scholarly journals Insights from 20 years of temperature parallel measurements in Mauritius around the turn of the 20<sup>th</sup> Century

2021 ◽  
Author(s):  
Samuel O. Awe ◽  
Martin Mahony ◽  
Edley Michaud ◽  
Conor Murphy ◽  
Simon J. Noone ◽  
...  

Abstract. There is considerable import in creating more complete, better understood, holdings of early meteorological data. Such data permit an improved understanding of climate variability and long-term changes. Early records are particularly incomplete in the tropics, with implications for estimates of global and regional temperature. There is also a relatively low level of scientific understanding of how these measurements were made and, as a result, of their homogeneity and comparability to more modern techniques and measurements. Herein we describe and analyse a newly rescued set of long-term, up to six-way parallel measurements, undertaken over 1884–1903 in Mauritius, an island situated in the southern Indian Ocean. Data include: i) measurements from a well-ventilated room, ii) a shaded Thermograph; iii) instruments housed in a manner broadly equivalent to a modern Stevenson Screen; iv) a set of measurements by a Hygrometer mounted in a Stevenson Screen; and for a very much shorter period v) two additional Stevenson Screen configurations. All measurements were undertaken within roughly 80 metre radius. To our knowledge this is the first such multidecadal multi-instrument assessment of meteorological instrument transition impacts ever undertaken, providing potentially unique insights. The intercomparison also considers the impact of different ways of deriving daily and monthly averages. The long-term comparison is sufficient to robustly characterise systematic offsets between all the instruments and seasonally varying impacts. Differences between all techniques range from tenths of a degree Celsius to in excess of a degree Celsius and are considerably larger for maximum and minimum temperatures than for means or averages. Systematic differences of several tenths of a degree also exist for the different ways of deriving average / mean temperatures. All differences bar two average temperature series pairs are significant at the 0.01 level using a paired t-test. Given that all thermometers were regularly calibrated against a primary Kew standard thermometer this analysis highlights significant impacts of instrument exposure, housing, siting and measurement practices in early meteorological records. These results reaffirm the importance of thoroughly assessing the homogeneity of early meteorological records.

Author(s):  
Saurabh Mahajan ◽  
Ravi Devarakonda ◽  
Gautam Mukherjee ◽  
Nisha Verma ◽  
Kumar Pushkar

Background: Coronaviruses are a family of viruses that can result in different types of illnesses, most commonly, as Severe acute respiratory syndrome (SARS). Researches have shown that the atmospheric variables and the density of population have affected the transmission of the disease. Meteorological variables like temperature, humidity among others have found to affect the rise of pandemic in positive or negative ways.  Respiratory virus illnesses have shown seasonal variability since the time they have been discovered and managed. This study investigated the relationship between the meteorological variables of temperature, humidity and precipitation in the spread of COVID-19 disease in the city of Pune.Methods: This record based descriptive study is conducted after secondary data analysis of number of new cases of COVID-19 per day from the period 01 May to 24 December 2020 in Pune. Meteorological data of maximum (Tmax), minimum (Tmin) and daily average temperature (Tavg), humidity and precipitation were daily noted from Indian meteorological department website. Trend was identified plotting the daily number of clinically diagnosed cases over time period. Pearson’s correlation was used to estimate association between meteorological variables and daily detected fresh cases of COVID-19 disease.  Results: Analysis revealed significant negative correlation (r=-0.3563, p<0.005) between daily detected number of cases and maximum daily temperature. A strong positive correlation was seen between humidity and daily number of cases (r=0.5541, p<0.005).Conclusions: The findings of this study will aid in forecasting epidemics and in preparing for the impact of climate change on the COVID epidemiology through the implementation of public health preventive measures.


2019 ◽  
Vol 12 (2) ◽  
pp. 987-1011
Author(s):  
Kostas Eleftheratos ◽  
Christos S. Zerefos ◽  
Dimitris S. Balis ◽  
Maria-Elissavet Koukouli ◽  
John Kapsomenakis ◽  
...  

Abstract. In this work we present evidence that quasi-cyclical perturbations in total ozone (quasi-biennial oscillation – QBO, El Niño–Southern Oscillation – ENSO, and North Atlantic Oscillation – NAO) can be used as independent proxies in evaluating Global Ozone Monitoring Experiment (GOME) 2 aboard MetOp A (GOME-2A) satellite total ozone data, using ground-based (GB) measurements, other satellite data, and chemical transport model calculations. The analysis is performed in the frame of the validation strategy on longer time scales within the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) Satellite Application Facility on Atmospheric Composition Monitoring (AC SAF) project, covering the period 2007–2016. Comparison of GOME-2A total ozone with ground observations shows mean differences of about -0.7±1.4 % in the tropics (0–30∘), about +0.1±2.1 % in the mid-latitudes (30–60∘), and about +2.5±3.2 % and 0.0±4.3 % over the northern and southern high latitudes (60–80∘), respectively. In general, we find that GOME-2A total ozone data depict the QBO–ENSO–NAO natural fluctuations in concurrence with the co-located solar backscatter ultraviolet radiometer (SBUV), GOME-type Total Ozone Essential Climate Variable (GTO-ECV; composed of total ozone observations from GOME, SCIAMACHY – SCanning Imaging Absorption SpectroMeter for Atmospheric CHartographY, GOME-2A, and OMI – ozone monitoring instrument, combined into one homogeneous time series), and ground-based observations. Total ozone from GOME-2A is well correlated with the QBO (highest correlation in the tropics of +0.8) in agreement with SBUV, GTO-ECV, and GB data which also give the highest correlation in the tropics. The differences between deseazonalized GOME-2A and GB total ozone in the tropics are within ±1 %. These differences were tested further as to their correlations with the QBO. The differences had practically no QBO signal, providing an independent test of the stability of the long-term variability of the satellite data. Correlations between GOME-2A total ozone and the Southern Oscillation Index (SOI) were studied over the tropical Pacific Ocean after removing seasonal, QBO, and solar-cycle-related variability. Correlations between ozone and the SOI are on the order of +0.5, consistent with SBUV and GB observations. Differences between GOME-2A and GB measurements at the station of Samoa (American Samoa; 14.25∘ S, 170.6∘ W) are within ±1.9 %. We also studied the impact of the NAO on total ozone in the northern mid-latitudes in winter. We find very good agreement between GOME-2A and GB observations over Canada and Europe as to their NAO-related variability, with mean differences reaching the ±1 % levels. The agreement and small differences which were found between the independently produced total ozone datasets as to the influence of the QBO, ENSO, and NAO show the importance of these climatological proxies as additional tool for monitoring the long-term stability of satellite–ground-truth biases.


2020 ◽  
Author(s):  
Hyunha Lee ◽  
Chunsil Jin ◽  
Chunji Kim

&lt;p&gt;&amp;#160; Clustering analysis using air parcel trajectories is actively used to investigate transport patterns of pollutants. To estimate the impact of nuclide dispersion from nuclear accident, comprehensive information based on long-term meteorological data is required to eatablish a complete and efficient public protection plan. Most of nuclear plants in South Korea are located in a complex terrain near coastal area that involves complicated meteorological phenomenon such as sea breezes and mountain-valley breezes. Robust approach based on long-term climatrological data is required to fully resolve the impacts near Korean nuclear power plants.&lt;/p&gt;&lt;p&gt;&amp;#160; In this study, we assessed the impacts of potential nuclear accident in South Korea by clustering dispersion patterns using 10-year meteorological data. Flow patterns are clustered using trajectory cluster analysis, and then combined with dispersion simulations to demonstrate the clustered dispersion patterns by each season and nuclear power plant.&lt;/p&gt;&lt;p&gt;&amp;#160; The long-term meteorological simulations from 2007 to 2016 were used to evaluate the potential impact of nuclear accidents in Korea, and the modeling framework was designed to show the impact map according to the flow patterns near each nuclear power plant. NOAA HYSPLIT modeling additional clustering analysis suggests that two or three cluster patterns for each power plant can be used. A total of 38 flow patterns are classified near the four nuclear plants in the previous season based on a 10-year wind field analysis.&amp;#160;Korea has very complex terrain and coastal areas, and more sophisticated modeling efforts are needed to fully understand the more realistic dispersion characteristics of air masses. In terms of space-time resolution, updating land use information for simulation is very important for weather simulation near the surface of Korea.&lt;/p&gt;&lt;p&gt;&amp;#160; The results of this study can be used as a guideline for constructing a modeling framework for nuclide diffusion simulations, but given these complex simulation configurations, the results demonstrated in the current study are should be interpreted with caution.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;


2006 ◽  
Vol 37 (4-5) ◽  
pp. 365-376 ◽  
Author(s):  
Jóna Finndís Jónsdóttir ◽  
Páll Jónsson ◽  
Cintia B. Uvo

This study is a part of a Nordic co-operative research project, Climate and Energy, funded by Nordic Energy Research and the Nordic energy sector. The project has the objective of a comprehensive assessment of the impact of climate change on Nordic renewable energy resources including hydropower, wind power, biofuels and solar energy. In this paper, the long term variability of precipitation, temperature and discharge of Icelandic rivers is analyzed with respect to trends. Trend is tested for two periods: 1941–2002, since the longest Icelandic discharge records reach 60 years back in time, and 1961–2000, so that a larger set of discharge records could be included, as only a few Icelandic discharge records extend more than 40 years back in time. An eventual trend in the time series is analyzed using the Mann–Kendall test. The test is applied to the time series of both annual and seasonal values, and also to the timing and volume of the maximum daily discharge in spring and autumn, respectively. The main conclusions from the study are that, despite significant increase in measured precipitation, discharge in non-glacial rivers has not increased. Meanwhile, spring temperatures have a negative trend and spring floods, therefore, are larger and delayed.


2010 ◽  
Vol 58 (Supplement 1) ◽  
pp. 83-88
Author(s):  
N. Harnos ◽  
É. Erdélyi ◽  
T. Árendás

Nowadays, studying the impact of climate change on agricultural crops is of great importance in national and international projects. Research on the effects of climate change on agricultural cultivars is supported by crop growth models. Simulations provide facilities for the low cost investigation of the effects of many factors, both independently of each other and in combination. These models require parameterisation and testing, which can be done using data measurements. In order to test the correctness of the simulations of meteorological and nutrient supply effects, it is necessary to use the results of long-term field experiments with many replicates.In the present study, the Ceres Wheat and AFRCWHEAT2 winter wheat crop growth models were tested, utilizing the data of a five-year sowing date experiment and the relevant meteorological data. An analysis was made of whether changes in the sowing date were able to influence or eliminate the negative effects of the changing climate. It was found that choosing the optimum sowing date could be the key to adapting to changing conditions.


Author(s):  
Michael Poteser ◽  
Hanns Moshammer

In Europe and many countries worldwide, a half-yearly changing time scheme has been adopted with the aim of optimizing the use of natural daylight during working hours and saving energy. Because the expected net economic benefit was not achieved, the discussion about the optimal solution has been reopened with a shifted focus on social and health related consequences. We set out to produce evidence for this discussion and analysed the impact of daylight saving time on total mortality of a general population in a time series study on daily total mortality for the years 1970–2018 in the city of Vienna, Austria. Daily deaths were modelled by Poisson regression controlling for seasonal and long-term trend, same-day and 14-day average temperature, humidity, and day of week. During the week after the spring transition a significant increase in daily total mortality of about 3% per day was observed. This was not the case during the week after the fall transition. The increase in daily mortality as observed in the week after spring DST-transition is most likely causally linked to the change in time scheme.


2019 ◽  
Vol 6 (2) ◽  
pp. 69-76
Author(s):  
Janardan Mahanta ◽  
Soumen Kishor Nath ◽  
Md. Haronur Rashid

In this paper has been studied the temperature trend in Bangladesh. Long-term changes of surface air temperature over Bangladesh have been studied using the available historical data collected by the Bangladesh meteorological Department (BMD). Daily temperature data is collected from BMD in Dhaka and Chittagong. Then month have been divided according to season and their descriptive statistics are computed. Maximum average temperature in pre-monsoon season and minimum average temperature in winter season have been shown in the paper. This study also reveals that temperature has increased over the time. Markov chain analysis has been applied for these data so as to find the stationary probability. After 26 and 13 days stationary probabilities in Dhaka and Chittagong stations respectively have observed.


2016 ◽  
Vol 77 (2) ◽  
pp. 141-150
Author(s):  
Maciej Bartold

Abstract The work presented here aims at developing cover mask for monitoring forest health in Poland using remote sensing data. The main objective was to assess the impact of using the mask on forest condition monitoring combined with vegetation indices obtained from long-term satellite data. In this study, a new mask developed from the CORINE Land Cover 2012 (CLC2012) database is presented and its one-kilometer pixel size matched to low-resolution data derived from SPOT VEGETATION satellite registrations. For vegetation mapping, only pixels with a cover ≥ 50% of broad-leaved and mixed forests defined by CLC2012 were taken into account. The masked pixels were used to evaluate spatial variability in eight Natural-Forest Regions (NFRs). The largest coverages by masked forests were obtained in Sudetian (65.7%), Carpathian (65.9%) and Baltic (51.3%) regions. For other forest regions the coverage was observed to be around 30-50%. Time-series of the Normalized Difference Vegetation Index (NDVI) comprising SPOT VEGETATION images from 1998 until 2014 were computed and cross-comparison analyses on ≥ 50% and < 50% forest cover masks brought up frequent differences at a level higher than 0.05 NDVI in seven out of eight NFRs. An exception is the Sudetian region, where the data was highly consistent. Furthermore, the Mann-Whitney U non-parametric test revealed statistically significant differences in two regions: Baltic and Masurian-Podlasie NFR. The comparative analysis of NDVI confirmed that there is a need for additional investigation of the quality of newly developed forest mask combined with vegetation and meteorological data.


Author(s):  
Bohdan Mucha ◽  
Iryna Bulavenko ◽  
Oksana Rodych

The demonstration and analysis of the monthly and annual average air temperatures in Southern Roztochia for last 46 years are proposed. The meteorological data of the Roztochia landscapegeophysical station (RLGS) of Ivan Franko National University of Lviv have served as the starting material for this publication. The long-term value of the average air temperature in RLGS has been defined. The average temperature warming by 2 °C has occurred from 1970 to 2000 and the amplitude of fluctuations of average temperatures has increased since 2000. The fact of a gradual warming trend in the region Roztochia and the adjacent Small Polissia was confirmed as an attribute of the consequences of global warming and drainage reclamation during the XX century. The graphs for annual average, maximum and minimum air temperatures for last 46 years were concluded for the duration of 5 years at the seasons. The coldest period of research is the years 1969–1989 and the warmest ones are the years since 2000 and especially 2015. The parameters of extreme warming in 2015 were fixed in agriculture and water management. We are warning about the possibility of aridization of the territory as a result of the trend of warming. The ways of preventing of regional warming due to reducing the activity of drainage reclamation systems, conservation of forest and meadow vegetation are suggested. Key words: average air temperature, regional warming, extreme air temperature, Southern Roztochia.


2014 ◽  
Vol 27 (17) ◽  
pp. 6673-6686 ◽  
Author(s):  
Cameron R. Homeyer ◽  
Courtney Schumacher ◽  
Larry J. Hopper

Abstract Long-term radar observations from a subtropical location in southeastern Texas are used to examine the impact of storm systems with tropical or extratropical characteristics on the large-scale circulation. Climatological vertical profiles of the horizontal wind divergence are analyzed for four distinct storm classifications: cold frontal (CF), warm frontal (WF), deep convective upper-level disturbance (DC-ULD), and nondeep convective upper-level disturbances (NC-ULD). DC-ULD systems are characterized by weakly baroclinic or equivalent barotropic environments that are more tropical in nature, while the remaining classifications are representative of common midlatitude systems with varying degrees of baroclinicity. DC-ULD systems are shown to have the highest levels of nondivergence (LND) and implied diabatic heating maxima near 6 km, whereas the remaining baroclinic storm classifications have LND altitudes that are about 0.5–1 km lower. Analyses of climatological mean divergence profiles are also separated by rain regions that are primarily convective, stratiform, or indeterminate. Convective–stratiform separations reveal similar divergence characteristics to those observed in the tropics in previous studies, with higher altitudes of implied heating in stratiform rain regions, suggesting that the convective–stratiform paradigm outlined in previous studies is applicable in the midlatitudes. Divergence profiles that cannot be classified as primarily convective or stratiform are typically characterized by large regions of stratiform rain with areas of embedded convection of shallow to moderate extent (i.e., echo tops &lt;10 km). These indeterminate profiles illustrate that, despite not being very deep and accounting for a relatively small fraction of a given storm system, convection dominates the vertical divergence profile and implied heating in these cases.


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