Climatology of Air Temperature in Belterra: Thermal Regulation Ecosystem Services Provided by the Tapajós National Forest in the Amazon

The Tapajós National Forest (Flona Tapajós) has been providing important ecosystem services to society since the creation of this Conservation Unit in the Amazon. This study analyzed two climatic series from Belterra to identify possible effects on the thermal regime in the municipality as a function of the proximity of the Flona Tapajós and the consolidated grain production center in western Pará. Two climatological normal datasets from the National Institute of Meteorology (INMET) were analyzed (1961-1990 and 1981-2010). Analysis of variance was used to compare averages, extremes (minimums and maximums), and thermal amplitudes. Average temperature was 24.6 °C in the first semester (1961-1990) and 25.2 °C (1981-2010), with maximums of 29.4 °C and 29.9 °C, and minimums of 20.6 and 21.2 °C, respectively. There were no statistical differences in these comparisons. In the second semester the averages increased to 25.2 °C and 26.0 °C, and were statistically different, with maximums of 31.2 °C and 31.6 °C and minimums of 20.4 °C and 21.2 °C, indicating different thermal regimes during 1981-2010. Additionally, from October to December the nights were warmer. The Flona Tapajós may have experienced a reduction in provision of ecosystem services, and the increase in minimum temperatures could be associated with grain production activities in the region.

Precipitação e temperatura do ar simuladas pelo modelo ETA/CPTEC - HADCM3 para o estado do Rio de Janeiro

O trabalho avaliou simulações de precipitação e temperatura do ar do modelo Eta-CPTEC para o Rio de Janeiro de 1961-1990. Nas simulações, considerou-se resolução espacial de 40 km para uma grade que compreendeu a América do Sul, com o Eta-CPTEC inicializado com o modelo HadCM3. As séries climáticas observadas das variáveis estudadas foram obtidas de estações meteorológicas do INMET distribuídas no estado do Rio de Janeiro. Estas séries foram comparadas com aquelas extraídas dos pontos de grade do modelo mais próximas das estações. Nas avaliações considerou-se o coeficiente de determinação (r²) da regressão linear simples entre dados observados e simulados; o índice de concordância de Willmott (d), o índice de desempenho (c) e a Raiz do Quadrado Médio do Erro (RQME) e seus componentes sistemático (RQMEs) e não sistemático (RQMEu). As simulações de precipitação apresentaram r² menores do que 0,32, o que indicou baixa precisão, enquanto que a exatidão (d) foi superior a 0,50, com exceção de Bangu (0,16). A baixa precisão comprometeu o desempenho (c) das simulações, com 0,07 <= c <= 0,42, classificados entre “péssimo” e “ruim”. A RQME variou entre 76,2 e 133,4 mm, que correspondeu a um erro de 78,1 e 115,5% em relação à precipitação média. As simulações de temperatura do ar mostraram desempenho melhor do que a precipitação, com maior precisão (0,39 <= r² <= 0,53), exatidão (0,50 <= d <= 0,79) e desempenho (0,36 <= c <= 0,52). A RQME ficou entre 1,9 e 5,7oC, representando 9 e 26% da média da temperatura do ar. Na maior parte das estações, o RQMEs se sobressaiu em relação ao RQMEu, indicando que as simulações podem ser corrigidas usando técnicas estatísticas. Precipitation and air temperature numerical simulations through ETA/CPTEC - HADCM3 model in Rio de Janeiro A B S T R A C TThe present study evaluated the precipitation and air temperature simulations of the Eta-CPTEC model for Rio de Janeiro state in 1961-1990. In the simulations, a spatial resolution of 40 km was considered for a grid that comprised South America, with Eta-CPTEC initialized with HadCM3 model. The observed climatic series of the studied variables were obtained from INMET meteorological stations distributed at Rio de Janeiro state. These series were compared with those extracted from the grid points of the model near to the stations. The coefficient of determination (r²) of the simple linear regression between observed and simulated, Willmott's index of agreement (d), performance index (c), Root Mean Square Error (RQME) and their systematic (RQMEs) and unsystematic (RQMEu) components were considered in the evaluations. The precipitation simulations showed r² less than 0.32, which indicated low precision, while the accuracy (Willmott's d) was greater than 0.50, except for Bangu station. The low precision compromised the performance (index “c”) of the simulations, with 0,07 £ c £ 0,42, classified as "terrible" and "bad". The RQME varied between 76.2 and 133.4 mm, which corresponded error of 78.1 and 115.5% in relation to mean precipitation. The simulations of air temperature showed better performance than precipitation, with greater precision (0.39 £ r² £ 0.53), accuracy (0.50 £ d £ 0.79) and performance (0.36 £ c £ 0.52). The RQME was between 1.9 and 5.7oC, which represented respectively 9 and 26% for average of air temperature. In most stations, RQMEs were higher than the RQMEu, which indicated that simulators can be fitted using statistical techniques.Keywords: climate model, meteorological dataset, downscaling

An overview on isotopic divergences – causes for instability of tree-ring isotopes and climate correlations

Climatic reconstructions based on tree-ring isotopic series convey substantial information about past conditions prevailing in forested regions of the globe. However, in some cases, the relations between isotopic and climatic records appear unstable over time, generating the “isotopic divergences”. Former reviews have thoroughly discussed the divergence concept for tree-ring physical properties but not for isotopes. Here we want to take stock of the isotopic divergence problem, express concerns and stimulate collaborative work for improving paleoclimatic reconstructions. There are five main causes for divergent parts in isotopic and climatic series: (1) artefacts due to sampling and data treatment, relevant for dealing with long series using sub-fossil stems; (2) stand dynamics, including juvenile effects mostly occurring in the early part of tree-ring series; (3) rise in atmospheric pCO2, which can directly influence the foliar behaviour; (4) change in climate, which may modify the isotope–climate causal links; and finally (5) atmospheric pollution, which may alter leaf and root functions. Future paleoclimate research would benefit from interdisciplinary efforts designed to develop further process-based models integrating multi-proxy inputs so as to help identify causes of isotopic divergences and circumvent some of them in inverse applications.

An Overview on Isotopic Divergences – Causes for instability of Tree-Ring Isotopes and Climate Correlations

Climatic reconstructions based on tree-ring isotopic series convey substantial information about past conditions prevailing in forested regions of the globe. However, in some cases, the relations between isotopic and climatic records appear unstable over time, generating the ‘isotopic divergences’. Former reviews have thoroughly discussed the divergence concept for tree-ring physical properties, but not for isotopes. Here we want to take stock of the isotopic divergence problem, express concerns and stimulate collaborative work for improving paleoclimatic reconstructions. There are five main causes for divergent parts in isotopic and climatic series. (1) Artefacts due to sampling and data treatment, relevant for dealing with long-series using sub-fossil stems. (2) Stand dynamics, including juvenile effects mostly occurring in the early part of tree-ring series. (3) Rise in atmospheric pCO2, which can directly influence the foliar behaviour. (4) Change of climate, which may modify the isotope-climate causal links. Finally (5), atmospheric pollution, which may alter leaf and root functions. Future paleoclimate research would benefit from interdisciplinary efforts designed to develop further process-based models integrating multi-proxy inputs, so to help identify causes of isotopic divergences and circumvent some of them in inverse applications.

The crucial boundaries in the development of the late cretaceous biota of plankton foraminifers in the southern part of the Indian ocean

The article analyzes own data on the species composition of shells of planktonic foraminifera from the Upper Cretaceous sediments of the Indian Oceans, as well as from the sections of the offshore seas of Australia. The species of planktonic foraminifera are grouped and arranged in a climatic series. An analysis of the change in the systematic composition of foraminifers made it possible to distinguish periods of extreme and intermediate climatic states in the Late Cretaceous.

Cuantificación de la recarga de agua en el sistema de riego Catarama mediante Modelo Renata

Cuantification of Catarama irrigation system recharge by Renata Model Resumen El objetivo de la investigación es cuantificar la recarga de agua generada en el sistema de riego Catarama (Cuenca del río Catarama) perteneciente a la provincia de Los Ríos (Ecuador), mediante la aplicación del modelo numérico RENATA (Recarga NATural a los Acuíferos) desarrollado por el Instituto Geológico y Minero de España (IGME) y la Diputación de Alicante. En el estudio se calculan los volúmenes de agua que son generados por la infiltración ocasionada por la lluvia y por el retorno de riego proveniente de las dotaciones de agua asignadas a los diferentes cultivos existentes en la zona. Para la determinación de la recarga se consideraron diferentes variables climáticas influyentes como precipitación, temperatura, evapotranspiración potencial y real; así como las diferentes características de los suelos del sector. A partir de estas variables RENATA pudo generar los resultados de la modelación en el sistema de riego, en base a los datos obtenidos de series climáticas mensuales correspondientes al periodo enero 2005 - diciembre 2014, obteniendo durante este tiempo una recarga teórica de 57,139 Hm3 en un área total aproximada de 6047 ha. Palabras clave: RENATA; variable; precipitación; recarga; infiltración; riego. Abstract In this article, the water recharge in the Catarama irrigation system (Catarama river basin), Los Ríos, Ecuador is quantified through the application of the RENATA numerical model (Natural Aquifer recharge) developed by the Instituto Geológico y Minero de España (IGME) and Diputación de Alicante. The study calculates the volumes of water generated by the infiltration caused by rainfull and the return of irrigation from the water assigned to the different crops in the area. To determine the recharge, different influential climatic variables were considered: precipitation, temperature, potential and the current evapotranspiration; as well as the different characteristics of the sector’s soils. From these variables, RENATA was able to generate the results of the irrigation system modeling, based on the data obtained from monthly climatic series corresponding to the period January 2005 - December 2014, getting during this time a theoretical recharge of 57,139 Hm3, in an approximate total area of 6047 ha. Keywords: RENATA; Variable; Precipitation; Recharge; Infiltration; Irrigation.

Cloud Changes in the Period of Global Warming: the Results of the International Satellite Project

The results of analysis of climatic series of global and regional cloudiness for 1983–2009. Data were obtained in the framework of the international satellite project ISCCP. The technology of statistical time series analysis including smoothing algorithm and wavelet analysis is described. Both methods are intended for the analysis of non-stationary series. The results of the analysis show that both global and regional cloudiness show a decrease of 2–6%. The greatest decrease is observed in the tropics and over the oceans. Over land, the decrease is minimal. The correlation coefficient between the global cloud series on the one hand and the global air and ocean surface temperature series on the other hand reaches values (–0.84) — (–0.86). The coefficient of determination that characterizes the accuracy of the regression for the prediction of global temperature changes based on data on changes in the lower cloud, in this case is 0.316.

R-Package <tt>BIOdry</tt>: DendroClimatic Modeling from Multilevel Ecological Data Series

R-package BIOdry is developed to consider ecological factors in dendroclimatic modeling of forest ecosystems. The package processes Multilevel ecological data series (MEDS) with two functions: modelFrame and muleMan. These integrate techniques for modeling Tree-rings in wood (TRW) chronologies and climatic series at specific ecological-factor levels (one-level modeling), developing multilevel analysis (mixed-effects detrending), and implementing multivariate comparison of MEDS. Several one-level functions for serial synchronization, drought modeling and allometric scaling are implemented to model tree-diameter growth and drought of Iberian pine forests (Pinus pinaster Ait.). Trends in the dendroclimatic MEDS are subtracted with in-package detrending methods. Extracted fluctuations are normalized with lme methods. Finally, enhancements in dendroclimatic modeling by accounting for ecological factors are tested. We conclude that BIOdry package is an useful tool for studying complex ecological time-space relationships.

Trend analysis of climatic variables in an arid and semi-arid region of the Ajmer District, Rajasthan, India

In the present study, trends and variations in climatic variables (i.e. rainfall, wet day frequency, surface temperature, diurnal temperature, cloud cover, and reference and potential evapotranspiration) were analyzed on seasonal (monsoon and non-monsoon) and annual time scales for the Ajmer District of Rajasthan, India. This was done using non-parametric statistical techniques, i.e. the Mann–Kendall (MK) and Modified Mann–Kendall (MMK) tests, over a period of 100 years. The MK test with prewhitening (MK–PW) of climatic series was also applied to climatic variables and the results were compared to those obtained through the MK and MMK tests in order to assess the performance of trend detection methods. The Pettitt–Mann–Whitney (PMW) test was applied to detect the temporal shift in climatic series. The trend analysis revealed that annual and seasonal rainfall did not show any statistically significant trend at a 10% significant level. A noticeable trend increase was found in wet day frequency, surface temperature and reference evapotranspiration (ET) during the non-monsoon season from the three non-parametric statistical tests at a 10% significance level. A statistically significant decrease in maximum temperature was found during the non-monsoon season by the MK–PW test alone. This analysis of several climatic variables at the district scale is helpful for the planning and management of water resources and the development of adaptation strategies in adverse climatic conditions.