Potential for long-range regional precipitation prediction over India

The potential for long-range precipitation prediction over the Indian monsoon region is generally good where climate noise (i.e., variability due to daily weather fluctuations) is small as compared to the climate signal (i.e., variability due to year to year fluctuations in monthly/seasonal means) being in the tropical belt. In order to understand the potential on smaller spatial scales, the ratios of inter-annual variability to that associated with climate noise have been computed for precipitation of four seasons as well as SW monsoon sub-seasons/months over 1656 stations in the Indian subcontinent. Precipitation in SW monsoon has been found potentially predictable on seasonal as well as intra-seasonal scale. The west coast and contiguous northwest India, part of the 'northeast India are more predictable. Potential for long-range prediction over northwest India is highest during the active monsoon period from July to September. Over eastern peninsula potential for prediction is generally found low whereas over north-central India it is always moderate. Over northern latitudes precipitation due to western disturbances during January to May is potentially predictable. Precipitation over southeast India and Sri Lanka during October to February due to northeast (NE) monsoon shows good potential for long-range prediction. It is manifested that long-range precipitation forecasting schemes for SW monsoon season, sub-seasons and months and for the other seasons over India on point to regional scale have good scope by taking into account the potential predictability at the individual stations as well as at contiguous resemblance areas over the country.

Multidecadal climate oscillations during the past millennium driven by volcanic forcing

Past research argues for an internal multidecadal (40- to 60-year) oscillation distinct from climate noise. Recent studies have claimed that this so-termed Atlantic Multidecadal Oscillation is instead a manifestation of competing time-varying effects of anthropogenic greenhouse gases and sulfate aerosols. That conclusion is bolstered by the absence of robust multidecadal climate oscillations in control simulations of current-generation models. Paleoclimate data, however, do demonstrate multidecadal oscillatory behavior during the preindustrial era. By comparing control and forced “Last Millennium” simulations, we show that these apparent multidecadal oscillations are an artifact of pulses of volcanic activity during the preindustrial era that project markedly onto the multidecadal (50- to 70-year) frequency band. We conclude that there is no compelling evidence for internal multidecadal oscillations in the climate system.

The Multi-Model Large Ensemble Archive as a climate noise generator: opportunities and outlooks for Observational Large Ensemble construction

<p>The Multi-Model Large Ensemble Archive (MMLEA) is a collection of CMIP5-generation single model initial condition large ensembles (SMILEs) and thus provides estimates of internal variability from several independently developed coupled climate models. Work is underway to determine whether these simulations provide a range of historical regional climate variability suitable for statistically increasing the observed temperature sample.  Alternative sequences of historical temperature can be constructed by combining a forced signal with estimates of internal climate noise; prior studies have used the forced response from one SMILE in concert with observational noise resampling to form an “observational large ensemble” (McKinnon et al. 2018). Analogous to a SMILE, an observational large ensemble can be used to statistically contextualize monthly to half-yearly extreme events, such as the persistently mild Siberian winter of 2020, and to develop additional extended hot or cold spell storylines to explore in future projections of regional climate.</p><p>In this study, an alternative approach to constructing an observational large ensemble of European surface air temperature over the historical period (1950-2014), made possible by the MMLEA, is explored. Rather than relying on forced response and internal variability, components not well-defined in the single realization of observed climate, the constructed circulation analogue method of dynamical adjustment is employed to separate temperature anomalies related to atmospheric circulation (“dynamic noise") from a more thermodynamically driven residual signal. The approach is advantageous because it can be applied in a similar manner to single realizations from both models and observations. Here, dynamic noise is computed by dividing each of the seven CMIP5-generation SMILEs in half and empirically estimating the component of temperature associated with interannual sea level pressure variability in one half of the SMILE using circulation analogues from members in the other half. Because ensemble means can be computed in SMILEs, it is possible to use the relationship between unforced temperature and unforced sea level pressure anomalies to construct dynamic noise. In observations, weekly-averaged analogues are assessed as a means to increase the size of the analogue pool such that the separation between dynamic noise and thermodynamic residual signal occurs in a manner more similar to that computed in the SMILEs.</p><p>The extent to which dynamic noise fields from different SMILEs are distinguishable from each other and from observational estimates is determined via spectral and spatial pattern analyses. To avoid introducing regional model bias into dynamic noise estimates, a mosaic approach will be taken; noise estimates from different models are mosaiced such that observed statistical properties are maintained at each grid point of the European domain. Upon validation, SMILE-derived dynamic noise and observational thermodynamic residual signal estimates are combined into a 50-member European observational large ensemble and evaluated via a multi-month extreme temperature frequency metric against the observational large ensemble developed by McKinnon et al. (2018). Anomalously persistent hot and cold spells found in the European observational large ensemble are further compared to events in out-of-sample future projections of climate from the CMIP6 archive.</p>

Assessing the Robustness of Future Extreme Precipitation Intensification in the CMIP5 Ensemble

A warming climate is expected to intensify extreme precipitation, and climate models project a general intensification of annual extreme precipitation in most regions of the globe throughout the twenty-first century. We investigate the robustness of this future intensification over land across different models, regions, and seasons and evaluate the role of model interdependencies in the CMIP5 ensemble. Strong similarities in extreme precipitation changes are found between models that share atmospheric physics, turning an ensemble of 27 models into around 14 projections. We find that future annual extreme precipitation intensity increases in the majority of models and in the majority of land grid cells, from the driest to the wettest regions, as defined by each model’s precipitation climatology. The intermodel spread is generally larger over wet than over dry regions, smaller in the dry season compared to the wet season and at the annual scale, and largely reduced in extratropical compared to tropical regions and at the global scale. For each model, the future increase in annual and seasonal maximum daily precipitation amounts exceeds the range of simulated internal variability in the majority of land grid cells. At both annual and seasonal scales, however, there are a few regions where the change is still within the background climate noise, but their size and location differ between models. In extratropical regions, the signal-to-noise ratio of projected changes in extreme precipitation is particularly robust across models because of a similar change and background climate noise, whereas projected changes are less robust in the tropics.

PERSEPSI PENGHUNI TERHADAP KENYAMANAN BERAKTIVITAS DI RUANG TERBUKA PERUMAHAN

A comfort open space has a function and a huge influence in housing because it becomes a means of activity throughout the housing dwellers. Debang Housing Taman Sari Medan is one of housing in Kecamatan Medan Selayang which has open space. The purpose of this research is to know the perception of occupant to the comfort of open space. There are several convenience factors that are used as indicators in research such as Circulation, Climate, Noise, Smell, Shape, Safety, Cleanliness, and Beauty. The research was done through qualitative descriptive analysis, where the data collection technique used questionnaire from the population and the specified sample. The process of collecting data, sampling technique until the criteria of research become an important process of research method. This study shows if the perception of occupants of the comfort of open space of housing Debang Taman Sari Medan is quite comfortable and needed supporting facilities for park users.

Potential predictability of Australian seasonal rainfall

The potential predictability of Australian seasonal mean rainfall at 800 stations is estimated using an analysis of variance method for the period 1957-2015 and for all twelve three-month seasons. The method estimates the contribution of the slow, potentially predictable, signal of the rainfall to the total inter-annual variance, after removing the climate noise due to intra-seasonal and weather variability.The results show that there are stations, in all seasons, where the potential predictability is relatively high, and can be greater than half of the total inter-annual variance. Largest potential predictability, coherent over eastern Australia, occurs during the transition to spring, and in spring seasons. Large and coherent potential predictability also occurs during the autumn seasons over Queensland and south-eastern Australia. For summer and the northern wet seasons, the potential predictability is larger over the northeast coastal stations, in the southeast, central east and central west of the continent. During winter, relatively large and coherent potential predictability occurs over the southeast, the central east, and in an implied northwest-southeast band across the continent. Patterns of seasonal forecast skill from the coupled Predictive Ocean Atmosphere Model for Australia are shown to be highly consistent with our estimates of the potential predictability.Factors that may influence the potential predictability are briefly discussed in the light of previous studies that have considered the relationships between the slow, potentially predictable, components of rainfall and the atmospheric and oceanic circulations. Prominent among these are the El Niño-Southern Oscillation, the Southern Annular mode and the meridional Indian Ocean Dipole.

GENETIC MARKERS AS AN INDICATOR OF HUMAN RESILIENCE TO VARIOUS ECOLOGICAL AND PROFESSIONAL FACTORS

Various ecological and professional factors (hypoxia, a hot or cold climate, noise, vibration, radiation, intense physical activity, etc.) are peculiarities of the military activities. The introduction of molecular and genetic methods in medical practice and occupational selection can greatly improve the efficiency of selection and rational appointment of people into separate specialties, optimize working capacity, maintain human health, reduce the costs for rehabilitation and (or) specialists’ treatment