Eta Model Research Articles

Ten-year seasonal climate reforecasts over South America using the Eta Regional Climate Model.

Ten-year seasonal climate reforecasts over South America are obtained using the Eta Regional Climate Model at 40 km resolution, driven by the large-scale forcing from the global atmospheric model of the Center for Weather Forecasts and Climate Studies. The objective of this work is to evaluate these regional reforecasts. The dataset is comprised of four-month seasonal forecasts performed on a monthly basis between 2001 and 2010. An ensemble of five members is constructed from five slightly different initial conditions to partially reduce the uncertainty in the seasonal forecasts. The seasonal mean precipitation and 2-meter temperature forecasts are compared with the observations. The comparison shows that, in general, forecasted precipitation is underestimated in the central part of the continent in the austral summer, whereas the forecasted 2 meter temperature is underestimated in most parts of the continent and throughout the year. Skill scores show higher skill in the northern part of the continent and lower skill in the southern part of the continent, but mixed skill signs are seen in the central part of the continent. During the El Niño and La Niña seasons, the forecast skill scores clearly increase. The downscaling of the Eta model seasonal forecasts provides added value over the driver global model forecasts, especially during rainy periods.

Phenotypic assessment and ligand screening of ETA/ETB receptors with label-free dynamic mass redistribution assay.

Endothelin receptors, consisting of two subtypes, ETA and ETB, are expressed in various tissues and widely regulate cardiovascular systems. The two receptors show distinct biological characteristics and are involved in different downstream pathways. Hence, to evaluate the ETA and ETB receptors on the same platform is helpful to display their pharmacological features. In this study, we developed a label-free dynamic mass redistribution (DMR) assay to investigate the phenotypic features of the ETA and ETB receptors in native cell lines. Meanwhile, specific agonists and antagonists were investigated for their pharmacological parameters. Results indicated that the DMR response of endothelin 1 (ET-1, an endogenous ETA/ETB agonist) was cell line dependent on ETA receptors and this ligand generated a biphasic dose-response curve in SH-SY5Y as well as PC3 cell lines. ET-1 and IRL 1620 (an ETB agonist) showed different DMR responses in U251 cells. IC50 values of antagonists were consistent with the Ki values previously reported. Furthermore, a list of compounds was screened on the ETA and ETB receptor models established by the high-throughput DMR assays. This study demonstrated that the DMR assay had great potential in the phenotypic-based investigation and ligand screening of GPCRs.

Forecasting the Full Distribution of Earthquake Numbers Is Fair, Robust, and Better

Forecasting the full distribution of the number of earthquakes is revealed to be inherently superior to forecasting their mean. Forecasting the full distribution of earthquake numbers is also shown to yield robust projections in the presence of surprise large earthquakes, which in the past have strongly deteriorated the scores of existing models. We show this with pseudo-prospective experiments on synthetic as well as real data from the Advanced National Seismic System (ANSS) database for California, with earthquakes with magnitude larger than 2.95 that occurred between the period 1971-2016. Our results call in question the testing methodology of the Collaboratory for the study of earthquake predictability (CSEP), which amounts to assuming a Poisson distribution of earthquake numbers, which is known to be a poor representation of the heavy-tailed distribution of earthquake numbers. Using a spatially varying ETAS model, we demonstrate a remarkable stability of the forecasting performance, when using the full distribution of earthquake numbers for the forecasts, even in the presence of large earthquakes such as Mw 7.1 Hector Mine, Mw 7.2 El Mayor-Cucapah, Mw 6.6 Sam Simeon earthquakes, or in the presence of intense swarm activity in Northwest Nevada in 2014. While our results have been derived for ETAS type models, we propose that all earthquake forecasting models of any type should embrace the full distribution of earthquake numbers, such that their true forecasting potential is revealed.

Impacts of regional climate change on the runoff and root water uptake in corn crops in Parana, Brazil

The natural environment of corn crops is being affected by climate changes. This research is aimed at evaluating the climate change scenarios resulting from the downscaling using the Eta regional climate model, nested in the global model CanESM2, and assessing the consequences of climate changes in the runoff and root water uptake of corn crops in the region of Parana, Brazil. This research also describes the climatology and the possible changes in the climate of the area, according to the different emission scenarios and infer how these changes will affect the dynamics of water in the corn crop in the region, simulated by Hydrus model. Simulations comprise of the historical period (1981–2005) and the future projections under RCP4.5 and RCP8.5, between the years 2046 to 2070. Eta model nested with the global model CanESM2 presented high ability to reproduce the climate in the region. Simulations showed changes in precipitation and an increasing trend of maximum and minimum temperatures when compared with the baseline. The root water uptake showed increasing trends predominantly in the RCP8.5 scenario. These climate changes can strongly affect corn production in the region of Parana, Brazil, as it can lead to increasing runoff and runoff extremes (runoff above 100 mm/day). This situation poses a risk to crop production since it causes losses by leaching and destruction of plants, as well as other factors such as lack of aeration and increased incidence of plant diseases. Similarly, the projected increase in temperature can result in increased evapotranspiration, which affects root water uptake, and the crop water demand.

ETAS 모델에 의한 한반도의 최근 지진활동 분석

ETAS 모델에 의한 한반도의 최근 지진활동 분석

The Relevance of Foreshocks in Earthquake Triggering: A Statistical Study.

An increase of seismic activity is often observed before large earthquakes. Events responsible for this increase are usually named foreshock and their occurrence probably represents the most reliable precursory pattern. Many foreshocks statistical features can be interpreted in terms of the standard mainshock-to-aftershock triggering process and are recovered in the Epidemic Type Aftershock Sequence ETAS model. Here we present a statistical study of instrumental seismic catalogs from four different geographic regions. We focus on some common features of foreshocks in the four catalogs which cannot be reproduced by the ETAS model. In particular we find in instrumental catalogs a significantly larger number of foreshocks than the one predicted by the ETAS model. We show that this foreshock excess cannot be attributed to catalog incompleteness. We therefore propose a generalized formulation of the ETAS model, the ETAFS model, which explicitly includes foreshock occurrence. Statistical features of aftershocks and foreshocks in the ETAFS model are in very good agreement with instrumental results.

Scenarios from the Eta Model on quality and hydrological quantity in the Atlantic Forest, Southern Brazil

ABSTRACT This work evaluated the response of two scenarios (4.5 and 8.5) of the Eta Model on the quality (sediment - TSS, nitrate - NO3- and phosphate - PO43-) and quantity (flow - Q) of the Concordia Catchment in the Atlantic forest biome. The importance of the work lies in the comparison of both scenarios until 2099, using current agricultural practices (2016). The SWAT model normally used for hydrological purposes has been applied to evaluate water quality from the monitoring programme database (2010-2014). Q showed a non-accentuated, upward trend. Modifications in Q were transmitted to TSS and PO43-. There was no significant difference between the tested scenarios.

PROJETA platform: accessing high resolution climate change projections over Central and South America using the Eta model

The search for data on climate change by researchers, government agencies or private companies is a recurrent demand. However, it is hampered by the means of access to this type of information, mainly due to the complexity of extracting, reformatting, and making this data available, which can exceed terabytes in size. The PROJETA platform aims to automate the process of extracting and making available the dataset of global climate change projections downscaling to 20 km over South America generated by the model Eta at CPTEC/INPE. The data request, processing, and conversion process, which used to be done manually and in a oneto-one data delivery basis. The objective of this work is to describe the methodology used to create the platform PROJETA and the information made available. It is a service that allows access to a broad set of different climatic variables. This dataset is available to different users via the Web or API, in a flexible way in terms of data format and data volume. In addition, it integrates technologies that allow the access to the database in an efficient and easy way for use in studies of impact, vulnerability, and adaptation to climate change in various socio-economic sectors.

Inference for ETAS models with non-Poissonian mainshock arrival times

The Hawkes process is a widely used statistical model for point processes which produce clustered event times. A specific version known as the ETAS model is used in seismology to forecast earthquake arrival times under the assumption that mainshocks follow a Poisson process, with aftershocks triggered via a parametric kernel function. However, this Poissonian assumption contradicts several aspects of seismological theory which suggest that the arrival time of mainshocks instead follows alternative renewal distributions such as the Gamma or Brownian Passage Time. We hence show how the standard ETAS/Hawkes process can be extended to allow for non-Poissonian distributions by introducing a dependence based on the underlying process’ behaviour. Direct maximum likelihood estimation of the resulting models is not computationally feasible in the general case, so we also present a novel Bayesian MCMC algorithm for efficient estimation using a latent variable representation.

Avalanche Behavior in Creep Failure of Disordered Materials

We present a mesoscale elastoplastic model of creep in disordered materials, which considers temperature-dependent stochastic activation of localized deformation events that are coupled by internal stresses, leading to collective avalanche dynamics. We generalize this stochastic plasticity model by introducing damage in terms of a local strength that decreases, on statistical average, with increasing local plastic strain. The model captures failure in terms of strain localization in a catastrophic shear band concomitant with a finite-time singularity of the creep rate. The statistics of avalanches in the run-up to failure is characterized by a decreasing avalanche exponent τ that, at failure, approaches the value τ=1.5 typical of a critical branching process. The average avalanche rate exhibits an inverse Omori law as a function of time to failure. The distribution of interavalanche times turns out to be consistent with the epidemic-type aftershock sequences (ETAS) model of earthquake statistics.

Probabilistic flood forecasting in the Doce Basin in Brazil: Effects of the basin scale and orientation and the spatial distribution of rainfall

We critically examined the performance of probabilistic streamflow forecasting in the prediction of flood events in 19 subbasins of the Doce River in Brazil using the Eta (4 members, 5 km spatial resolution) and European Centre for Medium‐Range Weather Forecasts (ECMWF; 51 members, 32 km resolution) weather forecast models as inputs for the MHD‐INPE hydrological model. We observed that the shapes and orientations of subbasins influenced the predictability of floods due to the orientation of rainfall events. Streamflow forecasts that use the ECMWF data as input showed higher skill scores than those that used the Eta model for subbasins with drainage areas larger than 20,000 km2. Since the skill scores were similar for both models in smaller subbasins, we concluded that the grid size of the weather model could be important for smaller catchments, while the number of members was crucial for larger scales. We also evaluated the performance of probabilistic streamflow forecasting for the severe flood event of late 2013 through a comparison of observations and streamflow estimations derived from interpolated rainfall fields. In many cases, the mean of the ensemble outperformed the streamflow estimations from the interpolated rainfall because the spatial structure of a rainfall event is better captured by weather forecast models.

Future climate change scenarios in Central America at high spatial resolution.

The objective of this work is to assess the downscaling projections of climate change over Central America at 8-km resolution using the Eta Regional Climate Model, driven by the HadGEM2-ES simulations of RCP4.5 emission scenario. The narrow characteristic of continent supports the use of numerical simulations at very high-horizontal resolution. Prior to assessing climate change, the 30-year baseline period 1961–1990 is evaluated against different sources of observations of precipitation and temperature. The mean seasonal precipitation and temperature distribution show reasonable agreement with observations. Spatial correlation of the Eta, 8-km resolution, simulations against observations show clear advantage over the driver coarse global model simulations. Seasonal cycle of precipitation confirms the added value of the Eta at 8-km over coarser resolution simulations. The Eta simulations show a systematic cold bias in the region. Climate features of the Mid-Summer Drought and the Caribbean Low-Level Jet are well simulated by the Eta model at 8-km resolution. The assessment of the future climate change is based on the 30-year period 2021–2050, under RCP4.5 scenario. Precipitation is generally reduced, in particular during the JJA and SON, the rainy season. Warming is expected over the region, but stronger in the northern portion of the continent. The Mid-Summer Drought may develop in regions that do not occur during the baseline period, and where it occurs the strength may increase in the future scenario. The Caribbean Low-Level Jet shows little change in the future. Extreme temperatures have positive trend within the period 2021–2050, whereas extreme precipitation, measured by R50mm and R90p, shows positive trend in the eastern coast, around Costa Rica, and negative trends in the northern part of the continent. Negative trend in the duration of dry spell, which is an estimate based on evapotranspiration, is projected in most part of the continent. Annual mean water excess has negative trends in most part of the continent, which suggests decreasing water availability in the future scenario.

Evaluating Precipitation Estimates from Eta, TRMM and CHRIPS Data in the South-Southeast Region of Minas Gerais State—Brazil

Precipitation estimates derived from the Eta model and from TRMM (Tropical Rainfall Measuring Mission) and CHIRPS (Climate Hazards Group InfraRed Precipitation with Station data) remotely sensed data were compared to the precipitation data of the INMET (National Institute of Meteorology) meteorological stations in the south-southeast region of Minas Gerais state, Brazil, in the period between July 2009 and June 2015. Then, information about evapotranspiration (ETR), water deficit (DEF), and water surplus (EXC) was obtained from the precipitation data, using the sequential water balance (SWB) separately for each type of precipitation data (INMET, TRMM, Eta, and CHIRPS). Subsequently, the components of the SWB were comparatively analyzed. The results indicate that all three products overestimate rainfall. The strongest relationships between the INMET data and the estimated data were observed for the TRMM, in terms of precipitation estimates, as well as DEF, EXC, and ETR components. The Eta precipitation estimates are overestimated relative to those from INMET, resulting in underestimation of the water deficit (DEFETA) and overestimation of evapotranspiration (ETRETA). In general, the CHIRPS data presented a pattern similar to the station data, though statistical analyses were lower than those of the TRMM data.

Projections of the impacts of climate change on the water deficit and on the precipitation erosive indexes in Mantaro River Basin, Peru

Projections of climate change are essential to guide sustainable development plans in the tropical Andean countries such as Peru. This study assessed the projections of precipitation and potential evaporation, rain erosive potential, and precipitation concentration in the Mantaro River Basin, in the Peruvian Andes, which is important for agriculture and energy production in Peru. We assumed the Intergovernmental Panel on Climate Change (IPCC) A1B greenhouse gas emission scenario and simulated the global climate change by the HadCM3 global climate model. Due to the steepness of the mountain slopes and the narrowness of the river valley, this study uses the downscaling of the global model simulations by the regional Eta model down to 20-km resolution. The downscaling projections show decrease in the monthly precipitation with respect to the baseline period, especially during the rainy season, between February and April, until the end of the 21st century. Meanwhile, a progressive increase in the monthly evaporation from the baseline period is projected. The Modified Fournier Index (MFI) shows a statistically significant downward trend in the Mantaro River Basin, which suggests a possible reduction in the rain erosive potential. The Precipitation Concentration Index (PCI) shows a statistically significant increasing trend, which indicates increasingly more irregular temporal distribution of precipitation towards the end of the century. The results of this study allow us to conclude that there should be a gradual increase in water deficit and precipitation concentration. Both changes can be negative for agriculture, power generation, and water supply in the Mantaro River Basin in Peru.

Improving drought management in the Brazilian semiarid through crop forecasting

In this paper, we evaluated the performance of the model AquaCrop for crop yield forecasting in the Brazilian semiarid (BSA) using meteorological observation and Eta model seasonal climate forecasts as input data. The study area is characterized by low rainfall that is poorly distributed throughout the rainy season; thus, the region's agricultural productivity is vulnerable to climate conditions. AquaCrop was first calibrated using field experiments and subsequently applied to simulate an operational crop yield forecast system for maize under rainfed conditions. Simulations were performed with daily data for 37 growing seasons for the period 2001–2010. The seasonal climate forecast was used in combination with observed meteorological data to anticipate the crop forecast. Soil characteristics were derived from pedotransfer functions (PTFs). We were able to demonstrate the ability of the seasonal crop yield forecast system to provide timely and accurate information about maize yield at least 30days in advance of the harvest. The development of improved crop yield forecasting system is crucial for implementing drought-preparedness measures in the BSA region.

The epistemic and aleatory uncertainties of the ETAS-type models: an application to the Central Italy seismicity

Stochastic models provide quantitative evaluations about the occurrence of earthquakes. A basic component of this type of models are the uncertainties in defining main features of an intrinsically random process. Even if, at a very basic level, any attempting to distinguish between types of uncertainty is questionable, an usual way to deal with this topic is to separate epistemic uncertainty, due to lack of knowledge, from aleatory variability, due to randomness. In the present study this problem is addressed in the narrow context of short-term modeling of earthquakes and, specifically, of ETAS modeling. By mean of an application of a specific version of the ETAS model to seismicity of Central Italy, recently struck by a sequence with a main event of Mw6.5, the aleatory and epistemic (parametric) uncertainty are separated and quantified. The main result of the paper is that the parametric uncertainty of the ETAS-type model, adopted here, is much lower than the aleatory variability in the process. This result points out two main aspects: an analyst has good chances to set the ETAS-type models, but he may retrospectively describe and forecast the earthquake occurrences with still limited precision and accuracy.

AN ANALYSIS OF RAINFALL EXTREMES IN THE NORTHERN SOUTH AMERICA AND THEIR BEHAVIORS FOR FUTURE CLIMATE BASED ON A1B SCENARIO

The Brazilian Amazon (BAMZ) and Northeast Brazil (NEB) regions have been facing intense climate extremes since the beginning of 21st century. In BAMZ, these climate extremes can modify the Amazon forest and its essential role in the local and remote climate. This study evaluated whether the extreme rainfall events in the both regions will be more intense and frequent in the future due to the increase of greenhouse gas emissions. An adapted version of the RX5day index was applied to distinguish between different types of extreme rainfall cases in the ETA model output for the decade 2089-2099 compared to the 1980-1990 decade. The results have shown that although the total rainfall is expected to be reduced by at least 1/3 (DJF) in the case of rare events, this kind of extreme rainfall will contribute with a higher amount of rainfall and will occur more frequently in both areas by the end of the 21st century. Heavy and very heavy events decrease for both areas (total rainfall amount and frequency). Results suggest that stakeholders must be prepared to cope with the population’s need for assistance during floods and rainfall reduction and reinforces the need to adapt to worse climate extremes projections.

Objective estimation of spatially variable parameters of epidemic type aftershock sequence model: Application to California

AbstractThe Epidemic Type Aftershock Sequence (ETAS) model is widely employed to model the spatiotemporal distribution of earthquakes, generally using spatially invariant parameters. We propose an efficient method for the estimation of spatially varying parameters, using the expectation maximization (EM) algorithm and spatial Voronoi tessellation ensembles. We use the Bayesian information criterion (BIC) to rank inverted models given their likelihood and complexity and select the best models to finally compute an ensemble model at any location. Using a synthetic catalog, we also check that the proposed method correctly inverts the known parameters. We apply the proposed method to earthquakes included in the Advanced National Seismic System catalog that occurred within the time period 1981–2015 in a spatial polygon around California. The results indicate significant spatial variation of the ETAS parameters. We find that the efficiency of earthquakes to trigger future ones (quantified by the branching ratio) positively correlates with surface heat flow. In contrast, the rate of earthquakes triggered by far‐field tectonic loading or background seismicity rate shows no such correlation, suggesting the relevance of triggering possibly through fluid‐induced activation. Furthermore, the branching ratio and background seismicity rate are found to be uncorrelated with hypocentral depths, indicating that the seismic coupling remains invariant of hypocentral depths in the study region. Additionally, triggering seems to be mostly dominated by small earthquakes. Consequently, the static stress change studies should not only focus on the Coulomb stress changes caused by specific moderate to large earthquakes but also account for the secondary static stress changes caused by smaller earthquakes.

CLIMATE CHANGE IMPACTS ON WATER DEMAND OF MELON PLANTS IN JAGUARIBE-APODI REGION, BRAZIL

ABSTRACT The aim of this study was to evaluate the impacts of climate change on irrigation water demand of melon plants grown in Jaguaribe-Apodi Irrigation District (DIJA), which is located between the states of Ceara and Rio Grande do Norte, in Northeastern Brazil. Future scenarios were developed using the Eta-CPTEC/HadCM3 climate change projections, after being submitted to downscaling method. We used a set of climate data from the same model for the period of 1961 through 1990, and further projections after bias correction. Local geographic coordinates were interpolated using GIS techniques. Reference evapotranspiration (ETo) was estimated from the monthly minimum and maximum mean temperatures, using a limited data method. The rainfall, temperature, ETo, and water demand future projections were mapped for the area of investigation to analyze spatial variability. ETA model simulations for climatic change showed growth in irrigation water demands due to evapotranspiration increase (from 28.4% to 33.4%), even though rainfall increases (between 61.9% and 89.9%). The increase in the average gross water demand is varied from 37.5% to 78.2% within the period of 2031 to 2060, respective to the common planting season.

Forecasts of extreme precipitation in the western Balkans in May 2014: model skill and sensitivity to the vertical co‐ordinate

ABSTRACTThis study examines the simulation of the catastrophic precipitating event that occurred on 14–16 May 2014 over the western Balkans, using two regional models, the Eta model and the Weather Research and Forecasting Non‐hydrostatic Mesoscale Model (WRF‐NMM). This case was an extreme precipitation event with very large precipitation totals exceeding 200 mm in 72 h. The Eta model was run in two variants, switched to use the eta co‐ordinate with sloping steps and switched to use the sigma co‐ordinate. The aim of this study was to analyse the ability of the regional model to forecast heavy precipitation successfully as well as the impact of the vertical co‐ordinate on the forecasting of extreme precipitation events based on realistic model simulation. Experiments show the ability of regional models to reproduce extreme accumulations for 2 days of heavy precipitation with bias adjusted equitable threat score ranging from 0.3 to 0.5 for precipitation greater than the analysed threshold values (25–55 mm day−1), whereby the Eta model exhibits a slight advantage over the WRF‐NMM and the run of the Eta model switched to the eta co‐ordinate has the smallest frequency bias. For larger observed accumulations exceeding 50 mm day−1 all forecasts tend to be more biased. The root mean square precipitation difference varies insignificantly between the three forecasts. The results of the experiment indicate that, in the case of the extreme precipitation considered in this study, scores of the forecasts of the Eta model for 10 m wind speed and 2 m temperature show a small dependence on the vertical co‐ordinate and in favour of the run with the eta co‐ordinate.