High Precipitation Variability Research Articles

Responses of riparian tetragnathid spiders to wildfire in forested ecosystems of the California Mediterranean climate region, USA

Mediterranean ecosystems of California are characterized by high interannual variability in precipitation and susceptibility to frequent high-severity wildfires. Variability in precipitation and fire severity are likely to become more pronounced because of climate change, but their relative effects on linked aquatic–terrestrial components of Mediterranean ecosystems have received limited attention. We investigated the effects of wildfire on riparian spiders of the family Tetragnathidae, which are common shoreline consumers that can be highly reliant on aquatic food resources in stream ecosystems. From 2011–2012, we assessed stream geomorphology; density and community composition of aquatic benthic macroinvertebrates; and density, Hg body loads, trophic position (TP), and reliance on aquatically derived energy (based on naturally abundant C and N isotopes) of tetragnathid spiders in study sections of 12 paired stream reaches in Yosemite National Park. The riparian zone of one member of each pair had experienced a high-severity wildfire, whereas the riparian zone of its counterpart had experienced a low-severity fire. After the 2013 Rim Fire, we resurveyed a subset of these variables in study sections of 4 reaches by means of a paired before-after–control-impact design. We also explored how reach- and catchment-scale variability might affect spider density and trophic dynamics. Differences in spider responses between paired sections were not statistically significant, but model-selection results suggested that variability in benthic invertebrate density, catchment-scale fire frequency, and precipitation were important drivers of spider density and TP. The consistent signal of precipitation across multiple spider responses suggests that climate variability could have greater effects on aquatic–terrestrial ecological linkages than the influence of fire alone.

Evolutionary drivers of mast-seeding in a long-lived desert shrub.

The evolutionary drivers and proximal regulators of mast-seeding are well understood for species of mesic environments, but how these regulators interact with high spatial and interannual variability in growing-season precipitation for a masting species in a desert environment has never been examined. We followed flowering and seed production in 16 populations of the North American desert shrub blackbrush (Coleogyne ramosissima) from contrasting environments across its range over an 11-year period to determine patterns of interannual reproductive output variation. Patterns of reproductive output in blackbrush did not track current growing season precipitation, but instead were regulated by prior-year weather cues. The strength of the response to the masting cue depended on habitat quality, with higher mean reproductive output, shorter intervals between years of high seed production, and lower CVp at more favorable sites. Wind pollination efficiency was demonstrated to be an important evolutionary driver of masting in blackbrush, and satiation of heteromyid seed predator-dispersers was supported as an evolutionary driver based on earlier studies. Both the evolutionary drivers and proximal regulators of masting in blackbrush are similar to those demonstrated for masting species of mesic environments. Relatively low synchrony across populations in response to regional masting cues occurs at least partly because prior-year environmental cues can trigger masting efforts in years with resource limitation due to suboptimal precipitation, especially in more xeric low-elevation habitats.

Entropy‐based spatiotemporal patterns of precipitation regimes in the Huai River basin, China

ABSTRACTSpatiotemporal patterns of precipitation regimes in terms of precipitation amount and number of precipitation days at different time scales are investigated using the entropy‐based methodologies in the Huai River basin, China. Trends of precipitation variability are quantitatively evaluated using the modified Mann–Kendall trend test method. Correlations between the largest 7‐day precipitation amount (R × 7day) and precipitation variability within 1 year are also analysed. Results indicate the following: (1) there is increasing nonuniformity of annual precipitation amount and annual precipitation days from south to north in the Huai River basin, indicating larger precipitation variability in the northern parts. Transition of precipitation changes is evident in the basin which is reflected by decreasing precipitation variability in the north and increasing precipitation variability in the south. (2) The disorder indices (DIs) exhibit variations at different time scales. In general, precipitation variability is larger at shorter time scales, such as daily, and is smaller at longer time scales, such as annual. (3) Significant relations are identified between the DI and extreme precipitation events, i.e. significant relations between apportionment DI and the largest 7‐day precipitation amount and it is particularly the case in the central and southwestern parts. Thus, it can be said that higher precipitation variability is due to higher frequency of extreme precipitation regimes. Results of this study are of practical significance for planning and management of water resources and agricultural irrigation and agricultural activities during climate change and particularly for enhancement of measures for mitigation of consequences of climate change.

Evaluation of the TMPA-3B42 precipitation product using a high-density rain gauge network over complex terrain in northeastern Iberia

The performance of the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA)-3B42 version 7 product is assessed over north-eastern Iberia, a region with considerable topographical gradients and complexity. Precipitation characteristics from a dense network of 656 rain gauges, spanning the period from 1998 to 2009, are used to evaluate TMPA-3B42 estimates on a daily scale. A set of accuracy estimators, including the relative bias, mean absolute error (MAE), root mean square error (RMSE) and Spearman coefficient was used to evaluate the results. The assessment indicates that TMPA-3B42 product is capable of describing the seasonal characteristics of the observed precipitation over most of the study domain. In particular, TMPA-3B42 precipitation agrees well with in situ measurements, with MAE less than 2.5mm.day−1, RMSE of 6.4mm.day−1 and Spearman correlation coefficients generally above 0.6. TMPA-3B42 provides improved accuracies in winter and summer, whereas it performs much worse in spring and autumn. Spatially, the retrieval errors show a consistent trend, with a general overestimation in regions of low altitude and underestimation in regions of heterogeneous terrain. TMPA-3B42 generally performs well over inland areas, while showing less skill in the coastal regions. A set of skill metrics, including a false alarm ratio [FAR], frequency bias index [FBI], the probability of detection [POD] and threat score [TS], is also used to evaluate TMPA performance under different precipitation thresholds (1, 5, 10, 25 and 50mm.day−1). The results suggest that TMPA-3B42 retrievals perform well in specifying moderate rain events (5–25mm.day−1), but show noticeably less skill in producing both light (<1mm.day−1) and heavy rainfall thresholds (more than 50mm.day−1). Given the complexity of the terrain and the associated high spatial variability of precipitation in north-eastern Iberia, the results reveal that TMPA-3B42 data provide an informative addition to the spatial and temporal coverage of rain gauges in the domain, offering insights into characteristics of average precipitation and their spatial patterns. However, the satellite-based precipitation data should be used cautiously for monitoring extreme precipitation events, particularly over complex terrain. An improvement in precipitation algorithms is still needed to more accurately reproduce high precipitation events in areas of heterogeneous topography over this region.

Impacts of climate change on precipitation and discharge extremes through the use of statistical downscaling approaches in a Mediterranean basin

Mediterranean region is characterized by high precipitation variability often enhanced by orography, with strong seasonality and large inter-annual fluctuations, and by high heterogeneity of terrain and land surface properties. As a consequence, catchments in this area are often prone to the occurrence of hydrometeorological extremes, including storms, floods and flash-floods. A number of climate studies focused in the Mediterranean region predict that extreme events will occur with higher intensity and frequency, thus requiring further analyses to assess their effect at the land surface, particularly in small- and medium-sized watersheds. In this study, climate and hydrologic simulations produced within the Climate Induced Changes on the Hydrology of Mediterranean Basins (CLIMB) EU FP7 research project were used to analyze how precipitation extremes propagate into discharge extremes in the Rio Mannu basin (472.5km2), located in Sardinia, Italy. The basin hydrologic response to climate forcings in a reference (1971–2000) and a future (2041–2070) period was simulated through the combined use of a set of global and regional climate models, statistical downscaling techniques, and a process based distributed hydrologic model. We analyzed and compared the distribution of annual maxima extracted from hourly and daily precipitation and peak discharge time series, simulated by the hydrologic model under climate forcing. For this aim, yearly maxima were fit by the Generalized Extreme Value (GEV) distribution using a regional approach. Next, we discussed commonality and contrasting behaviors of precipitation and discharge maxima distributions to better understand how hydrological transformations impact propagation of extremes. Finally, we show how rainfall statistical downscaling algorithms produce more reliable forcings for hydrological models than coarse climate model outputs.

Ecosystem functional assessment based on the “optical type” concept and self-similarity patterns: An application using MODIS-NDVI time series autocorrelation

Remote sensing (RS) time series are an excellent operative source for information about the land surface across several scales and different levels of landscape heterogeneity. Ustin and Gamon (2010) proposed the new concept of “optical types” (OT), meaning “optically distinguishable functional types”, as a way to better understand remote sensing signals related to the actual functional behavior of species that share common physiognomic forms but differ in functionality. Whereas the OT approach seems to be promising and consistent with ecological theory as a way to monitor vegetation derived from RS, it received little implementation.This work presents a method for implementing the OT concept for efficient monitoring of ecosystems based on RS time series. We propose relying on an ecosystem's repetitive pattern in the temporal domain (self-similarity) to assess its dynamics. Based on this approach, our main hypothesis is that distinct dynamics are intrinsic to a specific OT. Self-similarity level in the temporal domain within a broadleaf forest class was quantitatively assessed using the auto-correlation function (ACF), from statistical time series analysis. A vector comparison classification method, spectral angle mapper, and principal component analysis were used to identify general patterns related to forest dynamics. Phenological metrics derived from MODIS NDVI time series using the TIMESAT software, together with information from the National Forest Map were used to explain the different dynamics found.Results showed significant and highly stable self-similarity patterns in OTs that corresponded to forests under non-moisture-limited environments with an adaptation strategy based on a strong phenological synchrony with climate seasonality. These forests are characterized by dense closed canopy deciduous forests associated with high productivity and low biodiversity in terms of dominant species. Forests in transitional areas were associated with patterns of less temporal stability probably due to mixtures of different adaptation strategies (i.e., deciduous, marcescent and evergreen species) and higher functional diversity related to climate variability at long and short terms. A less distinct seasonality and even a double season appear in the OT of the broadleaf Mediterranean forest characterized by an open canopy dominated by evergreen-sclerophyllous formations. Within this forest, understory and overstory dynamics maximize functional diversity resulting in contrasting traits adapted to summer drought, winter frosts, and high precipitation variability.

Predicting long-term change of groundwater level with regional climate model in South Korea

Global climate change causes a high variability in precipitation and surface temperature increase in the world. Global climate models (GCMs) are effectively used to predict climate change at a global scale. In contrast, regional climate models (RCMs) can more efficiently predict climate change scenarios for a small territory such as South Korea. We estimated the groundwater level change in four drainage basins (the Han River, Nakdong River, Geum River, and Yeongsan-Sumjin River basins) in South Korea over the period 2000–2012, and then predicted the groundwater level change from 2000 to 2100 using a water budget model, considering RCMs with RCP 4.5 and RCP 8.5 scenarios. A distinct trend in the groundwater levels of each drainage basin was detected via the inversely close relationship with precipitation patterns of the drainage basin, showing a decrease in the groundwater level in relation to the increasing precipitation trend of the RCM scenarios. It is also proposed that the precipitation amount during the dry season more dominantly affects groundwater recharge than during the wet season.

Spatio-temporal characteristics of precipitation and drought in Balochistan Province, Pakistan

In this paper, spatial and temporal variability of drought in Balochistan has been investigated using 36 years (1975–2010) of monthly precipitation data recorded at 23 rain gauge stations in the study area. In order to detect and understand precipitation trend on drought severity, Mann–Kendall test is used. Standardized precipitation index is used to compute the severity of drought. Inverse distance weighted method has been used to illustrate the spatial and temporal aspects of drought with varying intensities. In addition, perception and understanding of the 215 farm households about drought are assessed following an in-depth field survey. The results reveal that farmers’ perception regarding climatic variability and drought are in line with the results obtained using the secondary climatic data and information. Mann–Kendall test results indicate that negative trends in precipitation are evident for both annual and seasonal scale for more than 70 % of the stations in Balochistan ranging from 137.2 to 283.4 mm over 36 years, which may affect the drought mitigation, local water resources management and agriculture decision making. Furthermore, frequency of severe and extreme droughts is higher in north-west, from central parts towards south, south-east and some coastal areas when analysed quarterly at 3-month winter season and annually for 12-month dry–wet periods. Central-eastern, south-western, southern and some isolated coastal areas in the south are more susceptible to severe droughts particularly during winter and dry–wet periods because of high variability in precipitation in these areas.

Extreme Precipitation Changes in the Semiarid Region of Xinjiang, Northwest China

This study focuses on extreme precipitation changes in Xinjiang Province of Northwest China, which has experienced an increase in climate disasters in recent years. This paper investigates extreme precipitation events in Xinjiang, using 54 stations with daily precipitation records from the period 1961–2008. Different statistical tests and approaches were used to check the significance of trends of single and Xinjiang regionally aggregated precipitation series for intensity and in frequency. There were predominantly positive trends in annual maximum precipitation and a remarkable increment in the frequency of extreme precipitation over certain thresholds (from 10 to 40 mm). Although the series of frequencies exceeding thresholds had positive trends, only a minority were statistically significant. This lack of significance is because of the high variability of extreme precipitation in space and time. Thus, significant trends were evident when we assessed the extreme precipitation indicators of intensity and frequency at the regional level, both in intensity and frequency over thresholds, with a clearer signal in Xinjiang.

Future projections of extreme precipitation using Advanced Weather Generator (AWE-GEN) over Peninsular Malaysia

Abstract. A stochastic downscaling methodology known as the Advanced Weather Generator, AWE-GEN, has been tested at four stations in Peninsular Malaysia using observations available from 1975 to 2005. The methodology involves a stochastic downscaling procedure based on a Bayesian approach. Climate statistics from a multi-model ensemble of General Circulation Model (GCM) outputs were calculated and factors of change were derived to produce the probability distribution functions (PDF). New parameters were obtained to project future climate time series. A multi-model ensemble was used in this study. The projections of extreme precipitation were based on the RCP 6.0 scenario (2081–2100). The model was able to simulate both hourly and 24-h extreme precipitation, as well as wet spell durations quite well for almost all regions. However, the performance of GCM models varies significantly in all regions showing high variability of monthly precipitation for both observed and future periods. The extreme precipitation for both hourly and 24-h seems to increase in future, while extreme of wet spells remain unchanged, up to the return periods of 10–40 years.

Exploring landscape sensitivity to the Pacific Trade Wind Inversion on the subsiding island of Hawaii

AbstractThe interaction of the subsiding limb of the Hadley circulation and the easterly North Pacific Trade Winds establishes a persistent thermal inversion at about 2000 m above sea level in the subtropical Pacific. The inversion restricts convective rainfall to the lower elevations of the windward flank of the island of Hawaii, creating an order‐of‐magnitude vertical rainfall gradient, as well as high interbasin variability in precipitation. In the high‐rainfall zone, streams are incised tens to hundreds of meters below the surface of the volcanic shield. We use a digital elevation model and 1‐D numerical modeling to assess whether deep incision on the flank of Mauna Kea is tied to the elevation of the trade wind inversion. The 83 channels examined can be well fit in aggregate by all models that account for differences in precipitation between basins; specifically, the maximum depth of incision in each drainage is a power function of precipitation‐weighted drainage area with an exponent of ~ ½. Individual longitudinal stream profiles are generally better fit by models that acknowledge both along‐channel precipitation variability and the subsidence of the island through that gradient, but this relationship is not clearly demonstrable for many channels. We argue that island subsidence through the dry‐to‐wet precipitation gradient has resulted in less cumulative discharge in the lower reaches of the drainages over their lifetime, relative to a nonsubsiding case. This reduces differential erosion between the wet and dry reaches by 20–30% over 300 kyr, making the longitudinal profiles less sensitive to the very strong climate gradient.

Biotic mechanisms of community stability shift along a precipitation gradient.

Understanding how biotic mechanisms confer stability in variable environments is a fundamental quest in ecology, and one that is becoming increasingly urgent with global change. Several mechanisms, notably a portfolio effect associated with species richness, compensatory dynamics generated by negative species covariance and selection for stable dominant species populations can increase the stability of the overall community. While the importance of these mechanisms is debated, few studies have contrasted their importance in an environmental context. We analyzed nine long-term data sets of grassland species composition to investigate how two key environmental factors, precipitation amount and variability, may directly influence community stability and how they may indirectly influence stability via biotic mechanisms. We found that the importance of stability mechanisms varied along the environmental gradient: strong negative species covariance occurred in sites characterized by high precipitation variability, whereas portfolio effects increased in sites with high mean annual precipitation. Instead of questioning whether compensatory dynamics are important in nature, our findings suggest that debate should widen to include several stability mechanisms and how these mechanisms vary in importance across environmental gradients.

Seasonal and regional biases in CMIP5 precipitation simulations

CR Climate Research Contact the journal Facebook Twitter RSS Mailing List Subscribe to our mailing list via Mailchimp HomeLatest VolumeAbout the JournalEditorsSpecials CR 60:35-50 (2014) - DOI: https://doi.org/10.3354/cr01221 Seasonal and regional biases in CMIP5 precipitation simulations Zhu Liu1, Ali Mehran1, Thomas J. Phillips2, Amir AghaKouchak1,* 1University of California Irvine, E4130 Engineering Gateway, Irvine, California 92697-2175, USA 2Lawrence Livermore National Laboratory, 7000 East Avenue, Livermore, California 94550, USA *Corresponding author: amir.a@uci.edu ABSTRACT: This study provides insight into how CMIP5 climate models perform in simulating summer and winter precipitation at different geographical locations and climate conditions. Precipitation biases in the CMIP5 historical (1901 to 2005) simulations relative to the Climatic Research Unit (CRU) observations are evaluated over 8 regions exhibiting distinct seasonal hydroclimates: moist tropical (Amazonia and central Africa), monsoonal (southern China), moist continental (central Europe), semi-arid (western United States and eastern Australia), and polar (Siberia and Canada). While the bias and monthly quantile bias (MQB) reflect no substantial differences in CMIP5 summer and winter precipitation simulations at the global scale, strong seasonality and high inter-model variability are found over the selected moist tropical regions (i.e. Amazonia and central Africa). In the semi-arid regions, high inter-model precipitation variability is also displayed, especially in summer, while the median of simulations is an overestimate of both winter and summer precipitation. In Siberia and central Europe, most CMIP5 models underestimate summer precipitation, and overestimate it in winter. Also, the MQB values decrease as the choice of quantile thresholds increase, implying that the underestimation of summer precipitation is primarily associated with biases in lower quantiles of the precipitation distribution. While the CMIP5 models exhibit similar behaviors in simulating high-latitude winter precipitation, they differ substantially in summer simulations for the selected Canadian and Siberian regions. Finally, in the monsoonal southern China region, CMIP5 models exhibit large overall precipitation biases in both summer and winter, as well as at higher quantiles. KEY WORDS: Precipitation · Climate · CMIP5 Full text in pdf format Supplementary material PreviousNextCite this article as: Liu Z, Mehran A, Phillips TJ, AghaKouchak A (2014) Seasonal and regional biases in CMIP5 precipitation simulations. Clim Res 60:35-50. https://doi.org/10.3354/cr01221 Export citation RSS - Facebook - Tweet - linkedIn Cited by Published in CR Vol. 60, No. 1. Online publication date: May 19, 2014 Print ISSN: 0936-577X; Online ISSN: 1616-1572 Copyright © 2014 Inter-Research.

Genetically based latitudinal variation in Artemisia californica secondary chemistry

Steep climatic gradients may select for clinal adaptation in plant functional traits with implications for interspecific interactions and response to future climate change. Terpenes are common in Mediterranean environments and mediate plant interactions with both the abiotic and biotic environment, including herbivores. Clines in traits such as terpenes have received much attention because they are linked to plant fitness and experience strong selection from the abiotic and biotic environment. In this study, we tested for intraspecific variation in Artemisia californica terpene chemistry in a common garden of plants sourced from populations spanning a large precipitation gradient (6° latitude) and grown in treatments of high and low precipitation. We found genetic variation in terpene richness, diversity, concentration and composition among A. californica populations spanning this species’ range. Of these traits, terpene composition and monoterpene concentration varied clinally with respect to source site latitude. Regarding terpene composition, pairwise dissimilarity among populations increased in parallel with geographic distance between source sites. At the same time, monoterpene concentration decreased monotonically from plants of southern origin (source sites with high temperature, aridity, and precipitation variability) to plants of northern origin. Our precipitation manipulation suggests that phenotypic selection by precipitation may underlie this clinal variation in monoterpene concentration, and that monoterpene concentration and other aspects of terpene chemistry are not phenotypically plastic. In summary, this study provides novel evidence for a genetically based latitudinal cline in plant secondary chemistry and suggests that adaptation to a key aspect of the abiotic environment may contribute to this intraspecific variation. Accordingly, changes in terpene chemistry under projected future climates will likely occur solely through the relatively slow process of adaptation, with important consequences for plant interactions with the abiotic environment and a diverse community of associates.

Improving AVSWAT Stream Flow Simulation by Incorporating Groundwater Recharge Prediction in the Upstream Lesti Watershed, East Java, Indonesia

The upstream Lesti watershed is one of the major watersheds of East Java in Indonesia, covering about 38093 hectares. Although there are enough water resources to meet current demands in the basin, many challenges including high spatial and temporal variability in precipitation from year to year exist. It is essential to understand how the climatic condition affects Lesti River stream flow in each sub basin. This study investigated the applicability of using the Soil and Water Assessment Tool (SWAT) with the incorporation of groundwater recharge prediction in stream flow simulation in the upstream Lesti watershed. Four observation wells in the upstream Lesti watershed were used to evaluate the seasonal and annual variations in the water level and estimate the groundwater recharge in the deep aquifer. The results show that annual water level rise was within the 2800-5700 mm range in 2007, 3900-4700 mm in 2008, 3200-5100 mm in 2009, and 2800-4600 mm in 2010. Based on the specific yield and the measured water level rise, the area-weighted groundwater predictions at the watershed outlet are 736, 820.9, 786.7, 306.4 mm in 2007, 2008, 2009, and 2010, respectively. The consistency test reveals that the R-square statistical value is greater than 0.7, and the DV (%) ranged from 32-55.3% in 2007-2010. Overall, the SWAT model performs better in the wet season flow simulation than the dry season. It is suggested that the SWAT model needs to be improved for stream flow simulation in tropical regions.

The Dynamics of Concentration of Selected Chemical Components of Rainfalls in the Miedzyzdroje

The development of a business man and also growing up processes the transformative environment adversely affect the individual elements of the natural environment. These processes they realize that individual elements of environmental protection becomes the basis for the further development of socio-economic background. In recent years the increasing pollution of the atmosphere causes more and more interest in the science of the substances contained in it and merge back to the surface of the Earth. Of great importance for the environment have the substances contained in the water drainage, as in the form of dissolved very easily reach the individual environmental elements causing their contamination. Research was carried out in the years 2008-2011 (January-December) in the town of Międzyzdroje. In the tests was measured the amount of precipitation, chemical composition (NH4+, NO3-, PO43-- ions were numbered), pH and conductivity. Międzyzdroje is a city located in the north-western part of the county on the island of Wolin on the Baltic Sea. The city is located on the Bay of Pomorska, in the central part of the coast of the island of Wolin. Part of the East of Międzyzdroje is situated on the western slopes of the remains of the Beautiful. The climate of the island of Wolin is different from the rest of the country because the climate is strongly influenced by the presence of the Baltic Sea. It is characterized by high humidity, sunlight and precipitation variability, wind direction and force large diurnal temperature amplitude. Międzyzdroje is a resort and tourist destination.

From pointwise testing to a regional vision: An integrated statistical approach to detect nonstationarity in extreme daily rainfall. Application to the Sahelian region

Global warming is expected to intensify the hydrologic cycle. Documenting whether significant changes in the extreme precipitation regimes have already happened is consequently one of the challenging topics in climatic research. The high natural variability of extreme precipitation often prevents from obtaining significant results when testing changes in the empirical distribution of extreme rainfall at regional scale. A regional integrated approach is proposed here as one possible answer to this complex methodological problem. Three methods are combined in order to detect regionally significant trends and/or breakpoints in series of annual maximum daily rainfall: (1) individual stationarity tests applied to the raw point series of maxima, (2) a maximum likelihood testing of time‐dependent generalized extreme value (GEV) distributions fitted to these series, and (3) a heuristic testing of a regional time‐dependent GEV distribution. This approach is applied to a set of 126 daily rain gauges covering the Sahel over the period 1950–1990. It is found that only a few stations are tested as nonstationary when applying classical tests on the raw series, while the two GEV‐based models converge to show that the extreme rainfall series indeed underwent a negative breakpoint around 1970. The study evidences the limits of the widely used classical stationarity tests to detect trends in noisy series affected by sampling uncertainties, while using a parametric space and time‐dependent GEV efficiently reduces this effect. Showing that the great Sahelian drought was accompanied by a significant decrease of extreme rainfall events is the other main result of this study.

Evaluation of areal precipitation estimates based on downscaled reanalysis and station data by hydrological modelling

Abstract. In data sparse mountainous regions it is difficult to derive areal precipitation estimates. In addition, their evaluation by cross validation can be misleading if the precipitation gauges are not in representative locations in the catchment. This study aims at the evaluation of precipitation estimates in data sparse mountainous catchments. In particular, it is first tested whether monthly precipitation fields from downscaled reanalysis data can be used for interpolating gauge observations. Secondly, precipitation estimates from this and other methods are evaluated by comparing simulated and observed discharge, which has the advantage that the data are evaluated at the catchment scale. This approach is extended here in order to differentiate between errors in the overall bias and the temporal dynamics, and by taking into account different sources of uncertainties. The study area includes six headwater catchments of the Karadarya Basin in Central Asia. Generally the precipitation estimate based on monthly precipitation fields from downscaled reanalysis data showed an acceptable performance, comparable to another interpolation method using monthly precipitation fields from multi-linear regression against topographical variables. Poor performance was observed in only one catchment, probably due to mountain ridges not resolved in the model orography of the regional climate model. Using two performance criteria for the evaluation by hydrological modelling allowed a more informed differentiation between the precipitation data and showed that the precipitation data sets mostly differed in their overall bias, while the performance with respect to the temporal dynamics was similar. Our precipitation estimates in these catchments are considerably higher than those from continental- or global-scale gridded data sets. The study demonstrates large uncertainties in areal precipitation estimates in these data sparse mountainous catchments. In such regions with only very few precipitation gauges but high spatial variability of precipitation, important information for evaluating precipitation estimates may be gained by hydrological modelling and a comparison to observed discharge.

Potential effects of climate change on inundation patterns in the Amazon Basin

Abstract. Floodplain forests, namely the Várzea and Igapó, cover an area of more than 97 000 km2. A key factor for their function and diversity is annual flooding. Increasing air temperature and higher precipitation variability caused by climate change are expected to shift the flooding regime during this century, and thereby impact floodplain ecosystems, their biodiversity and riverine ecosystem services. To assess the effects of climate change on the flooding regime, we use the Dynamic Global Vegetation and Hydrology Model LPJmL, enhanced by a scheme that realistically simulates monthly flooded area. Simulation results of discharge and inundation under contemporary conditions compare well against site-level measurements and observations. The changes of calculated inundation duration and area under climate change projections from 24 IPCC AR4 climate models differ regionally towards the end of the 21st century. In all, 70% of the 24 climate projections agree on an increase of flooded area in about one third of the basin. Inundation duration increases dramatically by on average three months in western and around one month in eastern Amazonia. The time of high- and low-water peak shifts by up to three months. Additionally, we find a decrease in the number of extremely dry years and in the probability of the occurrence of three consecutive extremely dry years. The total number of extremely wet years does not change drastically but the probability of three consecutive extremely wet years decreases by up to 30% in the east and increases by up to 25% in the west. These changes implicate significant shifts in regional vegetation and climate, and will dramatically alter carbon and water cycles.

Evapotranspiração de referência baseada em métodos empíricos em bacia experimental no estado de Pernambuco - Brasil

O estudo da evapotranspiração é importante para o planejamento agrícola, principalmente em regiões caracterizadas por grandes variabilidades espacial e temporal da precipitação, como nas áreas áridas e semiáridas do Nordeste do Brasil. Embora existam no Brasil duas grandes redes de observação meteorológica (INMET e CPTEC), ainda há muitas regiões não cobertas pelas mesmas, evidenciando a necessidade de métodos de cômputo da evapotranspiração baseados em poucos elementos meteorológicos. Considerando esta necessidade, este trabalho objetivou determinar a evapotranspiração de referência (ETo) por métodos indiretos em várias escalas de tempo na bacia experimental do riacho Gameleira, Vitória de Santo Antão, PE. Os métodos indiretos foram avaliados tendo como padrão o método Penman-Monteith FAO-56. Dentre os métodos baseados na temperatura do ar, Hargreaves-Samani (1985) apresentou desempenho "ótimo" nas escalas pentadal a mensal, seguido de Blaney-Criddle com desempenho "muito bom". Já os métodos de Camargo, Thornthwaite modificado e Thornthwaite apresentaram variações de desempenho de "mau a muito bom". Dos métodos baseados na radiação solar, o melhor desempenho foi o método da Radiação Solar, seguido de Makkink e Jensen-Haise. Diferentemente, os métodos baseados em modelagem estatística não estimaram a ETo com boa precisão, resultando em baixos coeficientes de determinação e desempenho.