important that the impact of this variability be assessed in terms of catchment hydrology, sediment transport and water quality. Here a numerical model of erosion and hydrology (CAESAR) is used to assess several different rainfall scenarios over a 1000 year modelled period. The results show that that increased rainfall amount and intensity increases sediment transport rates but predicted water quality was variable and non-linear but within the range of measured field data for the catchment and region. Therefore an assessment of sediment transport and water quality is a significant and complex issue that requires further understandings of the role of biophysical feedbacks such as vegetation as well as the role of humans in managing landscapes (i.e. controlled and uncontrolled fire). The study provides a robust methodology for assessing the impact of enhanced climate variability on sediment transport and water quality.

A Summary of Precipitation Characteristics from the 2006–11 Northern Australian Wet Seasons as Revealed by ARM Disdrometer Research Facilities (Darwin, Australia)

DOE PAGES

Giangrande, Scott E.; Bartholomew, Mary Jane; Pope, Mick; ...

2014-05-09

The variability of rainfall and drop size distributions (DSDs) as a function of large-scale atmospheric conditions and storm characteristics is investigated using measurements from the Atmospheric Radiation Measurement (ARM) program facility at Darwin, Australia. Observations are obtained from an impact disdrometer with a near continuous record of operation over five consecutive wet seasons (2006-2011). We partition bulk rainfall characteristics according to diurnal accumulation, convective and stratiform precipitation classifications, objective monsoonal regime and MJO phase. Our findings support previous Darwin studies suggesting a significant diurnal and DSD parameter signal associated with both convective-stratiform and wet season monsoonal regime classification. Negligible MJOmore » phase influence is determined for cumulative disdrometric statistics over the Darwin location.« less

Determining Scale-dependent Patterns in Spatial and Temporal Datasets

NASA Astrophysics Data System (ADS)

Roy, A.; Perfect, E.; Mukerji, T.; Sylvester, L.

2016-12-01

Spatial and temporal datasets of interest to Earth scientists often contain plots of one variable against another, e.g., rainfall magnitude vs. time or fracture aperture vs. spacing. Such data, comprised of distributions of events along a transect / timeline along with their magnitudes, can display persistent or antipersistent trends, as well as random behavior, that may contain signatures of underlying physical processes. Lacunarity is a technique that was originally developed for multiscale analysis of data. In a recent study we showed that lacunarity can be used for revealing changes in scale-dependent patterns in fracture spacing data. Here we present a further improvement in our technique, with lacunarity applied to various non-binary datasets comprised of event spacings and magnitudes. We test our technique on a set of four synthetic datasets, three of which are based on an autoregressive model and have magnitudes at every point along the "timeline" thus representing antipersistent, persistent, and random trends. The fourth dataset is made up of five clusters of events, each containing a set of random magnitudes. The concept of lacunarity ratio, LR, is introduced; this is the lacunarity of a given dataset normalized to the lacunarity of its random counterpart. It is demonstrated that LR can successfully delineate scale-dependent changes in terms of antipersistence and persistence in the synthetic datasets. This technique is then applied to three different types of data: a hundred-year rainfall record from Knoxville, TN, USA, a set of varved sediments from Marca Shale, and a set of fracture aperture and spacing data from NE Mexico. While the rainfall data and varved sediments both appear to be persistent at small scales, at larger scales they both become random. On the other hand, the fracture data shows antipersistence at small scale (within cluster) and random behavior at large scales. Such differences in behavior with respect to scale-dependent changes in antipersistence to random, persistence to random, or otherwise, maybe be related to differences in the physicochemical properties and processes contributing to multiscale datasets.

Significant uncertainty in global scale hydrological modeling from precipitation data errors

NASA Astrophysics Data System (ADS)

Sperna Weiland, Frederiek C.; Vrugt, Jasper A.; van Beek, Rens (L.) P. H.; Weerts, Albrecht H.; Bierkens, Marc F. P.

2015-10-01

In the past decades significant progress has been made in the fitting of hydrologic models to data. Most of this work has focused on simple, CPU-efficient, lumped hydrologic models using discharge, water table depth, soil moisture, or tracer data from relatively small river basins. In this paper, we focus on large-scale hydrologic modeling and analyze the effect of parameter and rainfall data uncertainty on simulated discharge dynamics with the global hydrologic model PCR-GLOBWB. We use three rainfall data products; the CFSR reanalysis, the ERA-Interim reanalysis, and a combined ERA-40 reanalysis and CRU dataset. Parameter uncertainty is derived from Latin Hypercube Sampling (LHS) using monthly discharge data from five of the largest river systems in the world. Our results demonstrate that the default parameterization of PCR-GLOBWB, derived from global datasets, can be improved by calibrating the model against monthly discharge observations. Yet, it is difficult to find a single parameterization of PCR-GLOBWB that works well for all of the five river basins considered herein and shows consistent performance during both the calibration and evaluation period. Still there may be possibilities for regionalization based on catchment similarities. Our simulations illustrate that parameter uncertainty constitutes only a minor part of predictive uncertainty. Thus, the apparent dichotomy between simulations of global-scale hydrologic behavior and actual data cannot be resolved by simply increasing the model complexity of PCR-GLOBWB and resolving sub-grid processes. Instead, it would be more productive to improve the characterization of global rainfall amounts at spatial resolutions of 0.5° and smaller.

Geo-statistical model of Rainfall erosivity by using high temporal resolution precipitation data in Europe

NASA Astrophysics Data System (ADS)

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

2015-04-01

Rainfall erosivity (R-factor) is among the 6 input factors in estimating soil erosion risk by using the empirical Revised Universal Soil Loss Equation (RUSLE). R-factor is a driving force for soil erosion modelling and potentially can be used in flood risk assessments, landslides susceptibility, post-fire damage assessment, application of agricultural management practices and climate change modelling. The rainfall erosivity is extremely difficult to model at large scale (national, European) due to lack of high temporal resolution precipitation data which cover long-time series. In most cases, R-factor is estimated based on empirical equations which take into account precipitation volume. The Rainfall Erosivity Database on the European Scale (REDES) is the output of an extensive data collection of high resolution precipitation data in the 28 Member States of the European Union plus Switzerland taking place during 2013-2014 in collaboration with national meteorological/environmental services. Due to different temporal resolutions of the data (5, 10, 15, 30, 60 minutes), conversion equations have been applied in order to homogenise the database at 30-minutes interval. The 1,541 stations included in REDES have been interpolated using the Gaussian Process Regression (GPR) model using as covariates the climatic data (monthly precipitation, monthly temperature, wettest/driest month) from WorldClim Database, Digital Elevation Model and latitude/longitude. GPR has been selected among other candidate models (GAM, Regression Kriging) due the best performance both in cross validation (R2=0.63) and in fitting dataset (R2=0.72). The highest uncertainty has been noticed in North-western Scotland, North Sweden and Finland due to limited number of stations in REDES. Also, in highlands such as Alpine arch and Pyrenees the diversity of environmental features forced relatively high uncertainty. The rainfall erosivity map of Europe available at 500m resolution plus the standard error and the erosivity density (Rainfall erosivity per mm of precipitation) are available in the European Soil Data Centre (ESDAC). The highest erosivity has been found in the mediterrean countries (Italy, Western Greece, Spain, Northern Portugal), South Austria, Slovenia, Croatia and Western United Kingdom.

Role of Satellite Rainfall Information in Improving Understanding of the Dynamical Link Between the Tropics and Extratropics Prospects of Improved Forecasts of Weather and Short-Term Climate Variability on Sub-Seasonal Time Scales

NASA Technical Reports Server (NTRS)

Hou, Arthur Y.

2002-01-01

The tropics and extratropics are two dynamically distinct regimes. The coupling between these two regimes often defies simple analytical treatment. Progress in understanding of the dynamical interaction between the tropics and extratropics relies on better observational descriptions to guide theoretical development. However, global analyses currently contain significant errors in primary hydrological variables such as precipitation, evaporation, moisture, and clouds, especially in the tropics. Tropical analyses have been shown to be sensitive to parameterized precipitation processes, which are less than perfect, leading to order-one discrepancies between estimates produced by different data assimilation systems. One strategy for improvement is to assimilate rainfall observations to constrain the analysis and reduce uncertainties in variables physically linked to precipitation. At the Data Assimilation Office at the NASA Goddard Space Flight Center, we have been exploring the use of tropical rain rates derived from the TRMM Microwave Imager (TMI) and the Special Sensor Microwave/ Imager (SSM/I) instruments in global data assimilation. Results show that assimilating these data improves not only rainfall and moisture fields but also related climate parameters such as clouds and radiation, as well as the large-scale circulation and short-range forecasts. These studies suggest that assimilation of microwave rainfall observations from space has the potential to significantly improve the quality of 4-D assimilated datasets for climate investigations (Hou et al. 2001). In the next few years, there will be a gradual increase in microwave rain products available from operational and research satellites, culminating to a target constellation of 9 satellites to provide global rain measurements every 3 hours with the proposed Global Precipitation Measurement (GPM) mission in 2007. Continued improvements in assimilation methodology, rainfall error estimates, and model parameterizations are needed to ensure that we derive maximum benefits from these observations.

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.

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.

Statistical characterisation of COSMO Sky-Med X-SAR retrieved precipitation fields by scale-invariance analysis

NASA Astrophysics Data System (ADS)

Deidda, Roberto; Mascaro, Giuseppe; Hellies, Matteo; Baldini, Luca; Roberto, Nicoletta

2013-04-01

COSMO Sky-Med (CSK) is an important programme of the Italian Space Agency aiming at supporting environmental monitoring and management of exogenous, endogenous and anthropogenic risks through X-band Synthetic Aperture Radar (X-SAR) on board of 4 satellites forming a constellation. Most of typical SAR applications are focused on land or ocean observation. However, X-band SAR can be detect precipitation that results in a specific signature caused by the combination of attenuation of surface returns induced by precipitation and enhancement of backscattering determined by the hydrometeors in the SAR resolution volume. Within CSK programme, we conducted an intercomparison between the statistical properties of precipitation fields derived by CSK SARs and those derived by the CNR Polar 55C (C-band) ground based weather radar located in Rome (Italy). This contribution presents main results of this research which was aimed at the robust characterisation of rainfall statistical properties across different scales by means of scale-invariance analysis and multifractal theory. The analysis was performed on a dataset of more two years of precipitation observations collected by the CNR Polar 55C radar and rainfall fields derived from available images collected by the CSK satellites during intense rainfall events. Scale-invariance laws and multifractal properties were detected on the most intense rainfall events derived from the CNR Polar 55C radar for spatial scales from 4 km to 64 km. The analysis on X-SAR retrieved rainfall fields, although based on few images, leaded to similar results and confirmed the existence of scale-invariance and multifractal properties for scales larger than 4 km. These outcomes encourage investigating SAR methodologies for future development of meteo-hydrological forecasting models based on multifractal theory.

Hydroclimatology of the 2008 Midwest floods

NASA Astrophysics Data System (ADS)

Budikova, D.; Coleman, J. S. M.; Strope, S. A.; Austin, A.

2010-12-01

The late spring/early summer flooding that occurred in the American Midwest between May and June 2008 resulted from a combination of large-scale atmospheric circulation patterns that supported a steady influx of moisture into the area. A low pressure system centered over the central-western United States steered a strong jet and associated storms along its eastern edge from the west to southwest and an anomalously strong Great Plains Low Level Jet brought continuous warm and moist air into the area from the Gulf of Mexico into the area. We examine and quantify here the impact these circulation patterns had on the hydroclimatology of the Midwest highlighting the magnitude, frequency, geographic distribution, and temporal evolution of precipitation that ultimately magnified the flooding. Historical precipitation records were used to assess the regional rainfall characteristics at various geographic and time scales. Five distinct hydroclimatic characteristics contributed to the definition of the 2008 flood including persistent high surface soil moisture conditions prior to flooding exasperated by anomalously high rainfall, extreme rainfall totals covering extensive areas, increased frequency of shorter-term, smaller-magnitude events, persistent multiday heavy precipitation events, and extreme flood-producing rain storms. The major flooding lasted for approximately 24 days and most greatly impacted the state of Iowa, southern Wisconsin, and central Indiana. Its occurrence during the May-June period makes the event especially unusual for this region.

Modelling scale-dependent runoff generation in a small semi-arid watershed accounting for rainfall intensity and water depth

USDA-ARS?s Scientific Manuscript database

Observed scale effects of runoff and erosion on hillslopes and small watersheds pose one of the most intriguing challenges to modellers, because it results from complex interactions of time-dependent rainfall input with runoff, infiltration and macro- and microtopographic structures. A little studie...

Biogeochemistry and ecology of terrestrial ecosystems of Amazonia

NASA Astrophysics Data System (ADS)

Malhi, Yadvinder; Davidson, Eric A.

The last decade of research associated with the Large-Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) has led to substantial advances in our understanding of the biogeochemistry and ecology of Amazonian forests and savannas, in particular in relation to the carbon cycle of Amazonia. In this chapter, we present a synthesis of results and ideas that are presented in more detail in subsequent chapters, drawing together evidence from studies of forest ecology, ecophysiology, trace gas fluxes and atmospheric flux towers, large-scale rainfall manipulation experiments and soil surveys, satellite remote sensing, and quantification of carbon and nutrient stocks and flows. The studies have demonstrated the variability of the functioning and biogeochemistry of Amazonian forests at a range of spatial and temporal scales, and they provide clues as to how Amazonia will respond to ongoing direct pressure and global atmospheric change. We conclude by highlighting key questions for the next decade of research to address.

Planting Patterns and Deficit Irrigation Strategies to Improve Wheat Production and Water Use Efficiency under Simulated Rainfall Conditions

PubMed Central

Ali, Shahzad; Xu, Yueyue; Ma, Xiangcheng; Ahmad, Irshad; Kamran, Muhammad; Dong, Zhaoyun; Cai, Tie; Jia, Qianmin; Ren, Xiaolong; Zhang, Peng; Jia, Zhikuan

2017-01-01

The ridge furrow (RF) rainwater harvesting system is an efficient way to enhance rainwater accessibility for crops and increase winter wheat productivity in semi-arid regions. However, the RF system has not been promoted widely in the semi-arid regions, which primarily exist in remote hilly areas. To exploit its efficiency on a large-scale, the RF system needs to be tested at different amounts of simulated precipitation combined with deficit irrigation. Therefore, in during the 2015–16 and 2016–17 winter wheat growing seasons, we examined the effects of two planting patterns: (1) the RF system and (2) traditional flat planting (TF) with three deficit irrigation levels (150, 75, 0 mm) under three simulated rainfall intensity (1: 275, 2: 200, 3: 125 mm), and determined soil water storage profile, evapotranspiration rate, grain filling rate, biomass, grain yield, and net economic return. Over the two study years, the RF treatment with 200 mm simulated rainfall and 150 mm deficit irrigation (RF2150) significantly (P < 0.05) increased soil water storage in the depth of (200 cm); reduced ET at the field scale by 33%; increased total dry matter accumulation per plant; increased the grain-filling rate; and improved biomass (11%) and grain (19%) yields. The RF2150 treatment thus achieved a higher WUE (76%) and RIWP (21%) compared to TF. Grain-filling rates, grain weight of superior and inferior grains, and net economic profit of winter wheat responded positively to simulated rainfall and deficit irrigation under both planting patterns. The 200 mm simulated rainfall amount was more economical than other precipitation amounts, and led to slight increases in soil water storage, total dry matter per plant, and grain yield; there were no significant differences when the simulated rainfall was increased beyond 200 mm. The highest (12,593 Yuan ha−1) net income profit was attained using the RF system at 200 mm rainfall and 150 mm deficit irrigation, which also led to significantly higher grain yield, WUE, and RIWP than all other treatments. Thus, we recommend the RF2150 treatment for higher productivity, income profit, and improve WUE in the dry-land farming system of China. PMID:28878787

Rainfall over the African continent from the 19th through the 21st century

NASA Astrophysics Data System (ADS)

Nicholson, Sharon E.; Funk, Chris; Fink, Andreas H.

2018-06-01

Most of the African continent is semi-arid and hence prone to extreme variations in rainfall from year to year. The extreme droughts that have plagued the Sahel and eastern Africa are particularly well known. This article uses a markedly expanded and updated rainfall data set to examine rainfall variability in 13 sectors that cover most of the continent. Annual rainfall is presented for each sector; the March-to-May and October-November seasons are also examined for equatorial sectors. In each case, the article includes the longest and most comprehensive precipitation gauge series ever published. All time series cover at least a century and most cover roughly one and one-half centuries or more. Although towards the end of the 20th century there was a widespread trend towards more arid conditions, few significant trends are evident over the entire period of record. The largest were downward trends in the Sahel and western sectors of North Africa. In those regions, an abrupt reduction in rainfall occurred around 1968, but a synchronous change occurred many other parts of Africa. A recovery did occur in the Sahel, but to varying degrees across the east-west expanse of the region. Noteworthy is that the west-to-east rainfall gradient across the region appears to have weakened in recent decades. For the continent as a whole, another change began in the 1980s decade, with more arid conditions persisting at the continental scale until early in the twenty-first century. No other such period of dry conditions occurred within the roughly one and one-half centuries evaluated here. A notable change also occurred at the seasonal level. During the period 1980 to 1998 rainfall during March-to-May was well below the long-term mean throughout most of the area from 20° N to 35° S. At the same time rainfall was above the long-term mean in most of eastern sectors within this latitude span, indicating a change in the seasonality of rainfall of a large part of Africa.

Droughts, rainfall and rural water supply in northern Nigeria

NASA Astrophysics Data System (ADS)

Tarhule, Aondover Augustine

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

Statistical downscaling modeling with quantile regression using lasso to estimate extreme rainfall

NASA Astrophysics Data System (ADS)

Santri, Dewi; Wigena, Aji Hamim; Djuraidah, Anik

2016-02-01

Rainfall is one of the climatic elements with high diversity and has many negative impacts especially extreme rainfall. Therefore, there are several methods that required to minimize the damage that may occur. So far, Global circulation models (GCM) are the best method to forecast global climate changes include extreme rainfall. Statistical downscaling (SD) is a technique to develop the relationship between GCM output as a global-scale independent variables and rainfall as a local- scale response variable. Using GCM method will have many difficulties when assessed against observations because GCM has high dimension and multicollinearity between the variables. The common method that used to handle this problem is principal components analysis (PCA) and partial least squares regression. The new method that can be used is lasso. Lasso has advantages in simultaneuosly controlling the variance of the fitted coefficients and performing automatic variable selection. Quantile regression is a method that can be used to detect extreme rainfall in dry and wet extreme. Objective of this study is modeling SD using quantile regression with lasso to predict extreme rainfall in Indramayu. The results showed that the estimation of extreme rainfall (extreme wet in January, February and December) in Indramayu could be predicted properly by the model at quantile 90th.

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

NASA Astrophysics Data System (ADS)

Munoz, Angel G.

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

Using a landslide inventory from online news to evaluate the performance of warning models for rainfall-induced landslides in Italy

NASA Astrophysics Data System (ADS)

Pecoraro, Gaetano; Calvello, Michele

2017-04-01

In Italy rainfall-induced landslides pose a significant and widespread hazard, resulting in a large number of casualties and enormous economic damages. Mitigation of such a diffuse risk cannot be attained with structural measures only. With respect to the risk to life, early warning systems represent a viable and useful tool for landslide risk mitigation over wide areas. Inventories of rainfall-induced landslides are critical to support investigations of where and when landslides have happened and may occur in the future, i.e. to establish reliable correlations between rainfall characteristics and landslide occurrences. In this work a parametric study has been conducted to evaluate the performance of correlation models between rainfall and landslides over the Italian territory using the "FraneItalia" database, an inventory of landslides retrieved from online Italian journalistic news. The information reported for each record of this database always include: the site of occurrence of the landslides, the date of occurrence, the source of the news. Multiple landslides occurring in the same date, within the same province or region, are inventoried together in one single record of the database, in this case also reporting the number of landslides of the event. Each record the database may also include, if the related information is available: hour of occurrence; typology, volume and material of the landslide; activity phase; effects on people, structures, infrastructures, cars or other elements. The database currently contains six complete years of data (2010-2015), including more than 4000 landslide reports, most of them triggered by rainfall. For the aim of this study, different rainfall-landslides correlation models have been tested by analysing the reported landslides, within all the 144 zones identified by the national civil protection for weather-related warnings in Italy, in relation to satellite-based precipitations estimates from the Global Precipitation Measurement (GPM) NASA mission. This remote sensing database contains gridded precipitation and precipitation-error estimates, with a half-hour temporal resolution and a 0.10-degree spatial resolution, covering most of the earth starting from 2014. It is well known that satellite estimates of rainfall have some limitations in resolving specific rainfall features (e.g., shallow orographic events and short-duration, high-intensity events), yet the temporal and spatial accuracy of the GPM data may be considered adequate in relation to the scale of the analysis and the size of the warning zones used for this study. The results of the parametric analysis conducted herein, although providing some indications on the most relevant rainfall conditions leading to widespread landsliding over a warning zone, must be considered preliminary as they show a very heterogeneous behaviour of the employed rainfall-based warning models over the Italian territory. Nevertheless, they clearly show the strong potential of the continuous multi-year landslide records available from the "FraneItalia" database as an important source of information to evaluate the performance of warning models at regional scale throughout Italy.

The distribution of grasslands, savannas and forests in Africa: a new look at the relationships between vegetation, fire and climate at continental scale

NASA Astrophysics Data System (ADS)

D'Onofrio, Donatella; von Hardenberg, Jost; Baudena, Mara

2017-04-01

Savannas occupy about a fifth of the global land surface and store approximately 15% of the terrestrial carbon. They also encompass about 85% of the global land area burnt annually. Along an increasing rainfall gradient, they are the intermediate biome between grassland and forest. Undergoing and predicted increasing temperature and CO2 concentration, modified precipitation regimes, as well as increasing land-use intensity, are expected to induce important shifts in savanna structure and in the distribution of grasslands, savannas and forests. Owing to the large extent and productivity of savanna biomes, these changes could have larger impacts on the global biogeochemical cycle and precipitation than for any other biome, thus influencing the vegetation-climate system. The dynamics of these biomes has been long studied, and the current theory postulates that while arid savannas are observed because of tree-water limitation, and competition with grasses, in mesic conditions savannas persist because a grass-fire feedback exists, which can maintain them as an alternatively stable state to closed forests. This feedback is reinforced by the different responses of savanna and forest tree type. In this context, despite their relevance, grasses and tree types have been studied mostly in small scale ecological studies, while continental analyses focused on total tree cover only. Here we analyze a recent MODIS product including explicitly the non-tree vegetation cover, allowing us to illustrate for the first time at continental scale the importance of grass cover and of tree-fire responses in determining the emergence of the different biomes. We analyze the relationships of woody and herbaceous cover with fire return time (all from MODIS satellite observations), rainfall annual average and seasonality (from TRMM satellite measurements), and we include tree phenology information, based on the ESA Global Land Cover map, also used to exclude areas with large anthropogenic land use. From this analysis we distinctively observe that tropical vegetation dynamics changes along a rainfall gradient more markedly than previously observed, in particular identifying three zones: (i) a dry region, where grasses are dominant and water-limited, and fires are rare; (ii) an intermediate rainfall range, where savanna with grass dominance is the predominant biome, maintained by frequent fires and rainfall seasonality; and (iii) a more humid area, where both savannas and forests can occur, as determined by the grass-fire feedback and the occurrence of different types of trees. The analysis of these important ecological processes can also be applied to the evaluation of Dynamic Global Vegetation Models, that currently have particular difficulties in simulating tropical vegetation.

A study on large-scale nudging effects in regional climate model simulation

NASA Astrophysics Data System (ADS)

Yhang, Yoo-Bin; Hong, Song-You

2011-05-01

The large-scale nudging effects on the East Asian summer monsoon (EASM) are examined using the National Centers for Environmental Prediction (NCEP) Regional Spectral Model (RSM). The NCEP/DOE reanalysis data is used to provide large-scale forcings for RSM simulations, configured with an approximately 50-km grid over East Asia, centered on the Korean peninsula. The RSM with a variant of spectral nudging, that is, the scale selective bias correction (SSBC), is forced by perfect boundary conditions during the summers (June-July-August) from 1979 to 2004. The two summers of 2000 and 2004 are investigated to demonstrate the impact of SSBC on precipitation in detail. It is found that the effect of SSBC on the simulated seasonal precipitation is in general neutral without a discernible advantage. Although errors in large-scale circulation for both 2000 and 2004 are reduced by using the SSBC method, the impact on simulated precipitation is found to be negative in 2000 and positive in 2004 summers. One possible reason for a different effect is that precipitation in the summer of 2004 is characterized by a strong baroclinicity, while precipitation in 2000 is caused by thermodynamic instability. The reduction of convective rainfall over the oceans by the application of the SSBC method seems to play an important role in modeled atmosphere.

Rainfall and Extratropical Transition of Tropical Cyclones: Simulation, Prediction, and Projection

NASA Astrophysics Data System (ADS)

Liu, Maofeng

Rainfall and associated flood hazards are one of the major threats of tropical cyclones (TCs) to coastal and inland regions. The interaction of TCs with extratropical systems can lead to enhanced precipitation over enlarged areas through extratropical transition (ET). To achieve a comprehensive understanding of rainfall and ET associated with TCs, this thesis conducts weather-scale analyses by focusing on individual storms and climate-scale analyses by focusing on seasonal predictability and changing properties of climatology under global warming. The temporal and spatial rainfall evolution of individual storms, including Hurricane Irene (2011), Hurricane Hanna (2008), and Hurricane Sandy (2012), is explored using the Weather Research and Forecast (WRF) model and a variety of hydrometeorological datasets. ET and Orographic mechanism are two key players in the rainfall distribution of Irene over regions experiencing most severe flooding. The change of TC rainfall under global warming is explored with the Forecast-oriented Low Ocean Resolution (FLOR) climate model under representative concentration pathway (RCP) 4.5 scenario. Despite decreased TC frequency, FLOR projects increased landfalling TC rainfall over most regions of eastern United States, highlighting the risk of increased flood hazards. Increased storm rain rate is an important player of increased landfalling TC rainfall. A higher atmospheric resolution version of FLOR (HiFLOR) model projects increased TC rainfall at global scales. The increase of TC intensity and environmental water vapor content scaled by the Clausius-Clapeyron relation are two key factors that explain the projected increase of TC rainfall. Analyses on the simulation, prediction, and projection of the ET activity with FLOR are conducted in the North Atlantic. FLOR model exhibits good skills in simulating many aspects of present-day ET climatology. The 21st-century-projection under RCP4.5 scenario demonstrates the dominant role of ET events on the projected increase of TC frequency in the eastern North Atlantic, highlighting increased exposure of the northeastern United States and Western Europe to storm hazards. Retrospective seasonal forecast experiments demonstrate the skill of HiFLOR in predicting basinwide and regional ET frequency. This skill, however, is not seen in the seasonal prediction of ET rate. More work on the property of signal-to-noise ratio of ET rate is needed.

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

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.

Rainfall-runoff properties of tephra: Simulated effects of grain-size and antecedent rainfall

NASA Astrophysics Data System (ADS)

Jones, Robbie; Thomas, Robert E.; Peakall, Jeff; Manville, Vern

2017-04-01

Rain-triggered lahars (RTLs) are a significant and often persistent secondary volcanic hazard at many volcanoes around the world. Rainfall on unconsolidated volcaniclastic material is the primary initiation mechanism of RTLs: the resultant flows have the potential for large runout distances (> 100 km) and present a substantial hazard to downstream infrastructure and communities. RTLs are frequently anticipated in the aftermath of eruptions, but the pattern, timing and scale of lahars varies on an eruption-by-eruption and even catchment-by-catchment basis. This variability is driven by a set of local factors including the grain size distribution, thickness, stratigraphy and spatial distribution of source material in addition to topography, vegetation coverage and rainfall conditions. These factors are often qualitatively discussed in RTL studies based on post-eruption lahar observations or instrumental detections. Conversely, this study aims to move towards a quantitative assessment of RTL hazard in order to facilitate RTL predictions and forecasts based on constrained rainfall, grain size distribution and isopach data. Calibrated simulated rainfall and laboratory-constructed tephra beds are used within a repeatable experimental set-up to isolate the effects of individual parameters and to examine runoff and infiltration processes from analogous RTL source conditions. Laboratory experiments show that increased antecedent rainfall and finer-grained surface tephra individually increase runoff rates and decrease runoff lag times, while a combination of these factors produces a compound effect. These impacts are driven by increased residual moisture content and decreased permeability due to surface sealing, and have previously been inferred from downstream observations of lahars but not identified at source. Water and sediment transport mechanisms differ based on surface grain size distribution: a fine-grained surface layer displayed airborne remobilisation, accretionary pellet formation, rapid surface sealing and infiltration-excess overland flow generation whilst a coarse surface layer demonstrated exclusively rainsplash-driven particle detachment throughout the rainfall simulations. This experimental protocol has the potential to quantitatively examine the effects of a variety of individual parameters in RTL initiation under controlled conditions.

Regional-scale analysis of extreme precipitation from short and fragmented records

NASA Astrophysics Data System (ADS)

Libertino, Andrea; Allamano, Paola; Laio, Francesco; Claps, Pierluigi

2018-02-01

Rain gauge is the oldest and most accurate instrument for rainfall measurement, able to provide long series of reliable data. However, rain gauge records are often plagued by gaps, spatio-temporal discontinuities and inhomogeneities that could affect their suitability for a statistical assessment of the characteristics of extreme rainfall. Furthermore, the need to discard the shorter series for obtaining robust estimates leads to ignore a significant amount of information which can be essential, especially when large return periods estimates are sought. This work describes a robust statistical framework for dealing with uneven and fragmented rainfall records on a regional spatial domain. The proposed technique, named "patched kriging" allows one to exploit all the information available from the recorded series, independently of their length, to provide extreme rainfall estimates in ungauged areas. The methodology involves the sequential application of the ordinary kriging equations, producing a homogeneous dataset of synthetic series with uniform lengths. In this way, the errors inherent to any regional statistical estimation can be easily represented in the spatial domain and, possibly, corrected. Furthermore, the homogeneity of the obtained series, provides robustness toward local artefacts during the parameter-estimation phase. The application to a case study in the north-western Italy demonstrates the potential of the methodology and provides a significant base for discussing its advantages over previous techniques.

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.

Historical climate controls soil respiration responses to current soil moisture

PubMed Central

Waring, Bonnie G.; Rocca, Jennifer D.; Kivlin, Stephanie N.

2017-01-01

Ecosystem carbon losses from soil microbial respiration are a key component of global carbon cycling, resulting in the transfer of 40–70 Pg carbon from soil to the atmosphere each year. Because these microbial processes can feed back to climate change, understanding respiration responses to environmental factors is necessary for improved projections. We focus on respiration responses to soil moisture, which remain unresolved in ecosystem models. A common assumption of large-scale models is that soil microorganisms respond to moisture in the same way, regardless of location or climate. Here, we show that soil respiration is constrained by historical climate. We find that historical rainfall controls both the moisture dependence and sensitivity of respiration. Moisture sensitivity, defined as the slope of respiration vs. moisture, increased fourfold across a 480-mm rainfall gradient, resulting in twofold greater carbon loss on average in historically wetter soils compared with historically drier soils. The respiration–moisture relationship was resistant to environmental change in field common gardens and field rainfall manipulations, supporting a persistent effect of historical climate on microbial respiration. Based on these results, predicting future carbon cycling with climate change will require an understanding of the spatial variation and temporal lags in microbial responses created by historical rainfall. PMID:28559315

Assessment of groundwater recharge in an ash-fall mantled karst aquifer of southern Italy

NASA Astrophysics Data System (ADS)

Manna, F.; Nimmo, J. R.; De Vita, P.; Allocca, V.

2014-12-01

In southern Italy, Mesozoic carbonate formations, covered by ash-fall pyroclastic soils, are large karst aquifers and major groundwater resources. For these aquifers, even though Allocca et al., 2014 estimated a mean annual groundwater recharge coefficient at regional scale, a more complete understanding of the recharge processes at small spatio-temporal scale is a primary scientific target. In this paper, we study groundwater recharge processes in the Acqua della Madonna test site (Allocca et al., 2008) through the integrated analysis of piezometric levels, rainfall, soil moisture and air temperature data. These were gathered with hourly frequency by a monitoring station in 2008. We applied the Episodic Master Recharge method (Nimmo et al., 2014) to identify episodes of recharge and estimate the Recharge to Precipitation Ratio (RPR) at both the individual-episode and annual time scales. For different episodes of recharge observed, RPR ranges from 97% to 37%, with an annual mean around 73%. This result has been confirmed by a soil water balance and the application of the Thornthwaite-Mather method to estimate actual evapotranspiration. Even though it seems higher than RPRs typical of some parts of the world, it is very close to the mean annual groundwater recharge coefficient estimated at the regional scale for the karst aquifers of southern Italy. In addition, the RPR is affected at the daily scale by both antecedent soil moisture and rainfall intensity, as demonstrated by a statistically significant multiple linear regression among such hydrological variables. In particular, the recharge magnitude is great for low storm intensity and high antecedent soil moisture value. The results advance the comprehension of groundwater recharge processes in karst aquifers, and the sensitivity of RPR to antecedent soil moisture and rainfall intensity facilitates the prediction of the influence of climate and precipitation regime change on the groundwater recharge process.

An experimental method to verify soil conservation by check dams on the Loess Plateau, China.

PubMed

Xu, X Z; Zhang, H W; Wang, G Q; Chen, S C; Dang, W Q

2009-12-01

A successful experiment with a physical model requires necessary conditions of similarity. This study presents an experimental method with a semi-scale physical model. The model is used to monitor and verify soil conservation by check dams in a small watershed on the Loess Plateau of China. During experiments, the model-prototype ratio of geomorphic variables was kept constant under each rainfall event. Consequently, experimental data are available for verification of soil erosion processes in the field and for predicting soil loss in a model watershed with check dams. Thus, it can predict the amount of soil loss in a catchment. This study also mentions four criteria: similarities of watershed geometry, grain size and bare land, Froude number (Fr) for rainfall event, and soil erosion in downscaled models. The efficacy of the proposed method was confirmed using these criteria in two different downscaled model experiments. The B-Model, a large scale model, simulates watershed prototype. The two small scale models, D(a) and D(b), have different erosion rates, but are the same size. These two models simulate hydraulic processes in the B-Model. Experiment results show that while soil loss in the small scale models was converted by multiplying the soil loss scale number, it was very close to that of the B-Model. Obviously, with a semi-scale physical model, experiments are available to verify and predict soil loss in a small watershed area with check dam system on the Loess Plateau, China.

HD Hydrological modelling at catchment scale using rainfall radar observations

NASA Astrophysics Data System (ADS)

Ciampalini Rossano. Ciampalini@Gmail. Com), Rossano; Follain, Stéphane; Raclot, Damien; Crabit, Armand; Pastor, Amandine; Augas, Julien; Moussa, Roger; Colin, François; Le Bissonnais, Yves

2017-04-01

Hydrological simulations at catchment scale repose on the quality and data availability both for soil and rainfall data. Soil data are quite easy to be collected, although their quality depends on the resources devoted to this task, rainfall data observations, instead, need further effort because of their spatiotemporal variability. Rainfalls are normally recorded with rain gauges located in the catchment, they can provide detailed temporal data, but, the representativeness is limited to the point where the data are collected. Combining different gauges in space can provide a better representation of the rainfall event but the spatialization is often the main obstacle to obtain data close to the reality. Since several years, radar observations overcome this gap providing continuous data registration, that, when properly calibrated, can offer an adequate, continuous, cover in space and time for medium-wide catchments. Here, we use radar records for the south of the France on the La Peyne catchment with the protocol there adopted by the national meteo agency, with resolution of 1 km space and 5' time scale observations. We present here the realisation of a model able to perform from rainfall radar observations, continuous hydrological and soil erosion simulations. The model is semi-theoretically based, once it simulates water fluxes (infiltration-excess overland flow, saturation overland flow, infiltration and channel routing) with a cinematic wave using the St. Venant equation on a simplified "bucket" conceptual model for ground water, and, an empirical representation of sediment load as adopted in models such as STREAM-LANDSOIL (Cerdan et al., 2002, Ciampalini et al., 2012). The advantage of this approach is to furnish a dynamic representation - simulation of the rainfall-runoff events more easily than using spatialized rainfalls from meteo stations and to offer a new look on the spatial component of the events.

Seasonal Scale Convective-Stratiform Pricipitation Variabilities at Tropics

NASA Astrophysics Data System (ADS)

S, Sreekanth T.

begin{center} Large Seasonal Scale Convective-Stratiform Pricipitation Variabilities at Tropics Sreekanth T S*, Suby Symon*, G. Mohan Kumar (1) and V Sasi Kumar (2) *Centre for Earth Science Studies, Akkulam, Thiruvananthapuram (1) D-330, Swathi Nagar, West Fort, Thiruvananthapuram 695023 (2) 32. NCC Nagar Peroorkada, Thiruvananthapuram ABSTRACT This study investigates the variabilities of convective and stratiform rainfall from 2011 to 2013 at a tropical coastal station in three seasons viz Pre-Monsoon (March-May), Monsoon (June-September) and Post-Monsoon (October-December). Understanding the climatological variability of these two dominant forms of precipitation and their implications in the total rainfall were the main objectives of this investigation. Variabilities in the frequency & duration of events, rain rate & total number of rain drops distribution in different events and the accumulated amount of rain water were analysed. Based on the ground & radar observations from optical & impact disdrometers, Micro Rain Radar and Atmospheric Electric Field Mill, precipitation events were classified into convective and stratiform in three seasons. Classification was done by the method followed by Testud et al (2001) and as an additional information electrical behaviour of clouds from Atmospheric Electric Field Mill is also used. Events which could not be included in both types were termed as 'mixed precipitation' and were included separately. Diurnal variability of the total rainfall in each seasons were also examined. For both convective and stratiform rainfall there exist distinct day-night differences. During nocturnal hours convective rain draged more attention. In all seasons almost 70% of rain duration and 60% of rain events of convective origin were confined to nocturnal hours. But stratiform rain was not affected by diurnal variations greatly because night time occurrences of stratiform duration and events were less than 50%. Also in Monsoon above 35% of rain duration is from mixed precipitation category.

Latent Heating Retrievals Using the TRMM Precipitation Radar: A Multi-Seasonal Study

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Lang, S.; Meneghini, R.; Halverson, J.; Johnson, R.; Simpson, J.; Einaudi, Franco (Technical Monitor)

2001-01-01

Rainfall is a key link in the hydrologic cycle and is a primary heat source for the atmosphere. The vertical distribution of latent heat release, which is accompanied by rainfall, modulates the large-scale circulations of the tropics and in turn can impact midlatitude weather. This latent heat release is a consequence of phase changes between vapor, liquid, and solid water. Present largescale weather and climate models can simulate latent heat release only crudely, thus reducing their confidence in predictions on both global and regional scales. This paper represents the first attempt to use NASA Tropical Rainfall Measuring Mission (TRMM) rainfall information to estimate the four-dimensional structure of global monthly latent heating profiles over the global tropics from December 1997 to October 2000. The Goddard Convective-Stratiform. Heating (CSH) algorithm and TRMM precipitation radar data are used for this study. We will examine and compare the latent heating structures between 1997-1998 (winter) ENSO and 1998-2000 (non-ENSO). We will also examine over the tropics. The seasonal variation of heating over various geographic locations (i.e., oceanic vs continental; Indian oceans vs west Pacific; Africa vs S. America) will be also examined and compared. In addition, we will examine the relationship between latent heating (max heating level) and SST. The period of interest also coincides with several TRMM field campaigns that recently occurred over the South China Sea in 1998 (SCSMEX), Brazil in 1999 (TRMM-LBA), and in the central Pacific in 1999 (KWAJEX). Sounding diagnosed Q1 budgets from these experiments could provide a means of validating the retrieved profiles of latent heating from the CSH algorithm.

Global Precipitation Patterns Associated with ENSO and Tropical Circulations

NASA Technical Reports Server (NTRS)

Curtis, Scott; Adler, Robert; Huffman, George; Bolvin, David; Nelkin, Eric

1999-01-01

Tropical precipitation and the accompanying latent heat release is the engine that drives the global circulation. An increase or decrease in rainfall in the tropics not only leads to the local effects of flooding or drought, but contributes to changes in the large scale circulation and global climate system. Rainfall in the tropics is highly variable, both seasonally (monsoons) and interannually (ENSO). Two experimental observational data sets, developed under the auspices of the Global Precipitation Climatology Project (GPCP), are used in this study to examine the relationships between global precipitation and ENSO and extreme monsoon events over the past 20 years. The V2x79 monthly product is a globally complete, 2.5 deg x 2.5 deg, satellite-gauge merged data set that covers the period 1979 to the present. Indices based on patterns of satellite-derived rainfall anomalies in the Pacific are used to analyze the teleconnections between ENSO and global precipitation, with emphasis on the monsoon systems. It has been well documented that dry (wet) Asian monsoons accompany warm (cold) ENSO events. However, during the summer seasons of the 1997/98 ENSO the precipitation anomalies were mostly positive over India and the Bay of Bengal, which may be related to an epoch-scale variability in the Asian monsoon circulation. The North American monsoon may be less well linked to ENSO, but a positive precipitation anomaly was observed over Mexico around the September following the 1997/98 event. For the twenty-year record, precipitation and SST patterns in the tropics are analyzed during wet and dry monsoons. For the Asian summer monsoon, positive rainfall anomalies accompany two distinct patterns of tropical precipitation and a warm Indian Ocean. Negative anomalies coincide with a wet Maritime Continent.

Freshwater availability and coastal wetland foundation species: ecological transitions along a rainfall gradient

USGS Publications Warehouse

Osland, Michael J.; Enwright, Nicholas M.; Stagg, Camille L.

2014-01-01

Climate gradient-focused ecological research can provide a foundation for better understanding critical ecological transition points and nonlinear climate-ecological relationships, which is information that can be used to better understand, predict, and manage ecological responses to climate change. In this study, we examined the influence of freshwater availability upon the coverage of foundation plant species in coastal wetlands along a northwestern Gulf of Mexico rainfall gradient. Our research addresses the following three questions: (1) what are the region-scale relationships between measures of freshwater availability (e.g., rainfall, aridity, freshwater inflow, salinity) and the relative abundance of foundation plant species in tidal wetlands; (2) How vulnerable are foundation plant species in tidal wetlands to future changes in freshwater availability; and (3) What is the potential future relative abundance of tidal wetland foundation plant species under alternative climate change scenarios? We developed simple freshwater availability-based models to predict the relative abundance (i.e., coverage) of tidal wetland foundation plant species using climate data (1970-2000), estuarine freshwater inflow-focused data, and coastal wetland habitat data. Our results identify regional ecological thresholds and nonlinear relationships between measures of freshwater availability and the relative abundance of foundation plant species in tidal wetlands. In drier coastal zones, relatively small changes in rainfall could produce comparatively large landscape-scale changes in foundation plant species abundance which would affect some ecosystem good and services. Whereas a drier future would result in a decrease in the coverage of foundation plant species, a wetter future would result in an increase in foundation plant species coverage. In many ways, the freshwater-dependent coastal wetland ecological transitions we observed are analogous to those present in dryland terrestrial ecosystems.

How would peak rainfall intensity affect runoff predictions using conceptual water balance models?

NASA Astrophysics Data System (ADS)

Yu, B.

2015-06-01

Most hydrological models use continuous daily precipitation and potential evapotranspiration for streamflow estimation. With the projected increase in mean surface temperature, hydrological processes are set to intensify irrespective of the underlying changes to the mean precipitation. The effect of an increase in rainfall intensity on the long-term water balance is, however, not adequately accounted for in the commonly used hydrological models. This study follows from a previous comparative analysis of a non-stationary daily series of stream flow of a forested watershed (River Rimbaud) in the French Alps (area = 1.478 km2) (1966-2006). Non-stationarity in the recorded stream flow occurred as a result of a severe wild fire in 1990. Two daily models (AWBM and SimHyd) were initially calibrated for each of three distinct phases in relation to the well documented land disturbance. At the daily and monthly time scales, both models performed satisfactorily with the Nash-Sutcliffe coefficient of efficiency (NSE) varying from 0.77 to 0.92. When aggregated to the annual time scale, both models underestimated the flow by about 22% with a reduced NSE at about 0.71. Exploratory data analysis was undertaken to relate daily peak hourly rainfall intensity to the discrepancy between the observed and modelled daily runoff amount. Preliminary results show that the effect of peak hourly rainfall intensity on runoff prediction is insignificant, and model performance is unlikely to improve when peak daily precipitation is included. Trend analysis indicated that the large decrease of precipitation when daily precipitation amount exceeded 10-20 mm may have contributed greatly to the decrease in stream flow of this forested watershed.

Stochastic Generation of Spatiotemporal Rainfall Events for Flood Risk Assessment

NASA Astrophysics Data System (ADS)

Diederen, D.; Liu, Y.; Gouldby, B.; Diermanse, F.

2017-12-01

Current flood risk analyses that only consider peaks of hydrometeorological forcing variables have limitations regarding their representation of reality. Simplistic assumptions regarding antecedent conditions are required, often different sources of flooding are considered in isolation, and the complex temporal and spatial evolution of the events is not considered. Mid-latitude storms, governed by large scale climatic conditions, often exhibit a high degree of temporal dependency, for example. For sustainable flood risk management, that accounts appropriately for climate change, it is desirable for flood risk analyses to reflect reality more appropriately. Analysis of risk mitigation measures and comparison of their relative performance is therefore likely to be more robust and lead to improved solutions. We provide a new framework for the provision of boundary conditions to flood risk analyses that more appropriately reflects reality. The boundary conditions capture the temporal dependencies of complex storms whilst preserving the extreme values and associated spatial dependencies. We demonstrate the application of this framework to generate a synthetic rainfall events time series boundary condition set from reanalysis rainfall data (CFSR) on the continental scale. We define spatiotemporal clusters of rainfall as events, extract hydrological parameters for each event, generate synthetic parameter sets with a multivariate distribution with a focus on the joint tail probability [Heffernan and Tawn, 2004], and finally create synthetic events from the generated synthetic parameters. We highlight the stochastic integration of (a) spatiotemporal features, e.g. event occurrence intensity over space-time, or time to previous event, which we use for the spatial placement and sequencing of the synthetic events, and (b) value-specific parameters, e.g. peak intensity and event extent. We contrast this to more traditional approaches to highlight the significant improvements in terms of representing the reality of extreme flood events.

Coincident scales of forest feedback on climate and conservation in a diversity hot spot

PubMed Central

Webb, Thomas J; Gaston, Kevin J; Hannah, Lee; Ian Woodward, F

2005-01-01

The dynamic relationship between vegetation and climate is now widely acknowledged. Climate influences the distribution of vegetation; and through a number of feedback mechanisms vegetation affects climate. This implies that land-use changes such as deforestation will have climatic consequences. However, the spatial scales at which such feedbacks occur remain largely unknown. Here, we use a large database of precipitation and tree cover records for an area of the biodiversity-rich Atlantic forest region in south eastern Brazil to investigate the forest–rainfall feedback at a range of spatial scales from ca 101–104 km2. We show that the strength of the feedback increases up to scales of at least 103 km2, with the climate at a particular locality influenced by the pattern of landcover extending over a large area. Thus, smaller forest fragments, even if well protected, may suffer degradation due to the climate responding to land-use change in the surrounding area. Atlantic forest vertebrate taxa also require large areas of forest to support viable populations. Areas of forest of ca 103 km2 would be large enough to support such populations at the same time as minimizing the risk of climatic feedbacks resulting from deforestation. PMID:16608697

Coincident scales of forest feedback on climate and conservation in a diversity hot spot.

PubMed

Webb, Thomas J; Gaston, Kevin J; Hannah, Lee; Ian Woodward, F

2006-03-22

The dynamic relationship between vegetation and climate is now widely acknowledged. Climate influences the distribution of vegetation; and through a number of feedback mechanisms vegetation affects climate. This implies that land-use changes such as deforestation will have climatic consequences. However, the spatial scales at which such feedbacks occur remain largely unknown. Here, we use a large database of precipitation and tree cover records for an area of the biodiversity-rich Atlantic forest region in south eastern Brazil to investigate the forest-rainfall feedback at a range of spatial scales from ca 10(1)-10(4) km2. We show that the strength of the feedback increases up to scales of at least 10(3) km2, with the climate at a particular locality influenced by the pattern of landcover extending over a large area. Thus, smaller forest fragments, even if well protected, may suffer degradation due to the climate responding to land-use change in the surrounding area. Atlantic forest vertebrate taxa also require large areas of forest to support viable populations. Areas of forest of ca 10(3) km2 would be large enough to support such populations at the same time as minimizing the risk of climatic feedbacks resulting from deforestation.

Relationships between Rainy Days, Mean Daily Intensity, and Seasonal Rainfall over the Koyna Catchment during 1961–2005

PubMed Central

Nandargi, S.; Mulye, S. S.

2012-01-01

There are limitations in using monthly rainfall totals in studies of rainfall climatology as well as in hydrological and agricultural investigations. Variations in rainfall may be considered to result from frequency changes in the daily rainfall of the respective regime. In the present study, daily rainfall data of the stations inside the Koyna catchment has been analysed for the period of 1961–2005 to understand the relationship between the rain and rainy days, mean daily intensity (MDI) and seasonal rainfall over the catchment on monthly as well as seasonal scale. Considering the topographical location of the catchment, analysis of seasonal rainfall data of 8 stations suggests that a linear relationship fits better than the logarithmic relationship in the case of seasonal rainfall versus mean daily intensity. So far as seasonal rainfall versus number of rainy days is considered, the logarithmic relationship is found to be better. PMID:22654646

Review and meta-analysis of trends in precipitation regime in Italy

NASA Astrophysics Data System (ADS)

Caporali, Enrica; Chiarello, Valentina; Defina, Ilaria; Fatichi, Simone

2017-04-01

Research to detect changes in climatic variables has become a topic of particular interest to observe signals of climate change as well as to understand drivers of modifications in water resources availability and suggest management adaptations. We specifically focus on Italy, outlining the "state of the art" of the Italian precipitation regime through a review of 46 published studies on rainfall trend analyses. The aim is to combine a large body of knowledge in a single review and to explain the main patterns of rainfall changes occurred in the last decades. The review results are analyzed for the entire Italian peninsula and separately for three macro areas: North, Central and South&Islands. The attention is focused on three indexes at the annual and seasonal scale: mean Total Precipitation (TP), number of Wet Days (WDs) and Precipitation Intensity (PI). Two other aspects are briefly investigated: drought and extreme rainfall events. Different geographic areas, time series length and number of stations, are taken into account using a "weight factor Fi". Subsequently, for each index, findings in terms of increasing or decreasing trends are collected into five principal categories: Negative (N), Negative Significant (NS), Positive (P), Positive Significant (PS), and No Trend (NT). Overall, there is an agreement about the tendency of the WDs that are decreasing on the whole Italy, with some discrepancies regarding the spring and the summer seasons. This is substantially in agreement with the tendency of the TP, especially at annual scale where the presence of a decreasing trend is detected. An opposite behavior is detected for PI, which increases both on an annual and on a seasonal basis. It is worth to point out that PI is analyzed just in few studies and it is strongly influenced on the classification in precipitation intensity intervals. A general finding is that signal to noise ratio on precipitation metrics is quite low, which hampers a clear definition of changes in rainfall occurred in Italy, especially for extreme events the large variability in space and time precludes robust conclusions despite the long-term records available.

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

PubMed

O'Reagain, P J; Scanlan, J C

2013-03-01

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

Anomalies of the Asian Monsoon Induced by Aerosol Forcings

NASA Technical Reports Server (NTRS)

Lau, William K. M.; Kim, M. K.

2004-01-01

Impacts of aerosols on the Asian summer monsoon are studied using the NASA finite volume General Circulation Model (fvGCM), with radiative forcing derived from three-dimensional distributions of five aerosol species i.e., black carbon, organic carbon, soil dust, and sea salt from the Goddard Chemistry Aerosol Radiation and Transport Model (GOCART). Results show that absorbing aerosols, i.e., black carbon and dust, induce large-scale upper-level heating anomaly over the Tibetan Plateau in April and May, ushering in & early onset of the Indian summer monsoon. Absorbing aerosols also I i enhance lower-level heating and anomalous ascent over northern India, intensifying the Indian monsoon. Overall, the aerosol-induced large-scale surface' temperature cooling leads to a reduction of monsoon rainfall over the East Asia continent, and adjacent oceanic regions.

Managment oriented analysis of sediment yield time compression

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

Rainfall characteristics associated to the triggering of fast- and slow-moving landslides - a comparison between the South French Alps and Lower Austria

NASA Astrophysics Data System (ADS)

Remaitre, Alexandre; Wallner, Stefan; Promper, Catrin; Glade, Thomas; Malet, Jean-Philippe

2013-04-01

Rainfall is worldwide a recognized trigger of landslides. Numerous studies were conducted in order to define the relationships between the precipitations and the triggering or the reactivation of landslides. Hydrological triggering of landslides can be divided in three general types: (1) development of local perched water tables in the subsoil leading to shallow slope instabilities and possible gravitational flows, (2) long-lasting rise in permanent water tables leading to more deep-seated slope instabilities, and (3) intense runoff causing channel-bed erosion and debris flows. Types (1) and (3) are usually observed during high rainfall intensities (hourly and daily rainfall) associated to heavy storms; type (2) is usually observed through increasing water content in the subsoil due to antecedent rainfalls (weekly or monthly rainfall) and/or massive snowmelt. Many investigations have been carried out to determine the amount of precipitation needed to trigger slopes failures. For rainfall-induced landslides a threshold may be define the rainfall, soil moisture or hydrological conditions that, when reached or exceeded, are likely to trigger landslides. Usually rainfall thresholds can be defined on physical process-based or conceptual models or empirical, historical and statistical bases. Nevertheless, both the large variety of landslides and to the extreme variety of climatic conditions leading to the triggering or the reactivation of a landslide lead to a regional definition of relationships between landslide occurrence and associated climatic conditions. The purpose of this case study is to analyze the relationships between the triggering of three types of landslides, debris flows, shallow landslides and deep-seated mudslides, and different patterns of rainfall in two study sites with different physiographic and climatic characteristics: the Barcelonnette basin in the South French Alps and the Waidhofen an der Ybbs area in Lower Austria. For this purpose, we exploit for the two test sites a landslide catalogue and rainfall data series to define a typology of rainfall induced-landslides for the relevant landslide types. Results from an analysis of the rainfall conditions associated to these events at different time scale (yearly, monthly, daily and hourly) show a clear distinction between these landslides. Slow-moving landslides are often associated to persistent rainstorms with low intensities during long periods causing the saturation of the soils while fast-moving landslides are usually triggered by short rainfall events with high intensities that occur in summer.

Climate Assessment for 1997.

NASA Astrophysics Data System (ADS)

Bell, Gerald D.; Halpert, Michael S.

1998-05-01

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

Effects of Urban Stormwater Infrastructure and Spatial Scale on Nutrient Export and Runoff from Semi-Arid Urban Catchments

NASA Astrophysics Data System (ADS)

Hale, R. L.; Turnbull, L.; Earl, S.; Grimm, N. B.

2011-12-01

There has been an abundance of literature on the effects of urbanization on downstream ecosystems, particularly due to changes in nutrient inputs as well as hydrology. Less is known, however, about nutrient transport processes and processing in urban watersheds. Engineered drainage systems are likely to play a significant role in controlling the transport of water and nutrients downstream, and variability in these systems within and between cities may lead to differences in the effects of urbanization on downstream ecosystems over time and space. We established a nested stormwater sampling network with 12 watersheds ranging in scale from 5 to 17000 ha in the Indian Bend Wash watershed in Scottsdale, AZ. Small (<200ha) watersheds had uniform land cover (medium density residential), but were drained by a variety of stormwater infrastructure including surface runoff, pipes, natural or modified washes, and retention basins. At the outlet of each of these catchments we monitored rainfall and discharge, and sampled stormwater throughout runoff events for dissolved nitrogen (N), phosphorus (P), and organic carbon (oC). Urban stormwater infrastructure is characterized by a range of hydrologic connectivity. Piped watersheds are highly connected and runoff responds linearly to rainfall events, in contrast to watersheds drained with retention basins and washes, where runoff exhibits a nonlinear threshold response to rainfall events. Nutrient loads from piped watersheds scale linearly with total storm rainfall. Because of frequent flushing, nutrient concentrations from these sites are lower than from wash and retention basin drained sites and total nutrient loads exhibit supply limitation, e.g., nutrient loads are poorly predicted by storm rainfall and are strongly controlled by factors that determine the amount of nutrients stored within the watershed, such as antecedent dry days. In contrast, wash and retention basin-drained watersheds exhibit transport limitation. These watersheds flow less frequently than pipe-drained sites and therefore stormwater has higher concentrations of nutrients, although total loads are significantly lower. Nonlinearities in cross-storm rainfall-nutrient loading relationships for the wash and retention basin watersheds suggest that these systems may become supply limited during large rain events. Results show that characteristics of the hydrologic network such as hydrologic connectivity mediate terrestrial-aquatic linkages. Specifically, we see that increased hydrologic connectivity, as in the piped watershed, actually decreases the predictive power of storm size with regard to nutrient export, whereas nutrient loads from poorly connected watersheds are strongly predicted by storm size.

Indian Monsoon Depression: Climatology and Variability

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

Yoon, Jin-Ho; Huang, Wan-Ru

The monsoon climate is traditionally characterized by large seasonal rainfall and reversal of wind direction (e.g., Krishnamurti 1979). Most importantly this rainfall is the major source of fresh water to various human activities such as agriculture. The Indian subcontinent resides at the core of the Southeast Asian summer monsoon system, with the monsoon trough extended from northern India across Indochina to the Western Tropical Pacific (WTP). Large fraction of annual rainfall occurs during the summer monsoon season, i.e., June - August with two distinct maxima. One is located over the Bay of Bengal with rainfall extending northwestward into eastern andmore » central India, and the other along the west coast of India where the lower level moist wind meets the Western Ghat Mountains (Saha and Bavardeckar 1976). The rest of the Indian subcontinent receives relatively less rainfall. Various weather systems such as tropical cyclones and weak disturbances contribute to monsoon rainfall (Ramage 1971). Among these systems, the most efficient rain-producing system is known as the Indian monsoon depression (hereafter MD). This MD is critical for monsoon rainfall because: (i) it occurs about six times during each summer monsoon season, (ii) it propagates deeply into the continent and produces large amounts of rainfall along its track, and (iii) about half of the monsoon rainfall is contributed to by the MDs (e.g., Krishnamurti 1979). Therefore, understanding various properties of the MD is a key towards comprehending the veracity of the Indian summer monsoon and especially its hydrological process.« less

Understanding the Global Water and Energy Cycle Through Assimilation of Precipitation-Related Observations: Lessons from TRMM and Prospects for GPM

NASA Technical Reports Server (NTRS)

Hou, Arthur; Zhang, Sara; daSilva, Arlindo; Li, Frank; Atlas, Robert (Technical Monitor)

2002-01-01

Understanding the Earth's climate and how it responds to climate perturbations relies on what we know about how atmospheric moisture, clouds, latent heating, and the large-scale circulation vary with changing climatic conditions. The physical process that links these key climate elements is precipitation. Improving the fidelity of precipitation-related fields in global analyses is essential for gaining a better understanding of the global water and energy cycle. In recent years, research and operational use of precipitation observations derived from microwave sensors such as the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager and Special Sensor Microwave/Imager (SSM/I) have shown the tremendous potential of using these data to improve global modeling, data assimilation, and numerical weather prediction. We will give an overview of the benefits of assimilating TRMM and SSM/I rain rates and discuss developmental strategies for using space-based rainfall and rainfall-related observations to improve forecast models and climate datasets in preparation for the proposed multi-national Global Precipitation Mission (GPM).

Climatic trends over Ethiopia: regional signals and drivers

USGS Publications Warehouse

Jury, Mark R.; Funk, Christopher C.

2013-01-01

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

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

Kooperman, Gabriel J.; Pritchard, Michael S.; Burt, Melissa A.

Changes in the character of rainfall are assessed using a holistic set of statistics based on rainfall frequency and amount distributions in climate change experiments with three conventional and superparameterized versions of the Community Atmosphere Model (CAM and SPCAM). Previous work has shown that high-order statistics of present-day rainfall intensity are significantly improved with superparameterization, especially in regions of tropical convection. Globally, the two modeling approaches project a similar future increase in mean rainfall, especially across the Inter-Tropical Convergence Zone (ITCZ) and at high latitudes, but over land, SPCAM predicts a smaller mean change than CAM. Changes in high-order statisticsmore » are similar at high latitudes in the two models but diverge at lower latitudes. In the tropics, SPCAM projects a large intensification of moderate and extreme rain rates in regions of organized convection associated with the Madden Julian Oscillation, ITCZ, monsoons, and tropical waves. In contrast, this signal is missing in all versions of CAM, which are found to be prone to predicting increases in the amount but not intensity of moderate rates. Predictions from SPCAM exhibit a scale-insensitive behavior with little dependence on horizontal resolution for extreme rates, while lower resolution (~2°) versions of CAM are not able to capture the response simulated with higher resolution (~1°). Furthermore, moderate rain rates analyzed by the “amount mode” and “amount median” are found to be especially telling as a diagnostic for evaluating climate model performance and tracing future changes in rainfall statistics to tropical wave modes in SPCAM.« less

Identifying a rainfall event threshold triggering herbicide leaching by preferential flow

NASA Astrophysics Data System (ADS)

McGrath, G. S.; Hinz, C.; Sivapalan, M.; Dressel, J.; Pütz, T.; Vereecken, H.

2010-02-01

How can leaching risk be assessed if the chemical flux and/or the toxicity is highly uncertain? For many strongly sorbing pesticides it is known that their transport through the unsaturated zone occurs intermittently through preferential flow, triggered by significant rainfall events. In these circumstances the timing and frequency of these rainfall events may allow quantification of leaching risk to overcome the limitations of flux prediction. In this paper we analyze the leaching behavior of bromide and two herbicides, methabenzthiazuron and ethidimuron, using data from twelve uncropped lysimeters, with high-resolution climate data, in order to identify the rainfall controls on rapid solute leaching. A regression tree analysis suggested that a coarse-scale fortnightly to monthly water balance was a good predictor of short-term increases in drainage and bromide transport. Significant short-term herbicide leaching, however, was better predicted by the occurrence of a single storm with a depth greater than a 19 mm threshold. Sampling periods where rain events exceeded this threshold accounted for between 38% and 56% of the total mass of herbicides leached during the experiment. The same threshold only accounted for between 1% and 10% of the total mass of bromide leached. On the basis of these results, we conclude that in this system, the leaching risks of strongly sorbing chemicals can be quantified by the timing and frequency of these large rainfall events. Empirical and modeling approaches are suggested to apply this frequentist approach to leaching risk assessment to other soil-climate systems.

Rainfall-runoff model parameter estimation and uncertainty evaluation on small plots

USDA-ARS?s Scientific Manuscript database

Four seasonal rainfall simulations in 2009 and 2010 were applied to a field containing 36 plots (0.75 × 2 m each), resulting in 144 runoff events. In all simulations, a constant rate of rainfall was applied, then halted 60 minutes after initiation of runoff, with plot-scale monitoring of runoff ever...

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

PubMed

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

2017-10-15

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

Regional reduction in paleogroundwater discharge and rainfall in the Late Holocene Yucatan Peninsula reconstructed from trace metals in benthic foraminifera

NASA Astrophysics Data System (ADS)

Broach, K. H.; Chapman, B. L.; Paytan, A.; Street, J.

2017-12-01

As climate change progresses, droughts are predicted to become more common in regions dominated by seasonal precipitation, a problem compounded where precipitation provides significant freshwater resources. The Yucatan Peninsula relies on rain-recharged groundwater for potable water, and regional development due to tourism will further strain supply. Historical and geochemical evidence suggest extensive droughts harmed Mayan Civilization and may again impact the Yucatan in the near future, but proxies around the Yucatan and Caribbean region are complicated by variability and even opposing interpretations. An integrated rainfall signal is needed to smooth variability and separate local aberrations from long-term regional trends that can be used for risk assessment. Here we present a 5,000 year record of rainfall sourced from a broad swath of the peninsula and recorded as trace metal ratios in the foram Ammonia parkinsoniana. Rainwater percolation across the western peninsula forms a groundwater lens that discharges as brackish springs in our field site Celestun Lagoon resulting in trace metal gradients (Li, B, Sr, Ba, Nd) along the lagoon that oscillate with discharge. Sr/Ca and Ba/Ca ratios in the forams suggest a long-term decrease in spring water discharge for the western Yucatan during the last 2,500 years with notable drops coinciding with known droughts (e.g. 800-950 CE) and more variability on a regional scale to 5,000 years. B/Ca ratios appear to depend on proximity to springs and may respond to low-pH discharge water while Nd/Ca ratios suggest sporadic incursions of seawater into the lagoon, possibly related to severely reduced spring water discharge or large hurricane events. We interpret these results to mean that periods of decreased rainfall broadly affect the western peninsula which may pose problems for large population centers like Merida. Future work will focus on periodicity of such rainfall changes and impact on the ecological environment of Celestun Lagoon.

Influence of Kuroshio Oceanic Eddies on North Pacific Weather Patterns

NASA Astrophysics Data System (ADS)

Ma, X.; Chang, P.; Saravanan, R.; Montuoro, R.; Hsieh, J. S.; Wu, D.; Lin, X.; Wu, L.; Jing, Z.

2016-02-01

High-resolution satellite observations reveal energetic meso-scale ocean eddy activity and positive correlation between meso-scale sea surface temperature (SST) and surface wind along oceanic frontal zones, such as the Kuroshio and Gulf Stream, suggesting a potential role of meso-scale oceanic eddies in forcing the atmosphere. Using a 27 km horizontal resolution Weather Research Forecasting (WRF) model forced with observed daily SST at 0.09° spatial resolution during boreal winter season, two ensembles of 10 WRF simulations, in one of which meso-scale SST variability induced by ocean eddies was suppressed, were conducted in the North Pacific to study the local and remote influence of meso-scale oceanic eddies in the Kuroshio Extention Region (KER) on the atmosphere. Suppression of meso-scale oceanic eddies results in a deep tropospheric response along and downstream of the KER, including a significant decrease (increase) in winter season mean rainfall along the KER (west coast of US), a reduction of storm genesis in the KER, and a southward shift of the jet stream and North Pacific storm track in the eastern North Pacific. The simulated local and remote rainfall response to meso-scale oceanic eddies in the KER is also supported by observational analysis. A mechanism invoking moist baroclinic instability is proposed as a plausible explanation for the linkage between meso-scale oceanic eddies in the KER and large-scale atmospheric response in the North Pacific. It is argued that meso-scale oceanic eddies can have a rectified effect on planetary boundary layer moisture, the stability of the lower atmosphere and latent heat release, which in turn affect cyclogenesis. The accumulated effect of the altered storm development downstream further contributes to the equivalent barotropic mean flow change in the eastern North Pacific basin.

Amazon rainforest modulation of water security in the Pantanal wetland.

PubMed

Bergier, Ivan; Assine, Mario L; McGlue, Michael M; Alho, Cleber J R; Silva, Aguinaldo; Guerreiro, Renato L; Carvalho, João C

2018-04-01

The Pantanal is a large wetland mainly located in Brazil, whose natural resources are important for local, regional and global economies. Many human activities in the region rely on Pantanal's ecosystem services including cattle breeding for beef production, professional and touristic fishing, and contemplative tourism. The conservation of natural resources and ecosystems services provided by the Pantanal wetland must consider strategies for water security. We explored precipitation data from 1926 to 2016 provided by a regional network of rain gauge stations managed by the Brazilian Government. A timeseries obtained by dividing the monthly accumulated-rainfall by the number of rainy days indicated a positive trend of the mean rate of rainy days (mm/day) for the studied period in all seasons. We assessed the linkage of Pantanal's rainfall patterns with large-scale climate data in South America provided by NOAA/ESRL from 1949 to 2016. Analysis of spatiotemporal correlation maps indicated that, in agreement with previous studies, the Amazon biome plays a significant role in controlling summer rainfall in the Pantanal. Based on these spatiotemporal maps, a multi-linear regression model was built to predict the mean rate of summer rainy days in Pantanal by 2100, relative to the 1961-1990 mean reference. We found that the deforestation of the Amazon rainforest has profound implications for water security and the conservation of Pantanal's ecosystem services. Copyright © 2017 Elsevier B.V. All rights reserved.

Contrasting watershed-scale trends in runoff and sediment yield complicate rangeland water resources planning

NASA Astrophysics Data System (ADS)

Berg, Matthew D.; Marcantonio, Franco; Allison, Mead A.; McAlister, Jason; Wilcox, Bradford P.; Fox, William E.

2016-06-01

Rangelands cover a large portion of the earth's land surface and are undergoing dramatic landscape changes. At the same time, these ecosystems face increasing expectations to meet growing water supply needs. To address major gaps in our understanding of rangeland hydrologic function, we investigated historical watershed-scale runoff and sediment yield in a dynamic landscape in central Texas, USA. We quantified the relationship between precipitation and runoff and analyzed reservoir sediment cores dated using cesium-137 and lead-210 radioisotopes. Local rainfall and streamflow showed no directional trend over a period of 85 years, resulting in a rainfall-runoff ratio that has been resilient to watershed changes. Reservoir sedimentation rates generally were higher before 1963, but have been much lower and very stable since that time. Our findings suggest that (1) rangeland water yields may be stable over long periods despite dramatic landscape changes while (2) these same landscape changes influence sediment yields that impact downstream reservoir storage. Relying on rangelands to meet water needs demands an understanding of how these dynamic landscapes function and a quantification of the physical processes at work.

Parameter uncertainty and nonstationarity in regional extreme rainfall frequency analysis in Qu River Basin, East China

NASA Astrophysics Data System (ADS)

Zhu, Q.; Xu, Y. P.; Gu, H.

2014-12-01

Traditionally, regional frequency analysis methods were developed for stationary environmental conditions. Nevertheless, recent studies have identified significant changes in hydrological records, leading to the 'death' of stationarity. Besides, uncertainty in hydrological frequency analysis is persistent. This study aims to investigate the impact of one of the most important uncertainty sources, parameter uncertainty, together with nonstationarity, on design rainfall depth in Qu River Basin, East China. A spatial bootstrap is first proposed to analyze the uncertainty of design rainfall depth estimated by regional frequency analysis based on L-moments and estimated on at-site scale. Meanwhile, a method combining the generalized additive models with 30-year moving window is employed to analyze non-stationarity existed in the extreme rainfall regime. The results show that the uncertainties of design rainfall depth with 100-year return period under stationary conditions estimated by regional spatial bootstrap can reach 15.07% and 12.22% with GEV and PE3 respectively. On at-site scale, the uncertainties can reach 17.18% and 15.44% with GEV and PE3 respectively. In non-stationary conditions, the uncertainties of maximum rainfall depth (corresponding to design rainfall depth) with 0.01 annual exceedance probability (corresponding to 100-year return period) are 23.09% and 13.83% with GEV and PE3 respectively. Comparing the 90% confidence interval, the uncertainty of design rainfall depth resulted from parameter uncertainty is less than that from non-stationarity frequency analysis with GEV, however, slightly larger with PE3. This study indicates that the spatial bootstrap can be successfully applied to analyze the uncertainty of design rainfall depth on both regional and at-site scales. And the non-stationary analysis shows that the differences between non-stationary quantiles and their stationary equivalents are important for decision makes of water resources management and risk management.

Varying Influence of Different Forcings on the Indo-Pacific Warm Pool Climate

NASA Astrophysics Data System (ADS)

Mohtadi, M.; Huang, E.; Hollstein, M.; Chen, Y.; Schefuß, E.; Rosenthal, Y.; Prange, M.; Oppo, D.; Liu, J.; Steinke, S.; Martinez-Mendez, G.; Tian, J.; Moffa-Sanchez, P.; Lückge, A.

2017-12-01

Proxy records of rainfall in marine archives from the eastern and western parts of the Indo-Pacific Warm Pool (IPWP) vary at precessional band and suggest a dominant role of orbital forcing by modulating monsoon rainfall and the position of the Inter Tropical Convergence Zone. Rainfall changes recorded in marine archives from the northern South China Sea reveal a more complex history. They are largely consistent with those recorded in the Chinese cave speleothems during glacial periods, but show opposite changes during interglacial peaks that coincide with strong Northern Hemisphere summer insolation maxima. During glacial periods, the establishment of massive Northern Hemisphere ice sheets and the exposure of broad continental shelves in East and Southeast Asia alter the large-scale routes and amounts of water vapor transport onto land relative to interglacials. Precipitation over China during glacials varies at precessional band and is dominated by water vapor transport from the nearby tropical and northwest Pacific, resulting in consistent changes in precipitation over large areas. In the absence of ice forcing during peak interglacials with a strong summer insolation, the low-level southerly monsoonal winds mainly of the Indian Ocean origin penetrate further landward and rainout along their path over China. Subsurface temperatures from the IPWP lack changes on glacial-interglacial timescales but follow the obliquity cycle, and suggest that obliquity-paced climate variations at mid-latitudes remotely control subsurface temperatures in the IPWP. Temperature and rainfall in the IPWP respond primarily to abrupt climate changes in the North Atlantic on millennial timescales, and to ENSO and solar forcing on interannual to decadal timescales. In summary, results from marine records reveal that the IPWP climate is sensitive to changes in spatial and temporal distribution of heat by many types of forcing, the influence of which seems to vary in time and space.

Response of transpiration to rain pulses for two tree species in a semiarid plantation.

PubMed

Chen, Lixin; Zhang, Zhiqiang; Zeppel, Melanie; Liu, Caifeng; Guo, Junting; Zhu, Jinzhao; Zhang, Xuepei; Zhang, Jianjun; Zha, Tonggang

2014-09-01

Responses of transpiration (Ec) to rain pulses are presented for two semiarid tree species in a stand of Pinus tabulaeformis and Robinia pseudoacacia. Our objectives are to investigate (1) the environmental control over the stand transpiration after rainfall by analyzing the effect of vapor pressure deficit (VPD), soil water condition, and rainfall on the post-rainfall Ec development and recovery rate, and (2) the species responses to rain pulses and implications on vegetation coverage under a changing rainfall regime. Results showed that the sensitivity of canopy conductance (Gc) to VPD varied under different incident radiation and soil water conditions, and the two species exhibited the same hydraulic control (-dG c/dlnVPD to Gcref ratio) over transpiration. Strengthened physiological control and low sapwood area of the stand contributed to low Ec. VPD after rainfall significantly influenced the magnitude and time series of post-rainfall stand Ec. The fluctuation of post-rainfall VPD in comparison with the pre-rainfall influenced the Ec recovery. Further, the stand Ec was significantly related to monthly rainfall, but the recovery was independent of the rainfall event size. Ec enhanced with cumulative soil moisture change (ΔVWC) within each dry-wet cycle, yet still was limited in large rainfall months. The two species had different response patterns of post-rainfall Ec recovery. Ec recovery of P. tabulaeformis was influenced by the pre- and post-rainfall VPD differences and the duration of rainless interval. R. pseudoacacia showed a larger immediate post-rainfall Ec increase than P. tabulaeformis did. We, therefore, concluded that concentrated rainfall events do not trigger significant increase of transpiration unless large events penetrate the deep soil and the species differences of Ec in response to pulses of rain may shape the composition of semiarid woodlands under future rainfall regimes.

Mycobiota of biological soil crusts in the Negev desert, Israel - differences on a regional and local scale

NASA Astrophysics Data System (ADS)

Grishkan, I.; Zaady, E.; Kidron, G.

2012-04-01

On a regional scale, we examined variations in microfungal communities inhabiting the biological soil crusts (BSC) and non-crusted soil of the northern and central Negev desert in 10 locations along a southward rainfall gradient (from 325 mm to 81 mm of annual rainfall). A total of 87 species from 49 genera were isolated using the soil dilution plate method. The mycobiota of BSC (80 species) was characterized by dominance of melanin-containing fungi, remarkable contribution of sexual Ascomycota, and low abundance of the typical soil genera Penicillium and Aspergillus. Morphological adaptations to the stressful desert environment were expressed in the prevalence of dark-colored microfungi with large, many-celled spores in the localities of the "drier" part of the rainfall gradient and in dark thick-walled fruit bodies of sexual ascomycetes. The abundance of melanin-containing species with multicellular spores was the only characteristic showed a highly significant (negative) correlation with the rainfall amount. We assume that the main factor influencing the content of these species was the latitudinal position of the locations, determining also the intensity of solar (UV) radiation. In the BSC communities, the xeric "desert" component (melanics, slow-reproducing fungi with large, thick-walled spores) was significantly more pronounced and the mesic "forest" component (Penicillium, fast-reproducing fungi with small, light-colored, and thin-walled spores) was much less represented than in the non-crusted shrub communities. In BSC, density of fungal isolates which can be considered an indirect characteristic of fungal biomass was significantly lower than in the non-crusted soil. Cluster analysis indicated that in most cases, the BSC and shrub localities, separated only by a few meters or less, differed on microfungal community structure much more significantly than BSC or shrub localities in the distance of tens of kilometers. The results of this analysis, together with the fact that the rainfall amount weakly influenced spatial variations of the most observed mycological characteristics, indicated that microenvironmental (edaphic) factors played a more essential role in the formation of studied communities than macroenvironmental (climatic) factors. On a local scale, we studied variations in microfungal communities from different crust types (cyanobacterial - moss-dominated) at the Nizzana research station, the western Negev Desert, and their relationship with moisture retention time and intensity of solar radiation. A total of 78 species from 48 genera was isolated. Microfungal communities in the Nizzana crusts were also dominated by melanin-containing species with large, thick-walled and multi-celled conidia. Abundance of this xeric group significantly increased with the increase of radiation intensity, while abundance of mesic Penicillium spp. and Zygomycota displayed the opposite trend. Density of microfungal isolates showed significant positive non-linear relationship with moisture retention time. The moss dominated crust differed markedly from the cyanobacterial crusts on species relative abundances, diversity level, and isolate density. The study showed the parallelism between structure of crust microfungal communities along a regional precipitation gradient in the Negev desert and within a small drainage basin of the Nizzana research station.

Relative importance of local- and large-scale drivers of alpine soil microarthropod communities.

PubMed

Mitchell, Ruth J; Urpeth, Hannah M; Britton, Andrea J; Black, Helaina; Taylor, Astrid R

2016-11-01

Nitrogen (N) deposition and climate are acknowledged drivers of change in biodiversity and ecosystem function at large scales. However, at a local scale, their impact on functions and community structure of organisms is filtered by drivers like habitat quality and food quality/availability. This study assesses the relative impact of large-scale factors, N deposition and climate (rainfall and temperature), versus local-scale factors of habitat quality and food quality/availability on soil fauna communities at 15 alpine moss-sedge heaths along an N deposition gradient in the UK. Habitat quality and food quality/availability were the primary drivers of microarthropod communities. No direct impacts of N deposition on the microarthropod community were observed, but induced changes in habitat quality (decline in moss cover and depth) and food quality (decreased vegetation C:N) associated with increased N deposition strongly suggest an indirect impact of N. Habitat quality and climate explained variation in the composition of the Oribatida, Mesostigmata, and Collembola communities, while only habitat quality significantly impacted the Prostigmata. Food quality and prey availability were important in explaining the composition of the oribatid and mesostigmatid mite communities, respectively. This study shows that, in alpine habitats, soil microarthropod community structure responds most strongly to local-scale variation in habitat quality and food availability rather than large-scale variation in climate and pollution. However, given the strong links between N deposition and the key habitat quality parameters, we conclude that N deposition indirectly drives changes in the soil microarthropod community, suggesting a mechanism by which large-scale drivers indirectly impacts these functionally important groups.

Why continuous simulation? The role of antecedent moisture in design flood estimation

NASA Astrophysics Data System (ADS)

Pathiraja, S.; Westra, S.; Sharma, A.

2012-06-01

Continuous simulation for design flood estimation is increasingly becoming a viable alternative to traditional event-based methods. The advantage of continuous simulation approaches is that the catchment moisture state prior to the flood-producing rainfall event is implicitly incorporated within the modeling framework, provided the model has been calibrated and validated to produce reasonable simulations. This contrasts with event-based models in which both information about the expected sequence of rainfall and evaporation preceding the flood-producing rainfall event, as well as catchment storage and infiltration properties, are commonly pooled together into a single set of "loss" parameters which require adjustment through the process of calibration. To identify the importance of accounting for antecedent moisture in flood modeling, this paper uses a continuous rainfall-runoff model calibrated to 45 catchments in the Murray-Darling Basin in Australia. Flood peaks derived using the historical daily rainfall record are compared with those derived using resampled daily rainfall, for which the sequencing of wet and dry days preceding the heavy rainfall event is removed. The analysis shows that there is a consistent underestimation of the design flood events when antecedent moisture is not properly simulated, which can be as much as 30% when only 1 or 2 days of antecedent rainfall are considered, compared to 5% when this is extended to 60 days of prior rainfall. These results show that, in general, it is necessary to consider both short-term memory in rainfall associated with synoptic scale dependence, as well as longer-term memory at seasonal or longer time scale variability in order to obtain accurate design flood estimates.

Evaluating Satellite-based Rainfall Estimates for Basin-scale Hydrologic Modeling

NASA Astrophysics Data System (ADS)

Yilmaz, K. K.; Hogue, T. S.; Hsu, K.; Gupta, H. V.; Mahani, S. E.; Sorooshian, S.

2003-12-01

The reliability of any hydrologic simulation and basin outflow prediction effort depends primarily on the rainfall estimates. The problem of estimating rainfall becomes more obvious in basins with scarce or no rain gauges. We present an evaluation of satellite-based rainfall estimates for basin-scale hydrologic modeling with particular interest in ungauged basins. The initial phase of this study focuses on comparison of mean areal rainfall estimates from ground-based rain gauge network, NEXRAD radar Stage-III, and satellite-based PERSIANN (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks) and their influence on hydrologic model simulations over several basins in the U.S. Six-hourly accumulations of the above competing mean areal rainfall estimates are used as input to the Sacramento Soil Moisture Accounting Model. Preliminary experiments for the Leaf River Basin in Mississippi, for the period of March 2000 - June 2002, reveals that seasonality plays an important role in the comparison. There is an overestimation during the summer and underestimation during the winter in satellite-based rainfall with respect to the competing rainfall estimates. The consequence of this result on the hydrologic model is that simulated discharge underestimates the major observed peak discharges during early spring for the basin under study. Future research will entail developing correction procedures, which depend on different factors such as seasonality, geographic location and basin size, for satellite-based rainfall estimates over basins with dense rain gauge network and/or radar coverage. Extension of these correction procedures to satellite-based rainfall estimates over ungauged basins with similar characteristics has the potential for reducing the input uncertainty in ungauged basin modeling efforts.

Rainfall-runoff modelling of the Okavango River catchment to assess impacts of land use change on runoff and downstream ecosystems

NASA Astrophysics Data System (ADS)

Milzow, Christian; Bauer-Gottwein, Peter

2010-05-01

The competition between human water use and ecosystem water use is one of the major challenges for water resources management at the global scale. We analyse the situation for the Okavango River basin of southern Africa. The Okavango River is representative for many large rivers throughout the developing world in that it is ungauged and poorly studied. The Okavango basin - spanning over Angola, Namibia and Botswana - represents a multi-objective problem in an international setting. Economic benefits of agricultural development and conservation of ecosystem services call for opposed actions. A semi-distributed rainfall-runoff model of the Okavango catchment is set up using the Soil and Water Assessment Tool (SWAT). The model is sufficiently physically based to simulate the impact on runoff of extent of agricultural use, crop types and management practices. Precipitation and temperature inputs are taken from datasets covering large parts of the globe. The methodology can thus easily be applied for other ungauged catchments. For temperature we use the ERA-Interim reanalysis product of the European Centre for Medium-Range Weather Forecasts and for precipitation the Famine Early Warning Systems Network data (FEWS-Net). Tropical Rainfall Measurement Mission (TRMM) data resulted in poor model performance compared to the FEWS-Net data. Presently, the upstream catchment in Angola is largely pristine and agriculture is basically restricted to dry land subsistence farming. But economic growth in Angola is likely to result in agricultural development and consequent impacts on catchment runoff. Land use scenarios that are simulated include large scale irrigated agriculture with water extractions from the river and the shallow aquifer. Climate change impacts are also studied and compared to land use change impacts. The downstream part of the basin consists of the large Okavango Wetlands, which are a biodiversity hotspot of global importance and, through tourism, an important source of economic income for Botswana. A second hydrological model simulating flow through the wetlands is used to study the impact of catchment runoff changes on the hydrology and ecology of the wetlands. The final goal of the project is to demonstrate the relation between economic benefits of water abstractions in the upstream and downstream environmental impact. Furthermore the results will provide a basis for defining adequate compensations for upstream stakeholders who forego benefits of agricultural intensification to ensure the conservation of downstream ecosystem services.

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

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

Missing pieces of the puzzle: understanding decadal variability of Sahel Rainfall

NASA Astrophysics Data System (ADS)

Vellinga, Michael; Roberts, Malcolm; Vidale, Pier-Luigi; Mizielinski, Matthew; Demory, Marie-Estelle; Schiemann, Reinhard; Strachan, Jane; Bain, Caroline

2015-04-01

The instrumental record shows that substantial decadal fluctuations affected Sahel rainfall from the West African monsoon throughout the 20th century. Climate models generally underestimate the magnitude of decadal Sahel rainfall changes compared to observations. This shows that the processes that control low-frequency Sahel rainfall change are misrepresented in most CMIP5-era climate models. Reliable climate information of future low-frequency rainfall changes thus remains elusive. Here we identify key processes that control the magnitude of the decadal rainfall recovery in the Sahel since the mid-1980s. We show its sensitivity to model resolution and physics in a suite of experiments with global HadGEM3 model configurations at resolutions between 130-25 km. The decadal rainfall trend increases with resolution and at 60-25 km falls within the observed range. Higher resolution models have stronger increases of moisture supply and of African Easterly wave activity. Easterly waves control the occurrence of strong organised rainfall events which carry most of the decadal trend. Weak rainfall events occur too frequently at all resolutions and at low resolution contribute substantially to the decadal trend. All of this behaviour is seen across CMIP5, including future scenarios. Additional simulations with a global 12km version of HadGEM3 show that treating convection explicitly dramatically improves the properties of Sahel rainfall systems. We conclude that interaction between convective scale and global scale processes is key to decadal rainfall changes in the Sahel. This work is distributed under the Creative Commons Attribution 3.0 Unported License together with an author copyright. This license does not conflict with the regulations of the Crown Copyright.Crown Copyright

Coupling a regional warning system to a semantic engine on online news for enhancing landslide prediction

NASA Astrophysics Data System (ADS)

Battistini, Alessandro; Rosi, Ascanio; Segoni, Samuele; Catani, Filippo; Casagli, Nicola

2017-04-01

Landslide inventories are basic data for large scale landslide modelling, e.g. they are needed to calibrate and validate rainfall thresholds, physically based models and early warning systems. The setting up of landslide inventories with traditional methods (e.g. remote sensing, field surveys and manual retrieval of data from technical reports and local newspapers) is time consuming. The objective of this work is to automatically set up a landslide inventory using a state-of-the art semantic engine based on data mining on online news (Battistini et al., 2013) and to evaluate if the automatically generated inventory can be used to validate a regional scale landslide warning system based on rainfall-thresholds. The semantic engine scanned internet news in real time in a 50 months test period. At the end of the process, an inventory of approximately 900 landslides was set up for the Tuscany region (23,000 km2, Italy). The inventory was compared with the outputs of the regional landslide early warning system based on rainfall thresholds, and a good correspondence was found: e.g. 84% of the events reported in the news is correctly identified by the model. In addition, the cases of not correspondence were forwarded to the rainfall threshold developers, which used these inputs to update some of the thresholds. On the basis of the results obtained, we conclude that automatic validation of landslide models using geolocalized landslide events feedback is possible. The source of data for validation can be obtained directly from the internet channel using an appropriate semantic engine. We also automated the validation procedure, which is based on a comparison between forecasts and reported events. We verified that our approach can be automatically used for a near real time validation of the warning system and for a semi-automatic update of the rainfall thresholds, which could lead to an improvement of the forecasting effectiveness of the warning system. In the near future, the proposed procedure could operate in continuous time and could allow for a periodic update of landslide hazard models and landslide early warning systems with minimum human intervention. References: Battistini, A., Segoni, S., Manzo, G., Catani, F., Casagli, N. (2013). Web data mining for automatic inventory of geohazards at national scale. Applied Geography, 43, 147-158.

Impacts of cloud superparameterization on projected daily rainfall intensity climate changes in multiple versions of the Community Earth System Model

DOE PAGES

Kooperman, Gabriel J.; Pritchard, Michael S.; Burt, Melissa A.; ...

2016-09-26

Changes in the character of rainfall are assessed using a holistic set of statistics based on rainfall frequency and amount distributions in climate change experiments with three conventional and superparameterized versions of the Community Atmosphere Model (CAM and SPCAM). Previous work has shown that high-order statistics of present-day rainfall intensity are significantly improved with superparameterization, especially in regions of tropical convection. Globally, the two modeling approaches project a similar future increase in mean rainfall, especially across the Inter-Tropical Convergence Zone (ITCZ) and at high latitudes, but over land, SPCAM predicts a smaller mean change than CAM. Changes in high-order statisticsmore » are similar at high latitudes in the two models but diverge at lower latitudes. In the tropics, SPCAM projects a large intensification of moderate and extreme rain rates in regions of organized convection associated with the Madden Julian Oscillation, ITCZ, monsoons, and tropical waves. In contrast, this signal is missing in all versions of CAM, which are found to be prone to predicting increases in the amount but not intensity of moderate rates. Predictions from SPCAM exhibit a scale-insensitive behavior with little dependence on horizontal resolution for extreme rates, while lower resolution (~2°) versions of CAM are not able to capture the response simulated with higher resolution (~1°). Furthermore, moderate rain rates analyzed by the “amount mode” and “amount median” are found to be especially telling as a diagnostic for evaluating climate model performance and tracing future changes in rainfall statistics to tropical wave modes in SPCAM.« less

An assessment of Indian monsoon seasonal forecasts and mechanisms underlying monsoon interannual variability in the Met Office GloSea5-GC2 system

NASA Astrophysics Data System (ADS)

Johnson, Stephanie J.; Turner, Andrew; Woolnough, Steven; Martin, Gill; MacLachlan, Craig

2017-03-01

We assess Indian summer monsoon seasonal forecasts in GloSea5-GC2, the Met Office fully coupled subseasonal to seasonal ensemble forecasting system. Using several metrics, GloSea5-GC2 shows similar skill to other state-of-the-art seasonal forecast systems. The prediction skill of the large-scale South Asian monsoon circulation is higher than that of Indian monsoon rainfall. Using multiple linear regression analysis we evaluate relationships between Indian monsoon rainfall and five possible drivers of monsoon interannual variability. Over the time period studied (1992-2011), the El Niño-Southern Oscillation (ENSO) and the Indian Ocean dipole (IOD) are the most important of these drivers in both observations and GloSea5-GC2. Our analysis indicates that ENSO and its teleconnection with Indian rainfall are well represented in GloSea5-GC2. However, the relationship between the IOD and Indian rainfall anomalies is too weak in GloSea5-GC2, which may be limiting the prediction skill of the local monsoon circulation and Indian rainfall. We show that this weak relationship likely results from a coupled mean state bias that limits the impact of anomalous wind forcing on SST variability, resulting in erroneous IOD SST anomalies. Known difficulties in representing convective precipitation over India may also play a role. Since Indian rainfall responds weakly to the IOD, it responds more consistently to ENSO than in observations. Our assessment identifies specific coupled biases that are likely limiting GloSea5-GC2 Indian summer monsoon seasonal prediction skill, providing targets for model improvement.

Response of African humid tropical forests to recent rainfall anomalies

PubMed Central

Asefi-Najafabady, Salvi; Saatchi, Sassan

2013-01-01

During the last decade, strong negative rainfall anomalies resulting from increased sea surface temperature in the tropical Atlantic have caused extensive droughts in rainforests of western Amazonia, exerting persistent effects on the forest canopy. In contrast, there have been no significant impacts on rainforests of West and Central Africa during the same period, despite large-scale droughts and rainfall anomalies during the same period. Using a combination of rainfall observations from meteorological stations from the Climate Research Unit (CRU; 1950–2009) and satellite observations of the Tropical Rainfall Measuring Mission (TRMM; 1998–2010), we show that West and Central Africa experienced strong negative water deficit (WD) anomalies over the last decade, particularly in 2005, 2006 and 2007. These anomalies were a continuation of an increasing drying trend in the region that started in the 1970s. We monitored the response of forests to extreme rainfall anomalies of the past decade by analysing the microwave scatterometer data from QuickSCAT (1999–2009) sensitive to variations in canopy water content and structure. Unlike in Amazonia, we found no significant impacts of extreme WD events on forests of Central Africa, suggesting potential adaptability of these forests to short-term severe droughts. Only forests near the savanna boundary in West Africa and in fragmented landscapes of the northern Congo Basin responded to extreme droughts with widespread canopy disturbance that lasted only during the period of WD. Time-series analyses of CRU and TRMM data show most regions in Central and West Africa experience seasonal or decadal extreme WDs (less than −600 mm). We hypothesize that the long-term historical extreme WDs with gradual drying trends in the 1970s have increased the adaptability of humid tropical forests in Africa to droughts. PMID:23878335

Response of African humid tropical forests to recent rainfall anomalies.

PubMed

Asefi-Najafabady, Salvi; Saatchi, Sassan

2013-01-01

During the last decade, strong negative rainfall anomalies resulting from increased sea surface temperature in the tropical Atlantic have caused extensive droughts in rainforests of western Amazonia, exerting persistent effects on the forest canopy. In contrast, there have been no significant impacts on rainforests of West and Central Africa during the same period, despite large-scale droughts and rainfall anomalies during the same period. Using a combination of rainfall observations from meteorological stations from the Climate Research Unit (CRU; 1950-2009) and satellite observations of the Tropical Rainfall Measuring Mission (TRMM; 1998-2010), we show that West and Central Africa experienced strong negative water deficit (WD) anomalies over the last decade, particularly in 2005, 2006 and 2007. These anomalies were a continuation of an increasing drying trend in the region that started in the 1970s. We monitored the response of forests to extreme rainfall anomalies of the past decade by analysing the microwave scatterometer data from QuickSCAT (1999-2009) sensitive to variations in canopy water content and structure. Unlike in Amazonia, we found no significant impacts of extreme WD events on forests of Central Africa, suggesting potential adaptability of these forests to short-term severe droughts. Only forests near the savanna boundary in West Africa and in fragmented landscapes of the northern Congo Basin responded to extreme droughts with widespread canopy disturbance that lasted only during the period of WD. Time-series analyses of CRU and TRMM data show most regions in Central and West Africa experience seasonal or decadal extreme WDs (less than -600 mm). We hypothesize that the long-term historical extreme WDs with gradual drying trends in the 1970s have increased the adaptability of humid tropical forests in Africa to droughts.