Monitoring and modelling of hydrological processes in the semiarid region of Brazil: The Cariri experimental basins

Catchments have highly variable yields of runoff and soil erosion. The size, land use and the surface cover play a significant role and influence the catchment response and parameter values of simulation models. Two experimental basins—the Cariri basins—were equipped in a semi-arid region of Brazil, for obtaining runoff and sediment yield at different catchment scales, as well as, to evaluate the influence of the land use and surface cover. In the first basin, located in the municipality of Sumé, the field studies were carried out at two different scales: four micro-catchments with an area of around 0.5 ha and nine standard Wischmeier-type erosion plots of 100 m². The experimental units had varied vegetation and management. They were subjected only to natural rainfall events, and were monitored from 1982 to 1991. The total runoff and total sediment yield were determined for each of the events. The installations in the second basin, in the municipality of São João do Cariri, from 1999, include two erosion plots, three micro-catchments, and two sub-catchments of a small basin. These basins are still being monitored for runoff and sediment production. Among the micro-catchments two are nested to detect any scale effect at the micro-catchment level. Nearly 600 events of precipitation, that produced runoff in at least one of the experimental units, have been registered. These data have been used to evaluate the influence of various factors, including cultivation practices and to calibrate hydrological models for plots and micro-catchments. Parameters have been tested by means of cross validations among micro-catchments and sub-catchments. The data sets are made available to all the catchment hydrology researchers and others at https://doi.org/10.5281/zenodo.4690886 .     

Ocean–atmosphere coupling and the boreal winter MJO

The influence of ocean–atmosphere coupling on the simulation and prediction of the boreal winter Madden–Julian Oscillation (MJO) is examined using the Seoul National University coupled general circulation model (CGCM) and atmospheric—only model (AGCM). The AGCM is forced with daily SSTs interpolated from pentad mean CGCM SSTs. Forecast skill is examined using serial extended simulations spanning 26 different winter seasons with 30-day forecasts commencing every 5 days providing a total of 598 30-day simulations. By comparing both sets of experiments, which share the same atmospheric components, the influence of coupled ocean–atmosphere processes on the simulation and prediction of MJO can be studied. The mean MJO intensity possesses more realistic amplitude in the CGCM than in AGCM. In general, the ocean–atmosphere coupling acts to improve the simulation of the spatio-temporal evolution of the eastward propagating MJO and the phase relationship between convection (OLR) and SST over the equatorial Indian Ocean and the western Pacific. Both the CGCM and observations exhibit a near-quadrature relationship between OLR and SST, with the former lagging by about two pentads. However, the AGCM shows a less realistic phase relationship. As the initial conditions are the same in both models, the additional forcing by SST anomalies in the CGCM extends the prediction skill beyond that of the AGCM. To test the applicability of the CGCM to real-time prediction, we compute the Real-time Multivariate MJO (RMM) index and compared it with the index computed from observations. RMM1 (RMM2) falls away rapidly to 0.5 after 17–18 (15–16) days in the AGCM and 18–19 (16–17) days in the CGCM. The prediction skill is phase dependent in both the CGCM and AGCM.     

Recent Near-surface Temperature Trends in the Antarctic Peninsula from Observed,Reanalysis and Regional Climate Model Data

This study investigates the recent near-surface temperature trends over the Antarctic Peninsula.We make use of available surface observations,ECMWF’s ERA5 and its predecessor ERA-Interim,as well as numerical simulations,allowing us to contrast different data sources.We use hindcast simulations performed with Polar-WRF over the Antarctic Peninsula on a nested domain configuration at 45 km(PWRF-45)and 15 km(PWRF-15)spatial resolutions for the period 1991?2015.In addition,we include hindcast simulations of KNMI-RACMO21P obtained from the CORDEX-Antarctica domain(~50 km)for further comparisons.Results show that there is a marked windward warming trend except during summer.This windward warming trend is particularly notable in the autumn season and likely to be associated with the recent deepening of the Amundsen/Bellingshausen Sea low and warm advection towards the Antarctic Peninsula.On the other hand,an overall summer cooling is characterized by the strengthening of the Weddell Sea low as well as an anticyclonic trend over the Amundsen Sea accompanied by northward winds.The persistent cooling trend observed at the Larsen Ice Shelf station is not captured by ERA-Interim,whereas hindcast simulations indicate that there is a clear pattern of windward warming and leeward cooling.Furthermore,larger temporal correlations and lower differences exhibited by PWRF-15 illustrate the existence of the added value in the higher spatial resolution simulation.     

Projections of severe droughts in future climate in Southeast Brazil: a case study in Southern Minas Gerais State,Brazil

Theoretical and Applied Climatology - South of Minas Gerais state, in Southeast Brazil, is known for the coffee crop production (more than 30% of country’s production) and hydroelectricity...     

Reconstruction of the Surface-Layer Vertical Structure from Measurements of Wind,Temperature and Humidity at Two Levels

A comparison of sensible heat flux derived from ultrasonic-anemometer measurements and profile-derived values shows strong systematic bias in the stable branch. One of the two effects, large sonic-based values combined with small profile-based values, can be explained as due to katabatic flows down the terrain slope. The other effect, large profile-based values combined with small sonic-based values, can only partially be explained as due to intermittent turbulence. The remainder occurs at small stability and indicates a possible systematic kink in ultrasonic-anemometer eddy-correlation values. Evaluation of the temperature-profile parameter θ _* contributes to further clarification by reducing the systematic bias and confirming the katabatic-flow explanation. Also, the intermittent-turbulence influence is confirmed by the θ _* evaluation, but the combination of large profile-based values with small sonic-based values does not vanish outside the more clearly defined intermittent-turbulence region. This is associated with a strongly increased occurrence of opposite-sign sonic values. Neutral profile values are frequently associated with considerably unstable sonic values of θ _*.     

Adaptation and poverty reduction in Mozambique: an opportunity for developing countries to lead§

Climate change disproportionately impacts the world’s poorest countries. A recent World Bank report highlighted that over 100 million people are at risk of falling into extreme poverty as a result of climate change. There is currently a lack of information about how to simultaneously address climate change and poverty. Climate change challenges provide an opportunity for those impacted most to come up with new and innovative technologies and solutions. This article uses an example from Mozambique where local and international partners are working side-by-side, to show how developing countries can simultaneously address climate change and poverty reduction using an ecosystem-based adaptation approach. Using ecosystem-based adaptation, a technique that uses the natural environment to help societies adapt to climate change, developing countries can lead the way to improve climate adaptation globally. This paradigm shift would help developing countries become leaders in ecosystem-based adaptation and green infrastructure techniques and has implications for climate policy worldwide.

POLICY RELEVANCE

The Paris Agreement resulting from the United Nations Framework Convention on Climate Change (UNFCCC) 21st Conference of Parties (COP 21) in December 2015 was rightly lauded for its global commitment to cut greenhouse gas emissions. However, COP 21 was also historic because of its call for non-party stakeholders to address climate change, inclusion of a global goal of ‘enhancing adaptive capacity, strengthening resilience and reducing vulnerability’, and the United States’ commitment of $800 million to adaptation funding. The combination of recognizing the need for new stakeholders to commit to climate change adaptation, the large impact climate change will have on the developing world, and providing access to funds for climate change adaptation creates a unique opportunity for developing countries to pave the way in adaptation policies in practices. Currently, developing countries are creating National Adaptation Plans (NAPs) for the UNFCCC. Through including a strong component of ecosystem-based adaptation in NAPs, developing countries can shape their countries’ policies, improve local institutions and governments, and facilitate a new generation of innovative leaders. Lessons learned in places like Mozambique can help lead the way in other regions facing similar climatic risks.     

Significance tests for covariate-dependent trends in inhomogeneous spatio-temporal point processes

Modeling and inference for spatial and spatio-temporal point processes is an issue that has been broadly investigated in the last years. Application fields such as forestry, epidemiology and ecology have been the main engine driving such raised interest. The inclusion of spatially varying covariates in the models for the intensity function is becoming of particular interest, but little attention has been paid to testing the significance of such covariates. Testing the significance of covariates is important if one seeks to explain which covariates have an effect in the spatial or spatio-temporal distribution of the point pattern observed. We thus provide practical procedures to build statistical tests of significance for covariates that have an effect on the intensity function of a point pattern. Our approximation focuses on the conditional intensity function, by considering nonparametric kernel-based estimators. We calculate thinning probabilities under the conditions of absence and presence of a covariate and compare them through divergence measures. Based on Monte Carlo experiments, we approximate the statistical properties of our tests under a variety of practical scenarios. An application on testing the significance of a covariate in a spatio-temporal data set on wildfires is also developed.     

Objective probabilities about future climate are a matter of opinion

In this paper, the unfeasibility of producing “objective” probabilistic climate change scenarios is discussed. Realizing that the knowledge of “true” probabilities of the different scenarios and temperature changes is unachievable, the objective must be to find the probabilities that are the most consistent with what our state of knowledge and expert judgment are. Therefore, subjective information plays, and should play, a crucial role. A new methodology, based on the Principle of Maximum Entropy, is proposed for constructing probabilistic climate change scenarios when only partial information is available. The objective is to produce relevant information for decision-making according to different agents’ judgment and subjective beliefs. These estimates have desirable properties such as: they are the least biased estimate possible on the available information; maximize the uncertainty (entropy) subject to the partial information that is given; The maximum entropy distribution assigns a positive probability to every event that is not excluded by the given information; no possibility is ignored. The probabilities obtained in this manner are the best predictions possible with the state of knowledge and subjective information that is available. This methodology allows distinguishing between reckless and cautious positions regarding the climate change threat.     

Possible climatic impacts of tropical deforestation

Large-scale conversion of tropical forests into pastures or annual crops will likely lead to changes in the local microclimate of those regions. Larger diurnal fluctuations of surface temperature and humidity deficit, increased surface runoff during rainy periods and decreased runoff during the dry season, and decreased soil moistrue are to be expected.It is likely that evapotranspiration will be reduced because of less available radiative energy at the canopy level since grass presents a higher albedo than forests, also because of the reduced availability of soil moisture at the rooting zone primarily during the dry season. Recent results from general circulation model (GCM) simulations of Amazonian deforestation seem to suggest that the equilibrium climate for a grassy vegetation in Amazonia would be one in which regional precipitation would be significantly reduced.Global climate changes probably will occur if there is a marked change in rainfall patterns in tropical forest regions as a result of deforestation. Besides that, biomass burning of tropical forests is likely adding CO₂ into the atmosphere, thus contributing to the enhanced greenhouse warming.