TAFILELT KSAR: BETWEEN TRADITION AND MODERNITY, AN EXPERIMENT OF ENERGY ENHANCEMENT HOUSING IN ALGERIA

Energy is one of the common determinant factors related to social, environmental and economic problems, which can also contribute to their solution. Among sectors where studies could be done to reduce energy demand, is building. This latter is the largest primary energy consumer and responsible for more than 40% of total CO2 emissions. Therefore, improving energy efficiency in buildings represents an economic and ecological challenge. The built environment quality, with good insulation and high-performance building materials, constitutes the first step towards this aim. Yet, this is not enough to make buildings low energy consumption. But then again, a starting point for which, it is necessary to manage how it should be occupied and exploited. Improving energy efficiency of buildings involves several steps through which, coherent actions, will enable energy savings acting on different human and material parameters. The conceptual approach for improving energy efficiency is identical for residential and tertiary sectors. However, in practice this is different due to divergences related to: technical aspects; used tools; operating and maintenance costs and return time of investment. The purpose of this research is to investigate an example of Energy Enhancement housing in Tafilelt ksar in the M’zab valley in Algeria (an example of ecologic planning with modern habitat perfectly adapted to environment), with the objective of creating adaptable housing according to changing needs of future generations.

Global Intercomparison of Hyper-Resolution ECOSTRESS Coastal Sea Surface Temperature Measurements from the Space Station with VIIRS-N20

The ECOSTRESS multi-channel thermal radiometer on the Space Station has an unprecedented spatial resolution of 70 m and a return time of hours to 5 days. It resolves details of oceanographic features not detectable in imagery from MODIS or VIIRS, and has open-ocean coverage, unlike Landsat. We calibrated two years of ECOSTRESS sea surface temperature observations with L2 data from VIIRS-N20 (2019–2020) worldwide but especially focused on important upwelling systems currently undergoing climate change forcing. Unlike operational SST products from VIIRS-N20, the ECOSTRESS surface temperature algorithm does not use a regression approach to determine temperature, but solves a set of simultaneous equations based on first principles for both surface temperature and emissivity. We compared ECOSTRESS ocean temperatures to well-calibrated clear sky satellite measurements from VIIRS-N20. Data comparisons were constrained to those within 90 min of one another using co-located clear sky VIIRS and ECOSTRESS pixels. ECOSTRESS ocean temperatures have a consistent 1.01 °C negative bias relative to VIIRS-N20, although deviation in brightness temperatures within the 10.49 and 12.01 µm bands were much smaller. As an alternative, we compared the performance of NOAA, NASA, and U.S. Navy operational split-window SST regression algorithms taking into consideration the statistical limitations imposed by intrinsic SST spatial autocorrelation and applying corrections on brightness temperatures. We conclude that standard bias-correction methods using already validated and well-known algorithms can be applied to ECOSTRESS SST data, yielding highly accurate products of ultra-high spatial resolution for studies of biological and physical oceanography in a time when these are needed to properly evaluate regional and even local impacts of climate change.

Complex system properties in the spreading of COVID-19 pandemic

The objective of the present study was to show that the spread of the COVID-19 pandemic around the world shows complex system properties such as lognormal laws, temporal fluctuation scaling, and time correlation. First, the daily cumulative number of confirmed cases and deaths is distributed among countries as lognormals such that the time series exhibit a temporal fluctuation scaling. Second, the daily return time series of cases and deaths per day have associated Levy stable distributions and they have time correlation. The idea was to draw attention to the fact that the spread of the COVID-19 pandemic can be seen as a complex system, and, thus, contribute to the identification of the structural properties of this system, which is relevant as it is expected that future stochastic models describing the spread of the COVID-19 pandemic from a microscopic dynamics perspective should be able to explain the emergence of the structural properties identified here.

Extrinsic and intrinsic factors influencing the emergence and return of Asian particolored bats Vespertilio sinensis

The circadian rhythm is an adaptive biological process, allows organisms to anticipate daily environmental changes and implement appropriate strategies. Circadian rhythms play a crucial role in the health and survival of organisms. However, little is known concerning how intrinsic and extrinsic factors affect animal daily rhythms in the field, especially in nocturnal animals. Here, we investigated the emergence and return times of Vesperilio sinensis, and also integrated environmental conditions (temperature, humidity and light intensity) and biotic factors (reproductive status and predation risk) to determine causes of variation in the activity rhythms of the bats. We found that variation in the first emergence time, the mid-emergence time, and the final return time were distinct. The results demonstrated that the emergence and return times of bats were affected by light intensity, reproductive status, and predation risk in a relatively complex pattern. Light intensity had the greatest contribution to activity rhythms. Moreover, we first investigated the effects of actual predators on the activity rhythms of bats; the results showed that the mid-emergence time of bats was earlier as predators were hunting, but the final return time was later when predators were present. This challenges the traditional view that high predation risk leads to later emergence and earlier return. Finally, our results also highlighted the importance of higher energy demands during the lactation period in bats to variation in activity rhythms. These results improve our understanding of the patterns and causes of variation in activity rhythms in bats and other nocturnal animals.

REVIEW: Like the pandemic, climate action is urgent

Climate Aotearoa: What’s happening and what we can do about it, edited by Helen Clark. Auckland: Allen & Unwin, 2021. 327 pages. ISBN 9781988547633 WHEN the publication of Climate Aotearoa was heralded by Radio New Zealand in April 2021 it was featured along with a striking image and a quote from the collection editor, former prime minister Helen Clark. The illustration by Vinay Ranchhod was a dazzling red lobster in a boiling pot. 'I would liken [the challenge of climate change] to being the lobster in the pot and the pot starts to heat, and by the time it’s realised it’s being cooked, it’s too late to change. Its fate is sealed. 'That’s in essence the message: you’ve got time to act, the window is closing. And if you don’t, you’re going to get over those tipping points from which there’s no return.' (‘Time for action’, 2021)

25,000 Years long seismic cycle in a slow deforming continental region of Mongolia

The spatial distribution of large earthquakes in slowly deforming continental regions (SDCR) is poorly documented and, thus, has often been deemed to be random. Unlike in high strain regions, where seismic activity concentrates along major active faults, earthquakes in SDCR may seem to occur more erratically in space and time. This questions classical fault behavior models, posing paramount issues for seismic hazard assessment. Here, we investigate the M7, 1967, Mogod earthquake in Mongolia, a region recognized as a SDCR. Despite the absence of visible cumulative deformation at the ground surface, we found evidence for at least 3 surface rupturing earthquakes during the last 50,000 years, associated with a slip-rate of 0.06 ± 0.01 mm/year. These results show that in SDCR, like in faster deforming regions, deformation localizes on specific structures. However, the excessive length of return time for large earthquakes along these structures makes it more difficult to recognize earthquake series, and could conversely lead to the misconception that in SDCR earthquakes would be randomly located. Thus, our result emphasizes the need for systematic appraisal of the potential seismogenic structures in SDCR in order to lower the uncertainties associated with the seismogenic sources in seismic hazard models.

Asymptotic distribution of hitting times for critical maps of the circle

It is well known that the renormalization group transformation $\mathcal{R}$ has a unique fixed point $f_{cr}$ in the space of critical $C^{3}$-circle homeomorphisms with one cubic critical point $x_{cr}$ and the golden mean rotation number $\overline{\rho}:=\frac{\sqrt{5}-1}{2}.$ Denote by $Cr(\overline{\rho})$ the set of all critical circle maps $C^{1}$-conjugated to $f_{cr}.$ Let $f\in Cr(\overline{\rho})$ and let $\mu:=\mu_{f}$ be the unique probability invariant measure of $f.$ Fix $\theta \in(0,1).$ For each $n\geq1$ define $c_{n}:=c_{n}(\theta)$ such that $\mu([x_{cr},c_{n}])=\theta\cdot\mu([x_{cr},f^{q_{n}}(x_{cr})]),$ where $q_{n}$ is the first return time of the linear rotation $f_{\overline{\rho}}.$ We study convergence in law of rescaled point process of time hitting. We show that the limit distribution is singular w.r.t. the Lebesgue measure.

Learning forecasts of rare stratospheric transitions from short simulations

Rare events arising in nonlinear atmospheric dynamics remain hard to predict and attribute. We address the problem of forecasting rare events in a prototypical example, Sudden Stratospheric Warmings (SSWs). Approximately once every other winter, the boreal stratospheric polar vortex rapidly breaks down, shifting midlatitude surface weather patterns for months. We focus on two key quantities of interest: the probability of an SSW occurring, and the expected lead time if it does occur, as functions of initial condition. These optimal forecasts concretely measure the event’s progress. Direct numerical simulation can estimate them in principle, but is prohibitively expensive in practice: each rare event requires a long integration to observe, and the cost of each integration grows with model complexity. We describe an alternative approach using integrations that are short compared to the timescale of the warming event. We compute the probability and lead time efficiently by solving equations involving the transition operator, which encodes all information about the dynamics. We relate these optimal forecasts to a small number of interpretable physical variables, suggesting optimal measurements for forecasting. We illustrate the methodology on a prototype SSW model developed by Holton and Mass (1976) and modified by stochastic forcing. While highly idealized, this model captures the essential nonlinear dynamics of SSWs and exhibits the key forecasting challenge: the dramatic separation in timescales between a single event and the return time between successive events. Our methodology is designed to fully exploit high-dimensional data from models and observations, and has the potential to identify detailed predictors of many complex rare events in meteorology.

Probability distributions for analog-to-target distances

Some properties of chaotic dynamical systems can be probed through features of recurrences, also called analogs. In practice, analogs are nearest neighbours of the state of a system, taken from a large database called the catalog. Analogs have been used in many atmospheric applications including forecasts, downscaling, predictability estimation, and attribution of extreme events. The distances of the analogs to the target state usually condition the performances of analog applications. These distances can be viewed as random variables, and their probability distributions can be related to the catalog size and properties of the system at stake. A few studies have focused on the first moments of return time statistics for the closest analog, fixing an objective of maximum distance from this analog to the target state. However, for practical use and to reduce estimation variance, applications usually require not just one, but many analogs. In this paper, we evaluate from a theoretical standpoint and with numerical experiments the probability distributions of the K shortest analog-to-target distances. We show that dimensionality plays a role on the size of the catalog needed to find good analogs, and also on the relative means and variances of the K closest analogs. Our results are based on recently developed tools from dynamical systems theory. These findings are illustrated with numerical simulations of well-known chaotic dynamical systems and on 10m-wind reanalysis data in north-west France. Practical applications of our derivations are shown for forecasts of an idealized chaotic dynamical system and for objective-based dimension reduction using the 10m-wind reanalysis data.

Analysis of the feasibility of the use of rainwater: A case study for standard school infrastructures

With the growth in water demand worldwide, cities are experiencing increasing difficulties to guarantee the public supply of drinking water. Therefore, the search for alternatives that replace the available sources needs to be disseminated. An alternative to reduce the demand for drinking water is to use the Rainwater harvesting system. This work analyzes the feasibility of implementing a system for capturing, storing, and distributing rainwater for non-drinking purposes in three standard projects of the National Fund for the Development of Education in three locations in the state of Pernambuco: Recife, Caruaru, and Petrolina. To achieve this objective, local rainfall data, the catchment area used and the demand for non-drinking water in the building were analyzed. Then, sizing calculations of the storage reservoir were performed by different methods. The time for return on investment was considered satisfactory for all types located in Recife and for the 1-room type in Caruaru and Petrolina, considering the benefit from the system in the long term. Therefore, the typologies of 6 and 12 rooms in Caruaru and Petrolina were excluded since they had a return time of more than 24 years. The advantages are not only financial, but also environmental, cultural, and educational.