Search

The purpose of this paper is to elucidate a potential use of the large samples of seasonal means that hindcasts provide for investigating different aspects of climate variability. This use of hindcasts complements their traditional uses in bias correction, real-time forecast calibration, and prediction skill assessment. For seasonal hindcast data from NCEP CFSv2 we show that a sample size 5208 for each target season is achievable. To demonstrate the utility of the proposed concept, we use this large sample dataset to illustrate how it could be used in documenting spatial variability in various moments of seasonal mean precipitation PDF over the US, and further, quantify nuances in the variations in precipitation PDF at different geographical locations with the amplitude of ENSO SSTs. It is our hope that analysis presented in this paper will accelerate utilization of seasonal hindcast datasets in furthering our understanding of different aspects of climate variability. With the advantage of the large sample size, we demonstrated that the precipitation PDF at the each grid of the CONUS can be represented by gamma distribution for a more concise and effective way to summarize precipitation variability. The availability of the large sample dataset also allowed us to analyze the statistical characteristic of the precipitation responses to the different amplitudes of ENSO SSTs. The results show that for strong warm events, enhancement in precipitation has larger amplitude than decrease in precipitation for cold events in the regions of Southern California and southeastern US. The variation of the precipitation signal over the other sub-regions including the southwestern US, mid-northwest, and mid-east shows more linear relationship with the ENSO SSTs. In response to anomalous ENSO SSTs, although the PDF of December-January-February seasonal mean precipitation anomaly is shifted from its climatological PDF, there is still a large overlap between precipitation PDFs for ENSO and its climatological counterpart. This uncertainty in seasonal mean outcomes of precipitation, therefore, limits the seasonal prediction skill. [ABSTRACT FROM AUTHOR]

Translating changes in land surface conditions and climate into changes in precipitation, runoff and flood frequencies over a range of catchment scales is a pressing challenge for hydrologic design and flood risk management today. In this paper, we describe a novel approach for modeling areal runoff frequency from heavy-to-extreme precipitation in large urban areas using a simple but general stochastic model for runoff at point scale and bi- and univariate parametric probability distributions for positive point precipitation and areal runoff, respectively. We apply the approach to the Dallas–Fort Worth area using a 22-year historical multisensor precipitation dataset from the National Weather Service to characterize how the different factors that specify the second-order statistics of precipitation, imperviousness and soil water holding capacity at point scale may shape areal runoff frequency, and to assess how changes in precipitation climatology and land surface conditions may change areal runoff frequency as a function of catchment scale and magnitude of precipitation. The results indicate that areal runoff frequency is impacted most significantly by changes in climatological mean and coefficient of variation of positive point precipitation, water holding capacity of soil, imperviousness, and spatial correlation scale of positive point precipitation given the probability of occurrence of heavy-to-extreme precipitation, and that a very small number of low-order statistics of point precipitation may describe areal runoff frequency given the conditional probability distribution models for point precipitation and areal runoff. The approach presented hence offers a parsimonious physically-based alternative to purely numerical approaches based on integrated modeling, or empirical approaches based solely on statistical modeling toward predictive modeling of areal precipitation and runoff frequencies under changing hydroclimatological conditions. [ABSTRACT FROM AUTHOR]

This paper examines an asymmetric spatiotemporal connection and climatic impact between the winter atmospheric blocking activity in the Euro-Atlantic sector and the life cycle of the North Atlantic Oscillation (NAO) during the period 1950-2012. Results show that, for positive NAO (NAO+) events, the instantaneous blocking (IB) frequency exhibits an enhancement along the southwest-northeast (SW-NE) direction from the eastern Atlantic to northeastern Europe (SW-NE pattern, hereafter), which is particularly evident during the NAO+ decaying stage. By contrast, for negative NAO (NAO−) events, the IB frequency exhibits a spatially asymmetric southeast-northwest (SE-NW) distribution from central Europe to the North Atlantic and Greenland (SE-NW pattern, hereafter). Moreover, for NAO− (NAO+) events, the most marked decrease (increase) in the surface air temperature (SAT) in winter over northern Europe is in the decaying stage. For NAO+ events, the dominant positive temperature and precipitation anomalies exhibit the SW-NE-oriented distribution from western to northeastern Europe, which is parallel to the NAO+-related blocking frequency distribution. For NAO- events, the dominant negative temperature anomaly is in northern and central Europe, whereas the dominant positive precipitation anomaly is distributed over southern Europe along the SW-NE direction. In addition, the downward infrared radiation controlled by the NAO’s circulation plays a crucial role in the SAT anomaly distribution. It is further shown that the NAO’s phase can act as an asymmetric impact on the European climate through producing this asymmetric spatiotemporal connection with the Euro-Atlantic IB frequency. [ABSTRACT FROM AUTHOR]

Global Climate Models (GCMs) have been extensively used in many climate change impact studies. However, the coarser resolution of these GCM outputs is not adequate to assess the potential effects of climate change on local scale. Downscaling techniques have thus been proposed to resolve this problem either by dynamical or statistical approaches. The statistical downscaling (SD) methods are widely privileged because of their simplicity of implementation and use. However, many of them ignore the observed spatial dependence between different locations, which significantly affects the impact study results. An improved multi-site SD approach is thus presented in this paper to downscaling of daily precipitation at many sites concurrently. This approach is based on a combination of multiple regression models for rainfall occurrences and amounts and the Singular Value Decomposition technique, which models the stochastic components of these regression models to preserve accurately the space-time statistical properties of the daily precipitation. Furthermore, this method was able to describe adequately the intermittency property of the precipitation processes. The proposed approach has been assessed using 10 rain gauges located in the southwest region of Quebec and southeast region of Ontario in Canada, and climate predictors from the National Centers for Environmental Prediction/National Centre for Atmospheric Research re-analysis data set. The results have indicated the ability of the proposed approach to reproduce accurately multiple observed statistical properties of the precipitation occurrences and amounts, the at-site temporal persistence, the spatial dependence between sites and the temporal variability and spatial intermittency of the precipitation processes. [ABSTRACT FROM AUTHOR]

The Arctic cell as a reversed and closed loop next to the Polar cell has been recently revealed in the Northern Hemisphere (NH). In this paper, we study the interannual variability of the Arctic and Polar cell strengths during 1979-2012, and their influence on surface air temperature (SAT), precipitation, and sea-ice concentration (SIC) at mid- and high-latitudes of the NH. We show that there is a significant negative correlation between the Arctic and Polar cell strengths. Both the Arctic and Polar cell strengths can well indicate the recurring climatic anomalies of SAT, precipitation, and SIC in their extreme winters. The surface large-scale cold-warm and dry-wet anomalous patterns in these extreme winters are directly linked with the vertical structure of height and temperature anomalies in the troposphere. Results suggest that the past climatic anomalies are better indicated by the strength anomalies of the Polar and Arctic cells than the traditional indices of mid-high latitude pattern such as the Arctic Oscillation and North Atlantic Oscillation. This study illustrates a three-dimensional picture of atmospheric variable anomalies in the troposphere that result in surface climatic anomalies. [ABSTRACT FROM AUTHOR]

The Eastern Mediterranean region has been exposed to drought episodes, which have been occurring more frequently during the last decades. The objective of the present paper is to study the precipitation regime of the Damascus (Mazzeh) meteoric station by analysing drought characteristics using the Standardized Precipitation Index (SPI) and comparing this with the drought in Cyprus. The cumulative drought conceptis proposed to characterize long-term hydrologic drought, which affects the shallow groundwater productivity in terms of quantity and quality. Gamma probability distribution was fitted to the long-term annual precipitation in Damascus from 1918-1919 to 2007-2008 ( n = 90 years). Generally, a decreasing trend of 17% to the mean annual rainfall of Damascus and 13% to the mean annual rainfall of Cyprus was estimated between 1970 and 2000. The SPI identifies three major extended drought periods: (1) 9 years of severe drought (1954-1963) with an average 20% precipitation deficit per year compared to the mean. (2) 8 years of severe drought (1983-1991) with a 27% deficit per year on average. (3) 9 years of extreme drought (1993-2002) with a 31% deficit per year on average. The cumulative standardized precipitation index (SPI 30) demonstrates positive values for the first period and is indicative of having no effect on the global water balance. SPI 30 exhibits sensitive equilibrium with near zero values / a near zero value (±1.5) for the second period. For the third period, however, the SPI 30 decreases below −10 indicating an extreme hydrological drought that has negative consequences on the recent groundwater recharge. It is required to develop and implement a sustainable groundwater management strategy to reduce long-terms drought risks. Generally, the SPI 30 in Cyprus is parallel to that in Damascus with a 3-5 year delay. Thus, the central zone of the Eastern Mediterranean region is facing big challenges and has been suffering from three decades of moderate to severe hydrological drought (SPI 30=−5 to −10) causing a severe decrease in springs discharges of the region. Therefore, in order to reduce the climate change effects on water resources, it is necessary to adopt a sustainable proactive management plan during the frequent severe droughts. [ABSTRACT FROM AUTHOR]

Statistical downscaling (SD) methods have become a popular, low-cost and accessible means of bridging the gap between the coarse spatial resolution at which climate models output climate scenarios and the finer spatial scale at which impact modellers require these scenarios, with various different SD techniques used for a wide range of applications across the world. This paper compares the Generator for Point Climate Change (GPCC) model and the Statistical DownScaling Model (SDSM)-two contrasting SD methods-in terms of their ability to generate precipitation series under non-stationary conditions across ten contrasting global climates. The mean, maximum and a selection of distribution statistics as well as the cumulative frequencies of dry and wet spells for four different temporal resolutions were compared between the models and the observed series for a validation period. Results indicate that both methods can generate daily precipitation series that generally closely mirror observed series for a wide range of non-stationary climates. However, GPCC tends to overestimate higher precipitation amounts, whilst SDSM tends to underestimate these. This infers that GPCC is more likely to overestimate the effects of precipitation on a given impact sector, whilst SDSM is likely to underestimate the effects. GPCC performs better than SDSM in reproducing wet and dry day frequency, which is a key advantage for many impact sectors. Overall, the mixed performance of the two methods illustrates the importance of users performing a thorough validation in order to determine the influence of simulated precipitation on their chosen impact sector. [ABSTRACT FROM AUTHOR]

The Andes Cordillera plays a role in driving moisture and heat from tropical onto subtropical South America. It forces the development of a lee-side trough that covers most of western Argentina and a low-level jet that maximizes over Paraguay, eastern Bolivia and northern Argentina and is tightly linked to precipitation variability over much of central and southeastern South America. Its steep slopes and the large zonal gradients in topography between the Equator and 40°S are misrepresented in climate simulations using Global Climate Models (GCM) with resolutions coarser than about 100 km, since they naturally have a poor representation of the Andes and related circulation features. This paper analyses the impact of varying artificially the altitude of the Andes Cordillera in a GCM as well as increasing the horizontal resolution to study how these variations determine moisture fluxes and precipitation over selected regions of South America. Results show that the height of the Andes is crucial in shaping moisture fluxes pathways onto subtropical South America all year long. In particular, the low-level jet is only simulated when the Andes heights are doubled. At the same time, the relationship between the Andes shape and the location of the Bolivian High in summer is also discussed. In terms of precipitation, the lowest bias in the simulations is achieved when the horizontal resolution is increased, while in particular near the Andes foothills the simulated annual rainfall is largely determined by the Mountains shape. [ABSTRACT FROM AUTHOR]