Uncertainties In Future Projections Of Extreme Rainfall: The Role Of Climate Model, Emission Scenario And Randomness

Climate change has resulted in substantial variations in annual extreme rainfall quantiles in different durations and return periods. Predicting the future changes in extreme rainfall quantiles is essential for various water resources design, assessment, and decision making purposes. Current Predictions of future rainfall extremes, however, exhibit large uncertainties. According to extreme value theory, rainfall extremes are rather random variables, with changing distributions around different return periods; therefore there are uncertainties even under current climate conditions. Regarding future condition, our large-scale knowledge is obtained using global climate models, forced with certain emission scenarios. There are widely known deficiencies with climate models, particularly with respect to precipitation projections. There is also recognition of the limitations of emission scenarios in representing the future global change. Apart from these large-scale uncertainties, the downscaling methods also add uncertainty into estimates of future extreme rainfall when they convert the larger-scale projections into local scale. The aim of this research is to address these uncertainties in future projections of extreme rainfall of different durations and return periods. We plugged 3 emission scenarios with 2 global climate models and used LARS-WG, a well-known weather generator, to stochastically downscale daily climate models’ projections for the city of Saskatoon, Canada, by 2100. The downscaled projections were further disaggregated into hourly resolution using our new stochastic and non-parametric rainfall disaggregator. The extreme rainfall quantiles can be consequently identified for different durations (1-hour, 2-hour, 4-hour, 6-hour, 12-hour, 18-hour and 24-hour) and return periods (2-year, 10-year, 25-year, 50-year, 100-year) using Generalized Extreme Value (GEV) distribution. By providing multiple realizations of future rainfall, we attempt to measure the extent of total predictive uncertainty, which is contributed by climate models, emission scenarios, and downscaling/disaggregation procedures. The results show different proportions of these contributors in different durations and return periods.

Quantization of the electromagnetic field outside static black holes and its application to low-energy phenomena

We discuss the Gupta-Bleuler quantization of the free electromagnetic field outside static black holes in the Boulware vacuum. We use a gauge which reduces to the Feynman gauge in Minkowski spacetime. We also discuss its relation with gauges used previously. Then we apply the low-energy sector of this held theory to investigate some low-energy phenomena. First, we discuss the response rate of a static charge outside the Schwarzschild black hole in four dimensions. Next, motivated by string physics, we compute the absorption cross sections of low-energy plane waves for the Schwarzschild and extreme Reissner-Nordstrom black holes in arbitrary dimensions higher than three.

Non-stationary frequency analysis of extreme daily rainfall in São Paulo, Brazil

This work is an assessment of frequency of extreme values (EVs) of daily rainfall in the city of São Paulo. Brazil, over the period 1933-2005, based on the peaks-over-threshold (POT) and Generalized Pareto Distribution (GPD) approach. Usually. a GPD model is fitted to a sample of POT Values Selected With a constant threshold. However. in this work we use time-dependent thresholds, composed of relatively large p quantities (for example p of 0.97) of daily rainfall amounts computed from all available data. Samples of POT values were extracted with several Values of p. Four different GPD models (GPD-1, GPD-2, GPD-3. and GDP-4) were fitted to each one of these samples by the maximum likelihood (ML) method. The shape parameter was assumed constant for the four models, but time-varying covariates were incorporated into scale parameter of GPD-2. GPD-3, and GPD-4, describing annual cycle in GPD-2. linear trend in GPD-3, and both annual cycle and linear trend in GPD-4. The GPD-1 with constant scale and shape parameters is the simplest model. For identification of the best model among the four models WC used rescaled Akaike Information Criterion (AIC) with second-order bias correction. This criterion isolates GPD-3 as the best model, i.e. the one with positive linear trend in the scale parameter. The slope of this trend is significant compared to the null hypothesis of no trend, for about 98% confidence level. The non-parametric Mann-Kendall test also showed presence of positive trend in the annual frequency of excess over high thresholds. with p-value being virtually zero. Therefore. there is strong evidence that high quantiles of daily rainfall in the city of São Paulo have been increasing in magnitude and frequency over time. For example. 0.99 quantiles of daily rainfall amount have increased by about 40 mm between 1933 and 2005. Copyright (C) 2008 Royal Meteorological Society

Los efectos de los desastres en 2004 y 2005: la necesidad de adaptación de largo plazo

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Analysis and developments of uncertainty processors for real time flood forecasting

The hydrologic risk (and the hydro-geologic one, closely related to it) is, and has always been, a very relevant issue, due to the severe consequences that may be provoked by a flooding or by waters in general in terms of human and economic losses. Floods are natural phenomena, often catastrophic, and cannot be avoided, but their damages can be reduced if they are predicted sufficiently in advance. For this reason, the flood forecasting plays an essential role in the hydro-geological and hydrological risk prevention. Thanks to the development of sophisticated meteorological, hydrologic and hydraulic models, in recent decades the flood forecasting has made a significant progress, nonetheless, models are imperfect, which means that we are still left with a residual uncertainty on what will actually happen. In this thesis, this type of uncertainty is what will be discussed and analyzed. In operational problems, it is possible to affirm that the ultimate aim of forecasting systems is not to reproduce the river behavior, but this is only a means through which reducing the uncertainty associated to what will happen as a consequence of a precipitation event. In other words, the main objective is to assess whether or not preventive interventions should be adopted and which operational strategy may represent the best option. The main problem for a decision maker is to interpret model results and translate them into an effective intervention strategy. To make this possible, it is necessary to clearly define what is meant by uncertainty, since in the literature confusion is often made on this issue. Therefore, the first objective of this thesis is to clarify this concept, starting with a key question: should be the choice of the intervention strategy to adopt based on the evaluation of the model prediction based on its ability to represent the reality or on the evaluation of what actually will happen on the basis of the information given by the model forecast? Once the previous idea is made unambiguous, the other main concern of this work is to develope a tool that can provide an effective decision support, making possible doing objective and realistic risk evaluations. In particular, such tool should be able to provide an uncertainty assessment as accurate as possible. This means primarily three things: it must be able to correctly combine all the available deterministic forecasts, it must assess the probability distribution of the predicted quantity and it must quantify the flooding probability. Furthermore, given that the time to implement prevention strategies is often limited, the flooding probability will have to be linked to the time of occurrence. For this reason, it is necessary to quantify the flooding probability within a horizon time related to that required to implement the intervention strategy and it is also necessary to assess the probability of the flooding time.

Impact of irrigation in the Po valley (Italy) on meteorological parameters through numerical simulation

Recent studies found that soil-atmosphere coupling features, through soil moisture, have been crucial to simulate well heat waves amplitude, duration and intensity. Moreover, it was found that soil moisture depletion both in Winter and Spring anticipates strong heat waves during the Summer. Irrigation in geophysical studies can be intended as an anthropogenic forcing to the soil-moisture, besides changes in land proprieties. In this study, the irrigation was add to a LAM hydrostatic model (BOLAM) and coupled with the soil. The response of the model to irrigation perturbation is analyzed during a dry Summer season. To identify a dry Summer, with overall positive temperature anomalies, an extensive climatological characterization of 2015 was done. The method included a statistical validation on the reference period distribution used to calculate the anomalies. Drought conditions were observed during Summer 2015 and previous seasons, both on the analyzed region and the Alps. Moreover July was characterized as an extreme event for the referred distribution. The numerical simulation consisted on the summer season of 2015 and two run: a control run (CTR), with the soil coupling and a perturbed run (IPR). The perturbation consists on a mask of land use created from the Cropland FAO dataset, where an irrigation water flux of 3 mm/day was applied from 6 A.M. to 9 A.M. every day. The results show that differences between CTR and IPR has a strong daily cycle. The main modifications are on the air masses proprieties, not on to the dynamics. However, changes in the circulation at the boundaries of the Po Valley are observed, and a diagnostic spatial correlation of variable differences shows that soil moisture perturbation explains well the variation observed in the 2 meters height temperature and in the latent heat fluxes.On the other hand, does not explain the spatial shift up and downslope observed during different periods of the day. Given the results, irrigation process affects the atmospheric proprieties on a larger scale than the irrigation, therefore it is important in daily forecast, particularly during hot and dry periods.

The extreme flood event of Lago Maggiore in September 1993

In September 1993, the Valais and Ticino regions of Switzerland were affected by extreme flooding triggered by heavy precipitation. The meteorological situation leading to this event is studied in the Twentieth Century Reanalysis (20CR) data set. A strong cut-off low development is found to be the driving synoptic-scale atmospheric circulation pattern. The agreement with previous studies highlights the applicability of 20CR for extreme event analysis.

Great expectations: what can fMRI research tell us about psychological phenomena?

Expectations for what functional magnetic resonance imaging (fMRI) can offer psychophysiology vary greatly. Overreaching enthusiasm such as the idea that fMRI can reveal lies and political attitudes are as common as the opinion that fMRI, in its current form, is useless for the advancement of psychological theories. Errors in the inferences being drawn from fMRI data may be contributing to each of these extreme positions, so the present paper addresses these several common inferential errors and describes some of the potential of fMRI for psychophysiological theory and research.

Trends of mean and extreme temperature indices since 1874 at low-elevation sites in the Southern Alps

We describe the recovery of three daily meteorological records for the southern Alps (Domodossola, Riva del Garda, and Rovereto), all starting in the second half of the nineteenth century. We use these new data, along with additional records, to study regional changes in the mean temperature and extreme indices of heat waves and cold spells frequency and duration over the period 1874–2015. The records are homogenized using subdaily cloud cover observations as a constraint for the statistical model, an approach that has never been applied before in the literature. A case study based on a record of parallel observations between a traditional meteorological window and a modern screen shows that the use of cloud cover can reduce the root-mean-square error of the homogenization by up to 30% in comparison to an unaided statistical correction. We find that mean temperature in the southern Alps has increased by 1.4°C per century over the analyzed period, with larger increases in daily minimum temperatures than maximum temperatures. The number of hot days in summer has more than tripled, and a similar increase is observed in duration of heat waves. Cold days in winter have dropped at a similar rate. These trends are mainly caused by climate change over the last few decades.

Turbulent flux and meteorological measurements during ARCTEX-2006 campaign

This dataset present result from the DFG- funded Arctic-Turbulence-Experiment (ARCTEX-2006) performed by the University of Bayreuth on the island of Svalbard, Norway, during the winter/spring transition 2006. From May 5 to May 19, 2006 turbulent flux and meteorological measurements were performed on the monitoring field near Ny-Ålesund, at 78°55'24'' N, 11°55'15'' E Kongsfjord, Svalbard (Spitsbergen), Norway. The ARCTEX-2006 campaign site was located about 200 m southeast of the settlement on flat snow covered tundra, 11 m to 14 m above sea level. The permanent sites used for this study consisted of the 10 m meteorological tower of the Alfred Wegener Institute for Polar- and Marine Research (AWI), the international standardized radiation measurement site of the Baseline Surface Radiation Network (BSRN), the radiosonde launch site and the AWI tethered balloon launch sites. The temporary sites - set up by the University of Bayreuth - were a 6 m meteorological gradient tower, an eddy-flux measurement complex (EF), and a laser-scintillometer section (SLS). A quality assessment and data correction was applied to detect and eliminate specific measurement errors common at a high arctic landscape. In addition, the quality checked sensible heat flux measurements are compared with bulk aerodynamic formulas that are widely used in atmosphere-ocean/land-ice models for polar regions as described in Ebert and Curry (1993, doi:10.1029/93JC00656) and Launiainen and Cheng (1995). These parameterization approaches easily allow estimation of the turbulent surface fluxes from routine meteorological measurements. The data show: - the role of the intermittency of the turbulent atmospheric fluctuation of momentum and scalars, - the existence of a disturbed vertical temperature profile (sharp inversion layer) close to the surface, - the relevance of possible free convection events for the snow or ice melt in the Arctic spring at Svalbard, and - the relevance of meso-scale atmospheric circulation pattern and air-mass advection for the near-surface turbulent heat exchange in the Arctic spring at Svalbard. Recommendations and improvements regarding the interpretation of eddy-flux and laser-scintillometer data as well as the arrangement of the instrumentation under polar distinct exchange conditions and (extreme) weather situations could be derived.

New analysis and estimations of atmospheric attenuation at 100 GHz using meteorological data in Madrid

Atmospheric propagation at frequencies within the THz domain are deeply affected by the influence of the composition and phenomena of the troposphere. This paper is focused on the estimation of first order statistics of total attenuation under non-rainy conditions at 100 GHz. With this purpose, a yearly meteorological database from Madrid, including radiosoundings, SYNOP observations and co-site rain gauge, have been used in order to calculate attenuation due to atmospheric gases and clouds, as well as to introduce and evaluate a rain detection method. This method allows to filter out rain events and refine the statistics of total attenuation under the scenarios under study. It is expected that the behavior of the statistics would be closest to the ones obtained by experimental techniques under similar conditions.

Evolution of extreme temperature events in short term climate projection for Iberian Peninsula

Extreme events of maximum and minimum temperatures are a main hazard for agricultural production in Iberian Peninsula. For this purpose, in this study we analyze projections of their evolution that could be valid for the next decade, represented in this study by the 30-year period 2004-2034 (target period). For this purpose two kinds of data were used in this study: 1) observations from the station network of AEMET (Spanish National Meteorological Agency) for five Spanish locations, and 2) simulated data at a resolution of 50 50 km horizontal grid derived from the outputs of twelve Regional Climate Models (RCMs) taken from project ENSEMBLES (van der Linden and Mitchell, 2009), with a bias correction (Dosio and Paruolo, 2011; Dosio et al., 2012) regarding the observational dataset Spain02 (Herrera et al., 2012). To validate the simulated climate, the available period of observations was compared to a baseline period (1964-1994) of simulated climate for all locations. Then, to analyze the changes for the present/very next future, probability of extreme temperature events for 2004-2034 were compared to that of the baseline period. Although only minor changes are expected, small variations in variability may have a significant impact in crop performance.

Extreme overirradiance events in Sao Paulo, Brazil

Phenomena of overirradiance have been pointed all over the World. This note presents the most extreme enhancement event reported in Brazil, which contains an irradiance reading of 1590 W/m2 measured in São Paulo (latitude 23°32′S) at relatively low altitude (760 m a.s.l.).