Spatio-temporal Precipitation Patterns Research Articles

Precipitation patterns and associated hydrological extremes in the Yangtze River basin, China, using TRMM/PR data and EOF analysis

A decadal-scale study to retrieve the spatio-temporal precipitation patterns of the Yangtze River basin, China, using the Tropical Rain Mapping Mission, Precipitation Radar (TRMM/PR) data is presented. The empirical orthogonal function (EOF) based on monthly TRMM/PR data extracts several leading precipitation patterns, which are largely connected with physical implications at the basin scale. With the aid of gauge station data, the amplitudes of major principal components (PCs) were used to examine the generic relationships between precipitation variations and hydrological extremes (e.g. floods and droughts) during summer seasons over the past decade. The emergence of such major precipitation patterns clearly reveals the possible linkages with hydrological processes, and the oscillations in relation to the amplitude of major PCs are consistent with these observed hydrological extremes. Although the floods in some sections of the Yangtze River were, to some extent, tied to human activities, such as the removal of wetlands, the variations in major precipitation patterns are recognized as the primary driving force of the flow extremes associated with floods and droughts. The research findings indicate that long-distance hydro-meteorological signals of large-scale precipitation variations over such a large river basin can be successfully identified with the aid of EOF analysis. The retrieved precipitation patterns and their low-frequency jumps of amplitude in relation to PCs are valuable tools to help understand the association between the precipitation variations and the occurrence of hydrological extremes. Such a study can certainly aid in disaster mitigation and decision-making in water resource management. Editor Z.W. Kundzewicz; Associate editor A. Montanari Citation Sun, Z., Chang, N.-B., Huang, Q., and Opp, C., 2013. Precipitation patterns and associated hydrological extremes in the Yangtze River basin, China, using TRMM/PR data and EOF analysis. Hydrological Sciences Journal, 57 (7), 1315–1324.

Runoff conditions in the upper Danube basin under an ensemble of climate change scenarios

► Evaluation of hydrological runoff simulations with 120 years of historic data. ► Usage of a large ensemble of regional climate models to address uncertainty in climate projections. ► Assessment of range in future runoff conditions until the end of the 21st century. Runoff conditions are strongly controlled by climate. Therefore, any uncertainties in the projections about future climate directly translate to uncertainties in future runoff. If several climate models are applied with the same emission scenario, there may be large differences in the climate projections due to model related biases and natural climate variability. To address this issue, an ensemble modelling approach – which considers a set of climate models – is applied in this study with a monthly, conceptual hydrological model for assessing future runoff conditions in the upper Danube basin (101,810 km 2 ). Observed data of the past 120 years of the HISTALP data-set are used to evaluate runoff simulations under historic climate variations as well as to test the delta-change method for bias correction of climate data. Uncertainties caused by the hydrological model or by the method for bias correction appear to be small. Projections about future climate are obtained from 21 regional climate models (RCMs) of the ENSEMBLES project for the A1B emission scenario. Evaluation and ranking of the RCMs reveals that some of the models have considerable biases in simulation of spatio-temporal patterns of historic precipitation and temperature. There is however, no systematic relationship between historic performance and projected future change. Even for the better performing RCMs the differences in the simulation results are large. This is a strong argument for using an ensemble modelling approach, which yields a range of future runoff conditions instead of a deterministic projection. In general, a strong decrease of summer runoff is simulated, whereas there is no clear signal for changes in winter runoff. The spread between different RCMs in future seasonal runoff is larger than for the monthly flow duration curve. Overall, the projected changes in future runoff conditions become more pronounced towards the end of the 21st century.

Climatic trends and different drought adaptive capacity and vulnerability in a mixed Abies pinsapo–Pinus halepensis forest

The projected temperature rise, rainfall decrease and concentration of rainfall in extreme events could induce growth decline and die-off on tree populations located at the geographical distribution limit of the species. Understanding of adaptive capacity and regional vulnerability to climate change in Mediterranean forests is not well developed and requires more focused research efforts. We studied the relationships between spatiotemporal patterns of temperature and precipitation along the southwestern edge of the Betic range (southern Spain) and measured basal area increment (BAI) and carbon isotope (Δ) in tree ring series of Abies pinsapo and Pinus halepensis, two Mediterranean conifer trees with contrasting drought adaptive capacity. Climatic information was obtained from a network covering a wide range of elevations and distances from the Atlantic and Mediterranean coasts. Temperature trends were tested by the Mann–Kendall test, and precipitation was thoroughly analyzed by quantile regression. Climatic data showed a warming trend, enhanced since the 1970s, while quantile regressions revealed that drought events worsened during the course of the twentieth century. Long-term decrease of A. pinsapo BAI was related to regional warming and changing precipitation patterns, suggesting increasing drought stress on this species. Both temperature and precipitation in the summer influenced wood Δ in P. halepensis, whereas negative correlation between wood Δ and current autumn temperature was yielded for A. pinsapo. Increased intrinsic water use efficiency was inferred from wood Δ in both species; however, A. pinsapo showed sudden growth reductions under drier conditions, while pine trees were able to maintain almost constant BAI values and lower water costs under increasing long-term water stress.

Spatiotemporal Variability of Precipitation, Modeled Soil Moisture, and Vegetation Greenness in North America within the Recent Observational Record

Abstract Dominant spatiotemporal patterns of precipitation, modeled soil moisture, and vegetation are determined in North America within the recent observational record (late twentieth century onward). These data are from a gridded U.S.–Mexico precipitation product, retrospective long-term integrations of two land surface models, and satellite-derived vegetation greenness. The analysis procedure uses three statistical techniques. First, all the variables are normalized according to the standardized precipitation index procedure. Second, dominant patterns of spatiotemporal variability are determined using multitaper method–singular value decomposition for interannual and longer time scales. The dominant spatiotemporal patterns of precipitation generally conform to known and distinct Pacific SST forcing in the cool and warm seasons. Two specific time scales in precipitation at 9 and 6–7 yr correspond to significant variability in soil moisture and vegetation, respectively. The 9-yr signal is related to precipitation in late fall to early winter, whereas the 6–7-yr signal is related to earlysummer precipitation. Canonical correlation analysis is finally used to confirm that strong covariability between land surface variables and precipitation exists at these specific times of the year. Both signals are strongest in the central and western United States and are consistent with prior global modeling and paleoclimate studies that have investigated drought in North America.

Regional Simulation of Summertime Precipitation over the Southwestern United States

Using results taken from a finescale (25 km), regional modeling simulation for the summer of 1999, along with contemporaneous daily surface observations, synoptic variations in summertime precipitation over the southwestern United States are described and analyzed. Two separate techniques for characterizing and evaluating large-scale summertime precipitation patterns within the observed and simulated systems are presented; in addition, these evaluation/characterization techniques are used to analyze the hydrologic forcings associated with observed and simulated modes of rainfall variability. Overall, two robust spatiotemporal precipitation patterns are identified involving 1) precipitation over the western portion of the Rocky Mountain plateau centered on eastern Arizona and southern Utah, and 2) precipitation located over the eastern portion of the plateau and the elevated orography of eastern New Mexico and southern Colorado. Time series associated with these two precipitation regimes are correlated with low-level and midlevel circulation patterns in order to investigate the related large-scale environmental conditions. It is found that for both regimes intraseasonal precipitation is related to the intrusion of midtroposphere, midlatitude low-pressure anomalies over the southwestern United States, resulting in synoptic-scale shifts in the position of the climatological midtroposphere monsoon ridge. The interaction between the resultant midtroposphere pressure fields and the quasi-stationary monsoon surface pressures found over the Rocky Mountain plateau during the summertime produce large-scale vertical velocities consistent with the observed and simulated rainfall patterns associated with each regime.

Regional Simulation of Intraseasonal Variations in the Summertime Hydrologic Cycle over the Southwestern United States

Abstract Using results taken from a finescale (25 km) regional modeling simulation for the summer of 1999, intraseasonal variations in the climatological summertime hydrologic cycle over the southwestern United States are described for two previously identified spatiotemporal precipitation patterns. Over the western portion of the Rocky Mountain plateau, centered on eastern Utah and western Colorado, columnar moisture divergence associated with precipitation is balanced by a combination of seasonal-mean convective moisture convergence and anomalous upper-air (>4 km) large-scale moisture convergence. The actual precipitating events themselves are predicated upon the anomalous upper-level advection of water vapor into the precipitating region; absent this large-scale advection at upper levels, vertical diffusion of moisture into the atmosphere balances large-scale divergence at midlevels, with little precipitation occurring. The anomalous large-scale advection during precipitating events is due primarily to...

Quantifying the agricultural landscape and assessing spatio-temporal patterns of precipitation and groundwater use

Quantitative agricultural landscape indices are useful to describe functional relationships among climatic conditions, groundwater dynamics, soil properties and agricultural land use for mathematical models. We applied methods of regression statistics, variance component estimation and a Geographical Information System (GIS) to construct indices describing crops and soils and to establish functional relationships among these variables. This paper describes the development of indices and the partitioning of the spatial and temporal variation in groundwater models using the data from Tulare County, California, which was selected as the study area. Indices of ground surface elevation, total crop water demand, soil water infiltration rate, and soil production index explain 91% of the variation in average spring groundwater level. After relating spatial patterns of groundwater use to indices of crop and soil properties, we found that mean groundwater use is positively related to total crop water demand and soil water infiltration rate while the variation in groundwater use was negatively correlated with the crop water demand and soil water infiltration rate and positively related to soil water holding capacity. The spatial variation in groundwater use was largely influenced by crops and soil types while the temporal variation was not. We also found that groundwater use increased exponentially with decreasing annual precipitation for most townships. Based on these associations, groundwater use in each township can be forecast from relative precipitation under current methods of agricultural production. Although groundwater table depth is strongly affected by topography, the statistically significant indices observed in the model clearly show that agricultural land use influences groundwater table depth. These simple relationships can be used by agronomists to make water management decisions and to design alternative cropping systems to sustain agricultural production during periods of surface water shortages.