94 research outputs found
Regionalisation of heat waves in southern South America
No full textThis study describes the climatological characteristics of regional heat waves (HWs) over southern South America (SSA) for the warm seasons (October–March) of 1979–2018 based on daily maximum temperature series from 131 weather stations. Clustering of stations with high co-occurrence of simultaneous HW days is employed to identify regional HW events over five homogeneous regions: northern, central-eastern and southern SSA regions, central Argentina, and central Chile. When all regions are considered, we find a mean frequency of ∼4 HWs per year. Transitional regions (northern SSA, central-eastern SSA and central Argentina) are characterised by longer, albeit less intense, HWs than the southernmost region (southern SSA), whereas central Chile events display the lowest duration, intensity and extension. By aggregating these single HW attributes into a combined severity index, a ranking of historical HWs has been obtained, with the March 1980 event standing as the most severe one of SSA. The assessment of long-term changes reveals significant increases in the frequency of regional HW days over central Argentina and central Chile only. Trends in HW characteristics are also region dependent, and the southernmost region is the only one where HW severity has increased significantly.We report similarities and differences in the synoptic circulation patterns associated with regional HW events. Southern SSA HWs have the most distinctive signatures, related to extratropical high-pressure systems blocking the westerly flow. In the remaining regions, HWs are associated with anomalies in the South Atlantic (northern SSA, central-eastern SSA and central Argentina) or South Pacific (central Chile) High, and the intensification of the northerly low-level flow by regional thermal lows and South American Low Level Jet events. Regional HWs often migrate from northern to central-eastern SSA and central Argentina, following the displacement/intensification of the South Atlantic High, which partially explains the similarity of their associated patterns
Construction of a daily precipitation grid for southeastern South America for the period 1961-2000
No full textDaily station precipitation totals are used to develop a gridded dataset for the region (14°–40°S, 45°–70°W) on a 0.5° × 0.5° latitude/longitude grid, primarily for comparison with regional climate model (RCM) simulations. The gridded dataset covers the period 1961–2000. Much of the paper discusses the quality control of the basic station precipitation series. Although the primary aim of the development has been RCM validation, we have assessed trends in seasonal precipitation totals as well as trends in two measures of precipitation extremes (R95p, the daily precipitation amount exceeded only 5% of the time and Rx5day, the maximum 5-d precipitation total during each season). Relatively few regions across the large domain have statistically significant trends, but those that do tend to be located in the eastern two thirds of the grid, particularly over southeastern Brazil and Uruguay. Significant trends are also more evident in the DJF and MAM seasons. There is good spatial agreement between the trends in seasonal totals and trends in the extreme indices.Fil: Jones, P. D.. University Of East Anglia; Reino UnidoFil: Lister, D. H.. University Of East Anglia; Reino UnidoFil: Harpham, C.. University Of East Anglia; Reino UnidoFil: Rusticucci, Matilde Monica. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Ciencias de la Atmósfera y los Océanos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Rusticucci, Matilde Monica. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Ciencias de la Atmósfera y los Océanos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin
Propiedades y procesos dominantes de una serie cuatridiurna de temperatura
No full textSe estudia la serie de temperaturas cuatridiurnas (hora 02, 08 14 y 20), de la estación Ezeiza (34° 49'S, 59° 32'W) en el período 1968-1980, con el objetivo final de obtener un diagnóstico que pueda servir a posteriori para el ajuste de un modelo de pronóstico para la serie. Se investiga el grado de variabilidad o contribución a la serie que introducen los meses, las horas y los años.
Los procesos estadísticos dominantes en las series, sean estas cuatridiurnas o diarias, son esencialmente Markovianos, según lo detecta la estimación de las funciones de autocorrelación y espectros de poder. Como se postula que la serie filtrada cuatridiurna puede describirse mediante un mismo proceso, se estudia el espectro hora a hora con el objeto de medir la homogeneidad. Se encuentra que las causas de inhomogeneidad serían provocadas por ondas mayores que 14 días.
En función de todas las propiedades que la serie presenta, es factible suponer que un modelo autorregresivo puede ser ajustado con fines de diagnóstico y pronóstico.The series of quartan temperatures of the station Ezeiza (34° 49'S, 59° 32'W) in the period 1968-1980 is being studied, with the final aim to obtain a diagnostic model for the series. The degree of variability or contribution to the series introduced by months, hours and years is being investigated.
The statistic processes dominant in the series, be these quartan or daily, are essentially Markovian, according is being revealed by the estimation of the functions of autocorrelation and power spectra. As it is being postulated that the filtered quartan series can be described by means of the same process, the spectrum is being studied hour by hour with the aim to measure homogeneity. It is found that the un-homogeneity is caused by waves longer than a fortnigth.
Based on the properties of the series, it is possible to assume that an autorregressive model can be adjusted for diagnostic and forecasting purposes.Asociación Argentina de Geofísicos y Geodesta
Variabilidad cada seis horas de la temperatura de superficie
No full textEn este trabajo se estudia el comportamiento del cambio de la temperatura cada seis horas en una estación ubicada en la periferia de la ciudad de Buenos Aires. Ese cambio se representa con la "diferencia" de temperatura en seis horas.
Se observa mayor cantidad de calentamientos que de enfriamientos pero de menor intensidad. Todas las distribuciones presentan una leve asimetría.
Estas "diferencias" pertenecen a ondas de período muy corto, lo que muestra que estos procesos se debilitan rápidamente.
En el análisis de valores extremos absolutos, se nota que su ocurrencia tiene horas preferenciales, a pesar de estar filtradas las ondas astronómicas. Es en el intervalo entre las 08 y las 14 donde se producen los mayores calentamientos y enfriamientos.The behavior of the temperature change each six hours, in a station near the city of Buenos Aires is studied. This change is explained by the difference between 6-hourly temporatures.
The distributions are slightly assimetric because there are more heatings than coolings but less intense.
It can be seen that those "differences" belong to short waves. They show that the processes weaken quickly.
A preferent interval occured in the absolute extrem values analysis, in spite of the astronomics waves have been filtered. The mayor heatings and coolings are produced between 08:00 and 14:00.Asociación Argentina de Geofísicos y Geodesta
Efecto de la ciudad y el rio sobre la temperatura de superficie en Buenos Aires
No full textEl objetivo de este trabajo es estudiar algunas estructuras climáticas de la temperatura y las perturbaciones provocadas por la ubicación de las estaciones. Se toman tres estaciones en las inmediaciones y dentro de la ciudad de Buenos Aires. y se analizan las temperaturas de las horas 02:00, 08:00, 14:00 y 20:00. Se muestra que la influencia de la dirección del viento en la manifestación de los efectos de la ciudad o el río en la temperatura, depende de la hora y de la época del año. Sin embargo la estación de referencia no está influenciada por la ciudad, en la mayoría de las veces. El efecto de la ciudad sobre los promedios de temperatura, es máximo en horas de la noche. La influyencia del río, en cambio, es más notable a las 14:00. Ambos efectos se reflejan sobre la distribución de las anomalías de las estaciones estudiadas. Los procesos que dominan estas series son más homogéneos entre estaciones, si se consideran las temperaturas diarias.The alm of this paper is to study the effect of the station location on the six-hourly temperatures climatic structures. The observed temperature (at 02:00. 08:00, 14:00, 20:00, local time), for three stations within the metropolitan area of Buenos Aires, is studied. Local influences depend on the day time and the season. In the analysis of the wind direction, in most oí the situations the reference station is not influenced by the city. The urban effect is maximum al night hours and the river influence is maximum at 14:00. Both effects are still present in the anomalies frequency distribution. The daily anomalies processes are more homogeneous than the six-hourly ones between stations.Asociación Argentina de Geofísicos y Geodesta
Propiedades y procesos dominantes de una serie cuatridiurna de temperatura
No full textSe estudia la serie de temperaturas cuatridiurnas (hora 02, 08 14 y 20), de la estación Ezeiza (34° 49'S, 59° 32'W) en el período 1968-1980, con el objetivo final de obtener un diagnóstico que pueda servir a posteriori para el ajuste de un modelo de pronóstico para la serie. Se investiga el grado de variabilidad o contribución a la serie que introducen los meses, las horas y los años.
Los procesos estadísticos dominantes en las series, sean estas cuatridiurnas o diarias, son esencialmente Markovianos, según lo detecta la estimación de las funciones de autocorrelación y espectros de poder. Como se postula que la serie filtrada cuatridiurna puede describirse mediante un mismo proceso, se estudia el espectro hora a hora con el objeto de medir la homogeneidad. Se encuentra que las causas de inhomogeneidad serían provocadas por ondas mayores que 14 días.
En función de todas las propiedades que la serie presenta, es factible suponer que un modelo autorregresivo puede ser ajustado con fines de diagnóstico y pronóstico.The series of quartan temperatures of the station Ezeiza (34° 49'S, 59° 32'W) in the period 1968-1980 is being studied, with the final aim to obtain a diagnostic model for the series. The degree of variability or contribution to the series introduced by months, hours and years is being investigated.
The statistic processes dominant in the series, be these quartan or daily, are essentially Markovian, according is being revealed by the estimation of the functions of autocorrelation and power spectra. As it is being postulated that the filtered quartan series can be described by means of the same process, the spectrum is being studied hour by hour with the aim to measure homogeneity. It is found that the un-homogeneity is caused by waves longer than a fortnigth.
Based on the properties of the series, it is possible to assume that an autorregressive model can be adjusted for diagnostic and forecasting purposes.Asociación Argentina de Geofísicos y Geodesta
The international surface temperature initiative's global land surface databank
No full textThe International Surface Temperature Initiative (ISTI) consists of an end-to-end process for land surface air temperature analyses. The foundation is the establishment of a global land surface Databank. This builds upon the groundbreaking efforts of scientists in the 1980s and 1990s. While using many of their principles, a primary aim is to improve aspects including data provenance, version control, openness and transparency, temporal and spatial coverage, and improved methods for merging disparate sources. The initial focus is on daily and monthly timescales. A Databank Working Group is focused on establishing Stage-0 (original observation forms) through Stage-3 data (merged dataset without quality control). More than 35 sources of data have already been added and efforts have now turned to development of the initial version of the merged dataset. Methods have been established for ensuring to the extent possible the provenance of all data from the point of observation through all intermediate steps to final archive and access. Databank submission procedures were designed to make the process of contributing data as easy as possible. All data are provided openly and without charge. We encourage the use of these data and feedback from interested users.Fil: Lawrimore, J. H.. National Oceanic and Atmospheric Administration; Estados UnidosFil: Rennie, J.. Nansen Environmental and Remote Sensing Center; NoruegaFil: Gambi de Almeida, W.. Centro de Previsao de Tempo e Estudos Climáticos. Instituto Nacional de Pesquisas Espaciais; BrasilFil: Christy, J.. University of Alabama; Estados UnidosFil: Flannery, M.. Bureau of Meteorology; AustraliaFil: Gleason, B.. National Oceanic and Atmospheric Administration; Estados UnidosFil: Klein Tank, A.. Royal Netherlands Meteorological Institute; Países BajosFil: Mhanda, A.. frican Centre of Meteorological Applications for Development; NigeriaFil: Ishihara, K.. Japan Meteorological Agency; JapónFil: Lister, D.. Climatic Research Unit; Reino UnidoFil: Menne, M. J.. National Oceanic and Atmospheric Administration; Estados UnidosFil: Razuvaev, V.. Russian Research Institute of Hydrometeorological Information; RusiaFil: Renom, M.. Universidad de la República; UruguayFil: Rusticucci, Matilde Monica. Universidad de Buenos Aires; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Tandy, J.. Met Office Hadley Centre; Reino UnidoFil: Thorne, P. W.. Nansen Environmental and Remote Sensing Center; NoruegaFil: Worley, S.. National Center for Atmospheric Research; Estados Unido
Efecto de la ciudad y el rio sobre la temperatura de superficie en Buenos Aires
No full textEl objetivo de este trabajo es estudiar algunas estructuras climáticas de la temperatura y las perturbaciones provocadas por la ubicación de las estaciones. Se toman tres estaciones en las inmediaciones y dentro de la ciudad de Buenos Aires. y se analizan las temperaturas de las horas 02:00, 08:00, 14:00 y 20:00. Se muestra que la influencia de la dirección del viento en la manifestación de los efectos de la ciudad o el río en la temperatura, depende de la hora y de la época del año. Sin embargo la estación de referencia no está influenciada por la ciudad, en la mayoría de las veces. El efecto de la ciudad sobre los promedios de temperatura, es máximo en horas de la noche. La influyencia del río, en cambio, es más notable a las 14:00. Ambos efectos se reflejan sobre la distribución de las anomalías de las estaciones estudiadas. Los procesos que dominan estas series son más homogéneos entre estaciones, si se consideran las temperaturas diarias.The alm of this paper is to study the effect of the station location on the six-hourly temperatures climatic structures. The observed temperature (at 02:00. 08:00, 14:00, 20:00, local time), for three stations within the metropolitan area of Buenos Aires, is studied. Local influences depend on the day time and the season. In the analysis of the wind direction, in most oí the situations the reference station is not influenced by the city. The urban effect is maximum al night hours and the river influence is maximum at 14:00. Both effects are still present in the anomalies frequency distribution. The daily anomalies processes are more homogeneous than the six-hourly ones between stations.Asociación Argentina de Geofísicos y Geodesta
Variabilidad cada seis horas de la temperatura de superficie
No full textEn este trabajo se estudia el comportamiento del cambio de la temperatura cada seis horas en una estación ubicada en la periferia de la ciudad de Buenos Aires. Ese cambio se representa con la "diferencia" de temperatura en seis horas.
Se observa mayor cantidad de calentamientos que de enfriamientos pero de menor intensidad. Todas las distribuciones presentan una leve asimetría.
Estas "diferencias" pertenecen a ondas de período muy corto, lo que muestra que estos procesos se debilitan rápidamente.
En el análisis de valores extremos absolutos, se nota que su ocurrencia tiene horas preferenciales, a pesar de estar filtradas las ondas astronómicas. Es en el intervalo entre las 08 y las 14 donde se producen los mayores calentamientos y enfriamientos.The behavior of the temperature change each six hours, in a station near the city of Buenos Aires is studied. This change is explained by the difference between 6-hourly temporatures.
The distributions are slightly assimetric because there are more heatings than coolings but less intense.
It can be seen that those "differences" belong to short waves. They show that the processes weaken quickly.
A preferent interval occured in the absolute extrem values analysis, in spite of the astronomics waves have been filtered. The mayor heatings and coolings are produced between 08:00 and 14:00.Asociación Argentina de Geofísicos y Geodesta
Central and South America
No full textThe chapter is divided into two main sections. The first section follows an integrative approach in which hazards, exposure, vulnerability, impacts and risks are discussed following the eight climatically homogeneous sub-regions described in WGI AR6 (Figure 12.1). The second section assesses the implemented and proposed adaptation practices by sector; in doing so, it connects to the WGII AR6 crosschapter themes. The storyline is then a description of the hazards, exposure, vulnerability and impacts providing as much detail as is available in the literature at the sub-regional level, followed by the
identification of risks as a result of the interaction of those aspects. This integrated sub-regional approach ensures a balance in the text, particularly for countries that are usually underrepresented in the literature but that show a high level of vulnerability and impacts, such as those observed in CA. The sectoral assessment of adaptation that follows is useful for policymakers and implementers, usually focused and organised by sectors, government ministries or secretaries that can easily locate the relevant adaptation information for their particular sector. To ensure coherence in the chapter, a summary of the assessed adaptation options by key risks is presented, followed by a feasibility assessment for some relevant adaptation options. The chapter closes
with case studies and a discussion of the knowledge gaps evidenced in the process of the assessment.EEA Santa CruzFil: Castellanos, Edwin J. Universidad del Valle de Guatemala; Guatemala.Fil: Lemos, Maria Fernanda. Pontifical Catholic University of Rio de Janeiro; Brasil.Fil: Astigarraga, Laura. Universidad de la República; Uruguay.Fil: Chacón, Noemí. Instituto Venezolano de Investigaciones Científicas; Venezuela.Fil: Cuvi, Nicolás. Facultad Latinoamericana de Ciencias Sociales (FLACSO); Ecuador.Fil: Huggel, Christian. University of Zurich; Switzerland.Fil: Miranda Sara, Liliana Raquel. Foro Ciudades para la Vida; Peru.Fil: Moncassim Vale, Mariana. Federal University of Rio de Janeiro; Brasil.Fil: Ometto, Jean Pierre. National Institute for Space Research; Brasil.Fil: Peri, Pablo Luis. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Santa Cruz; Argentina.Fil: Peri, Pablo Luis. Universidad Nacional de la Patagonia Austral; Argentina.Fil: Peri, Pablo Luis. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.Fil: Postigo, Julio C. Indiana University; Estados Unidos.Fil: Ramajo Gallardo, Laura. Adolfo Ibanez University; Chile.Fil: Roco, Lisandro. Catholic University of The North; Chile.Fil: Rusticucci, Matilde Monica. Universidad de Buenos Aires; Argentina
- …
