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Abstract: Eddy covariance measurements were carried out at the Wetzstein site in Thuringia, Germany since December 2001. Soon after the start of the measurements night-time fluxes well above average CO2-fluxes measured in temperate forest ecosystems were detected which could not be explained by biological processes but were valid with respect to standard quality criteria. The Wetzstein site is part of the CarboEurope-IP flux-network and the CO2-exchange of this spruce forest is of general ecological interest as the site is typical for central European spruce forest ecosystems at mountainous elevation. Additional investigations were made in order to identify the causes for the large difference between the flux balance and the inventory based NEP. Specific weather patterns and micrometeorological situations were identified during which a decoupling of the flows above and below the canopy leads to additional CO2-effluxes at the tower site which are not part of the net ecosystem exchange (NEE) at night. Rejecting data from these periods and gap-filling thereafter results in yearly sums of NEE, GPP and TER which are in better agreement with the biometric measurements at the tower site and comparable to other spruce forest sites. In this process ecosystem respiration was determined not only from extrapolation of night-time data but also from flux partitioning based on day-time data using the hyperbolic light response function. It can be shown that flux measurements at this complex site need to be treated in a modified procedure compared to what is generally performed, namely extrapolating ecosystem respiration from night-time data. Using multiple data sources and applying a careful filtering of the data, confidence in the estimates of the carbon balance components increased. [Copyright &y& Elsevier]

The Fluxpart partitioning model was employed to assess transpiration, photosynthesis and evaporation, respiration based exclusively through high-frequency eddy covariance (EC) data. The model was implemented across three sites with two vegetation cover conditions (dense and sparse) during the drought episode between 2012 and 2015 in the Caatinga biome in Northeast Brazil. Fluxpart, an open-source Python software, partitions data by analyzing the flux variance similarity (FVS) relationship and conducting correlation analyses of EC data. The main contribution to the evapotranspiration (ET) process was transpiration (T), representing about 64 and 67% of the amount ET in areas with dense and sparse vegetation cover, respectively. When the Caatinga biome is in a good state of conservation, it behaves as a carbon sink; the net ecosystem exchange average was −6 g C m−2 day−1 (gram of carbon per square meter daily) for dense vegetation and 3 g C m−2 day−1 for sparse vegetation. Through ET, vapor pressure deficit (VPD), and gross primary production (GPP) via Fluxpart, an assessment was made concerning the underlying water use efficiency (uWUE) to understand the nonlinear effects of VPD on the carbon-water coupling at the ecosystem scale. The overvalues of 60 g C hPa0.5 kg−1 H 2 O−1 (grams of carbon times square root of hectopascals per kilogram of water) prevailing in the rainy season and below 20 g C hPa0.5 kg−1 H 2 O−1 were mostly in the dry season. uWUE was an important indicator of the ability of the Caatinga biome to optimize water loss and carbon gain according to the water available in the soil-plant-atmosphere system to withstand water stress, especially at dense vegetation covers. • The fluxpart model was used to partition water and carbon dioxide fluxes in a Brazilian seasonally dry tropical forest. • Transpiration was the main component of evapotranspiration in areas of dense vegetation covers. • Caatinga biome behaved as a carbon sink when in a good conservation state. • Underlying water use efficiency (uWUE) was an indicator of the Caatinga's ability to optimize water loss and carbon gain. [ABSTRACT FROM AUTHOR]

Abstract Drought indices allow for the characterization of drought events, being the most widely used the Standardized Precipitation Index (SPI), which is recommended by the World Meteorological Organization (WMO) as the standard drought index. The objectives of this study are: i) to characterize the variation of annual SPI index in the state of Rio de Janeiro from 1979 to 2009; ii) to relate ENSO events with the variation of the annual SPI; iii) to identify possible significant trends of rainfall increase and reduction based on the annual SPI; and iv) characterize drought evolution in the SRJ in the 1979–2009 period (Appendix A). For the SPI calculation, a monthly time series with 31 consecutive years was used, based on rainfall data from 99 rainfall stations distributed in eight government regions. Annual SPI data was presented using maps created with ArcGIS software version 10.2.2 and all statistical procedures were calculated in the R environment software. The Shapiro-Wilk (SW) and Bartlett (B) tests characterized rainfall data as being mostly normal and non-homogeneous. The annual SPI showed that the Center South region experienced the highest continuous dry period between 1999 and 2000 and 2002–2003. The annual SPI was assessed with the Mann-Kendall (MK), Curvature Sen (magnitude) and Pettitt (abrupt inflection) tests. The MK test indicated significant trends of annual rainfall increase in the North and Mountainous regions, and significant reduction trends in the Mountainous and Center South regions. Pettitt's test indicated significant abrupt changes in the North, Center South and Mountainous regions. The Curvature Sen test revealed that stations Dois Rios (North) and Cordeiro (Mountainous) registered a greater magnitude in the increase and reduction of the annual SPI, respectively. Graphical abstract Unlabelled Image Highlights • The SPI index is an important tool in the spatiotemporal characterization of drought in the state of Rio de Janeiro. • Events of ENSO were not directly related to the increase or reduction of rainfall in any of the regions of the state. • The influence of ENSO seems to be less representative in terms of rainfall regime alteration in Rio de Janeiro. • Significant trends of annual SPI increase and reduction were identified in regions Center south, Mountainous and North. [ABSTRACT FROM AUTHOR]

Abstract: Extensive field measurements have been performed at three CarboEurope-Integrated Project forest sites with different topography (Renon/Ritten, Italian Alps, Italy; Wetzstein, Thuringia, Germany; Norunda, Uppland, Sweden) to evaluate the relevant terms of the carbon balance by measuring CO2 concentrations [CO2] and the wind field in a 3D multi-tower cube setup. The same experimental setup (geometry and instrumentation) and the same methodology were applied to all the three experiments. It is shown that all sites are affected by advection in different ways and strengths. Everywhere, vertical advection (F VA) occurred only at night. During the day, F VA disappeared because of turbulent mixing, leading to a uniform vertical profile of [CO2]. Mean F VA was nearly zero at the hilly site (Wetzstein) and at the flat site (Norunda). However, large, momentary positive or negative contributions occurred at the flat site, whereas vertical non-turbulent fluxes were generally very small at the hilly site. At the slope site (Renon), F VA was always positive at night because of the permanently negative mean vertical wind component resulting from downslope winds. Horizontal advection also occurred mainly at night. It was positive at the slope site and negative at the flat site in the mean diurnal course. The size of the averaged non-turbulent advective fluxes was of the same order of magnitude as the turbulent flux measured by eddy-covariance technique, but the scatter was very high. This implies that it is not advisable to use directly measured quantities of the non-turbulent advective fluxes for the estimation of net ecosystem exchange (NEE) on e.g. an hourly basis. However, situations with and without advection were closely related to local or synoptic meteorological conditions. Thus, it is possible to separate advection affected NEE estimates from fluxes which are representative of the source term. However, the development of a robust correction scheme for advection requires a more detailed site-specific analysis of single events for the identification of the relevant processes. This paper presents mean characteristics of the advective CO2 fluxes in a first site-to-site comparison and evaluates the main problems for future research. [Copyright &y& Elsevier]

Extreme rainfall events are likely to become more frequent according to recent scenarios of climate change. This issue is especially important over regions with complex topography, which enhances rainfall variability when associated with weather patterns. The state of Rio de Janeiro (SRJ), southeastern Brazil, is characterized by altitudes ranging from the mean sea level up to 2500 m.a.s.l, in mountain ranges and valleys covering significant parts of the region. Time series data of annual maximum daily rainfall were obtained from 110 stations with a data coverage of at least 20 years, from 1960 to 2010. The Probability Distribution Functions (PDFs) normal, log-normal, exponential, gamma, Gumbel, Weibull, and Generalized Extreme Value (GEV) were fitted to maximum rainfall series. Goodness-of-fit tests (Chi-squared - χ2 and Anderson-Darling) revealed that the Gumbel, GEV, and log-normal were found to be the best choices. However,the Gumbel and GEV PDFs were the best ranking by the χ2 and Anderson-Darling test, respectively. Extreme rainfall events with different recurrence intervals (5, 10, 25, 50 and 100 years) were calculated based on the Gumbel and GEV Cumulative Distribution Function (CDF). The differences between extreme values from Gumbell and GEV function increased as the shape parameter increases from zero, with higher probability and extreme value. Five regions with homogeneous patterns of extreme rainfall were identified using clustering analysis (Ward's method) and different recurrence intervals. Overall, the regions with higher values of extreme rainfall in all scenarios and CDFs were the ones close to the coast, within 40 km, and south of Serra dos Órgãos mountain range, located in the middle of the state. The mountain range separates the state in two halves, concentrating higher values of extreme rainfall in the lower part, where the city of Rio de Janeiro, the state's capital, is located. Scenarios for both CDF (GEV and Gumbel) indicated daily rainfall events up to 200 mm, with recurrence intervals of 50 to 100 years. In addition, the southernmost part of the state is subjected to rainfall extremes up to 260 mm in scenarios of 50 to 100 years of recurrence interval. This region, and the state's capital, are characterized by complex topography and a high fraction of population living in slums over hills, or lowlands near the ocean, increasing the vulnerability to events such as landslides and floods associated with extreme rainfall. Unlabelled Image • Seven probability distribution functions were fitted to annual maximum daily rainfall series in Rio de Janeiro State, Brazil • The best-fit distributions (Gumbel and GEV) were used to estimate extreme rainfall with different recurrence intervals • The cluster analysis and spline tension method were applied to assess the spatial patterns of the extreme rainfall • The regions with higher extreme rainfall were close to the coast and south of mountains located in the middle of the State • In these regions, extreme daily rainfall range between 200 and 300 mm, with return times of 50 to 100 years were expected [ABSTRACT FROM AUTHOR]

Climate Data analysis has become a fundamental tool for scientists who seek to better evaluate changes in climatic variables worldwide. When it comes to rainfall there are many datasets publicly available, and orbital products have been gradually sharpening its results. The Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks - Climate Data Record (PERSIANN-CDR) annual product is used in this study to characterize rainfall variation over the state of Rio de Janeiro (SRJ), considering the period of 1983 to 2017. A rainfall dataset with 35 year long series for each of the 92 municipalities of the SRJ was created using GIS software. Several statistical tests were then applied to the datasets of each municipality in order to verify normality (Shapiro-Wilk, Anderson-Darling, Lilliefors and Jarque-Bera), homogeneity (Pettitt, SNHT, Buishand and von Neumann), trends (Mann-Kendall) and intensity (Şen) of reduction or increase in annual rainfall. The estimated rainfall datasets were classified mainly as normal and homogenous (non-significant breakpoints), but significant breakpoints were registered by the Buishand's test in the dataset of twenty seven (29.34%) municipalities. Twenty municipalities had their estimated datasets compared to local meteorological stations in order to verify PERSIANN-CDR performance over the SRJ. Municipalities in the Middle Paraíba and Center South regions are the wettest of the state, while locations that presented lower average annual rainfalls in the state are concentrated in the North, Coastal Flats and Northwest regions. Alarming trends of reduction in annual rainfall were identified for all municipalities using the MK test, but to the threshold of 95% reliability, results show fifty four (58.69%) municipalities located in the central and western parts of the SRJ. According to Şen ´s test the intensity of annual rainfall reduction is greater in municipalities of the Middle Paraíba and Green Coast regions, but Center South, Metropolitan and Coastal Flats regions also registered disquieting results. PERSIANN-CDR analysis can be considered an efficient methodology in the characterization of rainfall variability and trend detection for the SRJ, being encouraged for future studies addressing rainfall and drought variability over the state. The analysis of the PERSIANN-CDR products should also be applied in other regions of the country, especially considering the remarkable interannual and intraseasonal variability of rainfall in Brazil. • The state of Rio de Janeiro presents decreasing trends of annual rainfall. • The south region of the state presents significant reduction. • Abrupt changes were identified in the years of 1996 and 1998. • Urgent measures are needed in order to guarantee future potable water supply. [ABSTRACT FROM AUTHOR]