975 resultados para Precipitation climatology
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The State of Sao Paulo is the richest in Brazil, responsible for over 30% of the Brazilian gross rate. It has a population of around 30 million and its economy is based on agriculture and industrial products. Any change in climate can have a profound influence on the socio-economics of the State. In order to determine changes in total and extreme rainfall over Sao Paulo State, climate change indices derived from daily precipitation data were calculated using specially designed software. Maps of trends for a subset of 59 rain gauge stations were analysed for the period 1950-1999 and also for a subset of this period, 1990-1999, representing more recent climate. A non-parametric Mann-Kendall test was applied to the time series. Maps of trends for six annual precipitation indices (annual total precipitation (PRCPTOT), very heavy precipitation days (R20mm), events greater than the 95th percentile (R95p), maximum five days precipitation total (RX5day), the length of the largest wet spell (CWD) and the length of the largest dry spell (CDD)) were analysed for the entire period. These exhibited statistically significant trends associated with a wetter climate. A significant increase in PRCPTOT, associated with very heavy precipitation days, were observed at more than 45% of the rain gauge stations. The Mann-Kendall test identified that the positive trend in PRCPTOT is possibly related to the increase in the R95p and R20mm indices. Therefore, the results suggest that there has been a change in precipitation intensity. In contrast, the indices for the more recent shorter time series are significantly different to the longer term indices. The results indicate that intense precipitation is becoming concentrated in a few days and spread over the period when the CDD and R20mm indices show positive trends, while negative ones are seen in the RX5day index. The trends found could be related to many anthropogenic aspects such as biomass burning aerosols and land use.
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The emphasis in this research is to evaluate the spatial distribution of the precipitation using a geostatistics approach. Seasonal time scales records considering DJF, MAM, JJA e SON periods performed the analysis. Procedures to evaluate the variogram selection and to produce kriging maps were performed in a GIS environment (ArcGIS®). The results showed that kriging method was very suitable to detect both large changes in the whole area as those local small and subtle changes. Kriging demonstrated be a powerful statistical interpolation method that might be very useful in regions with great complexity in climatology and geomorphology.
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The RegCM3 (Regional Climate Model-version 3) was nested in HadAM3 model to simulate present (1975-1989, referred hereafter as RegHad) and two future climate scenarios (A2 and B2 from 2071 to 2085, referred as RegA2 and RegB2) over the South America (SA) and South Atlantic Ocean (SAO). Projected changes in the air temperature, precipitation, low level circulation and cyclogenesis climatology were investigated. The cyclogenesis were identified using an automatic scheme for tracking based on the minimum of relative vorticity (zeta) from 10-m height wind. During summer, a general decrease (increase) in the precipitation is projected by RegA2 and RegB2 over the northeastern SA (center-west and south Brazil, north Argentina and Uruguay). For winter, an anomalous low level anticyclonic circulation is associated with the reduction in the rainfall over the central part of southern Brazil in RegA2 and RegB2 scenarios. Similar to HadAM3, RegCM3 projects larger warming in A2 scenario. For the present climate, when compared to HadAM3, RegHad defines better both the location of the main cyclogenetic areas and its annual cycle near southwestern SAO. The projections indicate a reduction in the total number of cyclones of -7.2% and -4.7% for RegA2 and RegB2, respectively, while HadAM3 reduction is -4.5% for both scenarios. The decrease is larger for initially intense cyclones (zeta <=-<= 2.5 x 10(-5) s-(1)): -20.9% (RegA2) and -11.3% (RegB2). For the lifetime, distance traveled and mean velocity of the cyclones, the A2 and B2 scenarios present mean values close to the present climate ( 3 days, 1900 km, and 9 m s(-1), respectively). Regarding the initial mean vorticity of the systems, RegB2 simulates values similar to the present climate, but they are initially weaker in RegA2. In general, RegA2 and RegB2 show a large decrease in the number of cyclones over the southern SAO due to an anticyclonic anomaly covering SAO between 30-55A degrees S. The reduction is larger in the scenario with higher concentrations of greenhouse gases (RegA2).
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We analyse winter (DJF) precipitation over the last 500 years on trends using a spatially and temporally highly resolved gridded multi-proxy reconstruction over European land areas. The trends are detected applying trend matrices, and the significance is assessed with the Mann–Kendall-trend test. Results are presented for southwestern Norway and southern Spain/northern Morocco, two regions that show high reconstruction skill over the entire period. The absolute trend values found in the second part of the 20th century are unprecedented over the last 500 years in both regions. During the period 1715–1765, the precipitation trends were most pronounced in southwestern Norway as well as southern Spain/northern Morocco, with first a distinct negative trend followed by a positive countertrend of similar strength. Relating the precipitation time series to variations of the North Atlantic Oscillation Index (NAOI) and the solar irradiance using running correlations revealed a couple of instationarities. Nevertheless, it appears that the NAO is responsible in both regions for most of the significant winter precipitation trends during the earlier centuries as well as during recent decades. Some of the significant winter precipitation trends over southwestern Norway and southern Spain/northern Morocco might be related to changes in the solar irradiance.
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An important key for the understanding of the dynamic response to large tropical volcanic eruptions is the warming of the tropical lower stratosphere and the concomitant intensification of the polar vortices. Although this mechanism is reproduced by most general circulation models today, most models still fail in producing an appropriate winter warming pattern in the Northern Hemisphere. In this study ensemble sensitivity experiments were carried out with a coupled atmosphere-ocean model to assess the influence of different ozone climatologies on the atmospheric dynamics and in particular on the northern hemispheric winter warming. The ensemble experiments were perturbed by a single Tambora-like eruption. Larger meridional gradients in the lower stratospheric ozone favor the coupling of zonal wind anomalies between the stratosphere and the troposphere after the eruption. The associated sea level pressure, temperature, and precipitation patterns are more pronounced and the northern hemispheric winter warming is highly significant. Conversely, weaker meridional ozone gradients lead to a weaker response of the winter warming and the associated patterns. The differences in the number of stratosphere-troposphere coupling events between the ensembles experiments indicate a nonlinear response behavior of the dynamics with respect to the ozone and the volcanic forcing.
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The tropical region is an area of maximum humidity and serves as the major humidity source of the globe. Among other phenomena, it is governed by the so-called Inter-Tropical Convergence Zone (ITCZ) which is commonly defined by converging low-level winds or enhanced precipitation. Given its importance as a humidity source, we investigate the humidity fields in the tropics in different reanalysis data sets, deduce the climatology and variability and assess the relationship to the ITCZ. Therefore, a new analysis method of the specific humidity distribution is introduced which allows detecting the location of the humidity maximum, the strength and the meridional extent. The results show that the humidity maximum in boreal summer is strongly shifted northward over the warm pool/Asia Monsoon area and the Gulf of Mexico. These shifts go along with a peak in the strength in both areas; however, the extent shrinks over the warm pool/Asia Monsoon area, whereas it is wider over the Gulf of Mexico. In winter, such connections between location, strength and extent are not found. Still, a peak in strength is again identified over the Gulf of Mexico in boreal winter. The variability of the three characteristics is dominated by inter-annual signals in both seasons. The results using ERA-interim data suggest a positive trend in the Gulf of Mexico/Atlantic region from 1979 to 2010, showing an increased northward shift in the recent years. Although the trend is only weakly confirmed by the results using MERRA reanalysis data, it is in phase with a trend in hurricane activity�a possible hint of the importance of the new method on hurricanes. Furthermore, the position of the maximum humidity coincides with one of the ITCZ in most areas. One exception is the western and central Pacific, where the area is dominated by the double ITCZ in boreal winter. Nevertheless, the new method enables us to gain more insight into the humidity distribution, its variability and the relationship to ITCZ characteristics.
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Determining the role of different precipitation periods for peak discharge generation is crucial for both projecting future changes in flood probability and for short- and medium-range flood forecasting. In this study, catchment-averaged daily precipitation time series are analyzed prior to annual peak discharge events (floods) in Switzerland. The high number of floods considered – more than 4000 events from 101 catchments have been analyzed – allows to derive significant information about the role of antecedent precipitation for peak discharge generation. Based on the analysis of precipitation times series, a new separation of flood-related precipitation periods is proposed: (i) the period 0 to 1 day before flood days, when the maximum flood-triggering precipitation rates are generally observed, (ii) the period 2 to 3 days before flood days, when longer-lasting synoptic situations generate "significantly higher than normal" precipitation amounts, and (iii) the period from 4 days to 1 month before flood days when previous wet episodes may have already preconditioned the catchment. The novelty of this study lies in the separation of antecedent precipitation into the precursor antecedent precipitation (4 days before floods or earlier, called PRE-AP) and the short range precipitation (0 to 3 days before floods, a period when precipitation is often driven by one persistent weather situation like e.g., a stationary low-pressure system). A precise separation of "antecedent" and "peak-triggering" precipitation is not attempted. Instead, the strict definition of antecedent precipitation periods permits a direct comparison of all catchments. The precipitation accumulating 0 to 3 days before an event is the most relevant for floods in Switzerland. PRE-AP precipitation has only a weak and region-specific influence on flood probability. Floods were significantly more frequent after wet PRE-AP periods only in the Jura Mountains, in the western and eastern Swiss plateau, and at the outlet of large lakes. As a general rule, wet PRE-AP periods enhance the flood probability in catchments with gentle topography, high infiltration rates, and large storage capacity (karstic cavities, deep soils, large reservoirs). In contrast, floods were significantly less frequent after wet PRE-AP periods in glacial catchments because of reduced melt. For the majority of catchments however, no significant correlation between precipitation amounts and flood occurrences is found when the last 3 days before floods are omitted in the precipitation amounts. Moreover, the PRE-AP was not higher for extreme floods than for annual floods with a high frequency and was very close to climatology for all floods. The fact that floods are not significantly more frequent nor more intense after wet PRE-AP is a clear indicator of a short discharge memory of Pre-Alpine, Alpine and South Alpine Swiss catchments. Our study poses the question whether the impact of long-term precursory precipitation for floods in such catchments is not overestimated in the general perception. The results suggest that the consideration of a 3–4 days precipitation period should be sufficient to represent (understand, reconstruct, model, project) Swiss Alpine floods.
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Land and water management in semi-arid regions requires detailed information on precipitation distribution, including extremes, and changes therein. Such information is often lacking. This paper describes statistics of mean and extreme precipitation in a unique data set from the Mount Kenya region, encompassing around 50 stations with at least 30 years of data. We describe the data set, including quality control procedures and statistical break detection. Trends in mean precipitation and extreme indices calculated from these data for individual rainy seasons are compared with corresponding trends in reanalysis products. From 1979 to 2011, mean precipitation decreased at 75% of the stations during the ‘long rains’ (March to May) and increased at 70% of the stations during the ‘short rains’ (October to December). Corresponding trends are found in the number of heavy precipitation days, and maximum of consecutive 5-day precipitation. Conversely, an increase in consecutive dry days within both main rainy seasons is found. However, trends are only statistically significant in very few cases. Reanalysis data sets agree with observations with respect to interannual variability, while correlations are considerably lower for monthly deviations (ratios) from the mean annual cycle. While some products well reproduce the rainfall climatology and some the spatial trend pattern, no product reproduces both.
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Data compiled within the IMPENSO project. The Impact of ENSO on Sustainable Water Management and the Decision-Making Community at a Rainforest Margin in Indonesia (IMPENSO), http://www.gwdg.de/~impenso, was a German-Indonesian research project (2003-2007) that has studied the impact of ENSO (El Nino-Southern Oscillation) on the water resources and the agricultural production in the PALU RIVER watershed in Central Sulawesi. ENSO is a climate variability that causes serious droughts in Indonesia and other countries of South-East Asia. The last ENSO event occurred in 1997. As in other regions, many farmers in Central Sulawesi suffered from reduced crop yields and lost their livestock. A better prediction of ENSO and the development of coping strategies would help local communities mitigate the impact of ENSO on rural livelihoods and food security. The IMPENSO project deals with the impact of the climate variability ENSO (El Niño Southern Oscillation) on water resource management and the local communities in the Palu River watershed of Central Sulawesi, Indonesia. The project consists of three interrelated sub-projects, which study the local and regional manifestation of ENSO using the Regional Climate Models REMO and GESIMA (Sub-project A), quantify the impact of ENSO on the availability of water for agriculture and other uses, using the distributed hydrological model WaSiM-ETH (Sub-project B), and analyze the socio-economic impact and the policy implications of ENSO on the basis of a production function analysis, a household vulnerability analysis, and a linear programming model (Sub-project C). The models used in the three sub-projects will be integrated to simulate joint scenarios that are defined in collaboration with local stakeholders and are relevant for the design of coping strategies.
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The Ebro River Basin, with around 85 000 km2 and located in NE Spain, is characterized by the high spatial heterogeneity of its geology, topography, climatology and land use. Rainfall is one of the most important climatic variables studied owing to its non-homogenous behaviour in event and intensity, which creates drought, water runoff and soil erosion with negative environmental and social consequences. In this work we characterized the rainfall variability pattern in the Ebro River Basin using universal multifractal (UM) analysis, which estimates the concentration of the data around the precipitation average (C1, codimension average), the degree of multiscaling behaviour in time (? index) and the maximum probable singularity in the rainfall distribution ( s). A spatial and temporal analysis of the UM parameters is applied to study the possible changes. With this porpoise, 60 daily rainfall series were selected from 132 synthetic series generated by Luna and Balairón (AEMet). These daily rainfall series present a length of 60 years, from 1950 to 2009. Each one of them was subdivided (1950?1970 and 1980?2009) to analyse the difference between the two periods. The range of variation of precipitation amounts and the frequency of dry events between both periods are discussed, as well as the evolution of the UM parameters through the years.
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This paper presents a new statistical algorithm to estimate rainfall over the Amazon Basin region using the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI). The algorithm relies on empirical relationships derived for different raining-type systems between coincident measurements of surface rainfall rate and 85-GHz polarization-corrected brightness temperature as observed by the precipitation radar (PR) and TMI on board the TRMM satellite. The scheme includes rain/no-rain area delineation (screening) and system-type classification routines for rain retrieval. The algorithm is validated against independent measurements of the TRMM-PR and S-band dual-polarization Doppler radar (S-Pol) surface rainfall data for two different periods. Moreover, the performance of this rainfall estimation technique is evaluated against well-known methods, namely, the TRMM-2A12 [ the Goddard profiling algorithm (GPROF)], the Goddard scattering algorithm (GSCAT), and the National Environmental Satellite, Data, and Information Service (NESDIS) algorithms. The proposed algorithm shows a normalized bias of approximately 23% for both PR and S-Pol ground truth datasets and a mean error of 0.244 mm h(-1) ( PR) and -0.157 mm h(-1)(S-Pol). For rain volume estimates using PR as reference, a correlation coefficient of 0.939 and a normalized bias of 0.039 were found. With respect to rainfall distributions and rain area comparisons, the results showed that the formulation proposed is efficient and compatible with the physics and dynamics of the observed systems over the area of interest. The performance of the other algorithms showed that GSCAT presented low normalized bias for rain areas and rain volume [0.346 ( PR) and 0.361 (S-Pol)], and GPROF showed rainfall distribution similar to that of the PR and S-Pol but with a bimodal distribution. Last, the five algorithms were evaluated during the TRMM-Large-Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) 1999 field campaign to verify the precipitation characteristics observed during the easterly and westerly Amazon wind flow regimes. The proposed algorithm presented a cumulative rainfall distribution similar to the observations during the easterly regime, but it underestimated for the westerly period for rainfall rates above 5 mm h(-1). NESDIS(1) overestimated for both wind regimes but presented the best westerly representation. NESDIS(2), GSCAT, and GPROF underestimated in both regimes, but GPROF was closer to the observations during the easterly flow.