scholarly journals Opportunities of short-term weather forecasts data in the environmental monitoring of the Kazakhstan

2020 ◽  
Vol 149 ◽  
pp. 03003
Author(s):  
Alexey Terekhov ◽  
Nurlan Abayev ◽  
Kainar Bolatov ◽  
Zaure Egemberdyeva
Keyword(s):  
Environmental Monitoring ◽  
Arid Zone ◽  
Meteorological Data ◽  
Warning System ◽  
Resource Monitoring ◽  
Short Term ◽  
Weather Forecasts ◽  
Temperature And Precipitation ◽  
Remote Measurements ◽  
Natural Resource Monitoring

This paper considers the possibilities of assimilation of FEWS NET (Famine early Warning System Network) products in natural resource monitoring of the territory of Kazakhstan in the cold period. With an area of 2.7 million km2, Kazakhstan is located in the center of Eurasia in the arid zone, and snow is one of the most important water sources in the first half of the vegetation season. The products “Snow Depth”, “Temperature” and “Precipitation” developed for Central Asia are based on model meteorological data, including short-term weather forecasts. This information, presented in the form of regular matrices, has several advantages in efficiency and spatial detailing over direct ground (remote) measurements of meteorological parameters. The use of FEWS NET products for the environmental monitoring of the entire territory of Kazakhstan or its separate parts is of benefit for assessing the current situation on snow reserves, weather regimes and prospects for spring snowmelt.

scholarly journals Evaluation of a Warning System for Controlling Primary Infections of Grapevine Downy Mildew

Plant Disease ◽  
2010 ◽  
Vol 94 (6) ◽  
pp. 709-716 ◽  
Author(s):  
T. Caffi ◽  
V. Rossi ◽  
R. Bugiani
Keyword(s):  
Disease Incidence ◽  
Warning System ◽  
Plasmopara Viticola ◽  
Short Message ◽  
Short Term ◽  
Infection Period ◽  
Grapevine Downy Mildew ◽  
Weather Forecasts ◽  
Short Message System ◽  
Message System

A warning system based on (i) a model that simulates the development of all cohorts of Plasmopara viticola oospores, from oospore germination to infection; (ii) short-term weather forecasts; and (iii) a mobile phone short message system was tested in Northern Italy, from 2006 to 2008. An unsprayed control was compared with a “Warning A” treatment (WA, fungicides were applied whenever the warning system predicted an infection period), a “Warning B” treatment (WB, fungicides were applied as in the WA treatment but only when the relative dimension of any oospore cohort predicted by the model exceeded a threshold), and a “grower” treatment (fungicides were applied according to a conventional schedule). Average disease incidence on leaves was reduced by up to 90% in sprayed plots compared with unsprayed plots. On bunches, efficacy was always >90% at fruit set; when most berries were touching, efficacy was higher for the WA (96%) than for grower (89%) and WB (85%) treatments. On average, 6.8 fungicide sprays were applied following the grower's schedule; use of the warning system reduced applications by about one-half (WA treatment) or two-thirds (WB treatment). The grower's schedule had an average cost of 337 €/ha; the average saving with the WA and the WB treatments was 174 and 224 €/ha, respectively.

scholarly journals A heat-health watch and warning system with extended season and evolving thresholds

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Mahamat Abdelkerim Issa ◽  
Fateh Chebana ◽  
Pierre Masselot ◽  
Céline Campagna ◽  
Éric Lavigne ◽  
...  
Keyword(s):  
Excess Mortality ◽  
Heat Waves ◽  
Meteorological Data ◽  
Warm Season ◽  
Warning System ◽  
Early Warning Systems ◽  
Climate Projections ◽  
Warning Systems ◽  
Extreme Heat Events ◽  
Watch And Warning System

Abstract Background Many countries have developed heat-health watch and warning systems (HHWWS) or early-warning systems to mitigate the health consequences of extreme heat events. HHWWS usually focuses on the four hottest months of the year and imposes the same threshold over these months. However, according to climate projections, the warm season is expected to extend and/or shift. Some studies demonstrated that health impacts of heat waves are more severe when the human body is not acclimatized to the heat. In order to adapt those systems to potential heat waves occurring outside the hottest months of the season, this study proposes specific health-based monthly heat indicators and thresholds over an extended season from April to October in the northern hemisphere. Methods The proposed approach, an adoption and extension of the HHWWS methodology currently implemented in Quebec (Canada). The latter is developed and applied to the Greater Montreal area (current population 4.3 million) based on historical health and meteorological data over the years. This approach consists of determining excess mortality episodes and then choosing monthly indicators and thresholds that may involve excess mortality. Results We obtain thresholds for the maximum and minimum temperature couple (in °C) that range from (respectively, 23 and 12) in April, to (32 and 21) in July and back to (25 and 13) in October. The resulting HHWWS is flexible, with health-related thresholds taking into account the seasonality and the monthly variability of temperatures over an extended summer season. Conclusions This adaptive and more realistic system has the potential to prevent, by data-driven health alerts, heat-related mortality outside the typical July–August months of heat waves. The proposed methodology is general and can be applied to other regions and situations based on their characteristics.

scholarly journals Reconstruction of the annual balance of Vadret da Morteratsch, Switzerland, since 1865

2009 ◽  
Vol 50 (50) ◽  
pp. 126-134 ◽  
Author(s):  
Johanna Nemec ◽  
Philippe Huybrechts ◽  
Oleg Rybak ◽  
Johannes Oerlemans
Keyword(s):  
Meteorological Data ◽  
Balance Model ◽  
Surface Energy Fluxes ◽  
Temperature And Precipitation ◽  
Continuous Mass ◽  
Weather Stations ◽  
Precipitation Records ◽  
High Elevations ◽  
Annual Balance ◽  
Almost Continuous

AbstractWe have reconstructed the annual balance of Vadret da Morteratsch, Engadine, Switzerland, with a two-dimensional energy-balance model for the period 1865–2005. The model takes into account a parameterization of the surface energy fluxes, an albedo that decreases exponentially with snow depth as well as the shading effect of the surrounding mountains. The model was first calibrated with a 5 year record of annual balance measurements made at 20 different sites on the glacier between 2001 and 2006 using meteorological data from surrounding weather stations as input. To force the model for the period starting in 1865, we employed monthly temperature and precipitation records from nearby valley stations. The model reproduces the observed annual balance reasonably well, except for the lower part during the warmest years. Most crucial to the results is the altitudinal precipitation gradient, but this factor is hard to quantify from the limited precipitation data at high elevations. The simulation shows an almost continuous mass loss since 1865, with short interruptions around 1920, 1935 and 1980. A trend towards a more negative annual balance can be observed since the beginning of the 1980s. The simulated cumulative mass balance for the entire period 1865–2005 was found to be –46mw.e.

scholarly journals Toward an Improved Air Pollution Warning System in Quebec

2019 ◽  
Vol 16 (12) ◽  
pp. 2095 ◽  
Author(s):  
Pierre Masselot ◽  
Fateh Chebana ◽  
Éric Lavigne ◽  
Céline Campagna ◽  
Pierre Gosselin ◽  
...  
Keyword(s):  
Air Pollution ◽  
Excess Mortality ◽  
Fine Particulate Matter ◽  
Warning System ◽  
Quebec City ◽  
Local Health ◽  
Warning Systems ◽  
Health Warnings ◽  
Short Term ◽  
Fine Particulate

The nature of pollutants involved in smog episodes can vary significantly in various cities and contexts and will impact local populations differently due to actual exposure and pre-existing sensitivities for cardiovascular or respiratory diseases. While regulated standards and guidance remain important, it is relevant for cities to have local warning systems related to air pollution. The present paper proposes indicators and thresholds for an air pollution warning system in the metropolitan areas of Montreal and Quebec City (Canada). It takes into account past and current local health impacts to launch its public health warnings for short-term episodes. This warning system considers fine particulate matter (PM2.5) as well as the combined oxidant capacity of ozone and nitrogen dioxide (Ox) as environmental exposures. The methodology used to determine indicators and thresholds consists in identifying extreme excess mortality episodes in the data and then choosing the indicators and thresholds to optimize the detection of these episodes. The thresholds found for the summer were 31 μg/m3 for PM2.5 and 43 ppb for Ox in Montreal, and 32 μg/m3 and 23 ppb in Quebec City. In winter, thresholds found were 25 μg/m3 and 26 ppb in Montreal, and 33 μg/m3 and 21 ppb in Quebec City. These results are in line with different guidelines existing concerning air quality, but more adapted to the cities examined. In addition, a sensitivity analysis is conducted which suggests that Ox is more determinant than PM2.5 in detecting excess mortality episodes.

Spatial distribution and temporal variability of open fire in China

2017 ◽  
Vol 26 (2) ◽  
pp. 122 ◽  
Author(s):  
Kunpeng Yi ◽  
Yulong Bao ◽  
Jiquan Zhang
Keyword(s):  
Meteorological Data ◽  
Fire Season ◽  
Spatial And Temporal Patterns ◽  
Burnt Area ◽  
The North ◽  
Temperature And Precipitation ◽  
North Eastern ◽  
Vegetation Fires ◽  
Precipitation Variation ◽  
Two Peaks

This study presents the spatial and temporal patterns of vegetation fires in China based on a combination of national fire records (1950–2010) and satellite fire data (2001–12). This analysis presents the first attempt to understand existing patterns of open fires and their consequences for the whole of China. We analysed inter- and intra-annual fire trends and variations in nine subregions of China as well as associated monthly meteorological data from 130 stations within a 50-year period. During the period 2001–12, an average area of 3.2 × 106 ha was consumed by fire per year in China. The Chinese fire season has two peaks occurring in the spring and autumn. The profiles of the burnt area for each subregion exhibit distinct seasonality. The majority of the vegetation fires occurred in the north-eastern and south-western provinces. We analysed quantitative relationships between climate (temperature and precipitation) and burnt area. The results indicate a synchronous relationship between precipitation variation and burnt area. The data in this paper reveal how climate and human activities interact to create China’s distinctive pyrogeography.

scholarly journals Summer drought in Switzerland 1981‒2020: Events, trends and drivers

2021 ◽  
Author(s):  
Simon C. Scherrer ◽  
Christoph Spirig ◽  
Martin Hirschi ◽  
Felix Maurer ◽  
Sven Kotlarski
Keyword(s):  
Regional Climate Model ◽  
Soil Water ◽  
Climate Model ◽  
Potential Evapotranspiration ◽  
Meteorological Data ◽  
Regional Climate ◽  
Reanalysis Data ◽  
Summer Drought ◽  
Temperature And Precipitation ◽  
Temperature Scaling

<p>The Alpine region has recently experienced several dry summers with negative impacts on the economy, society and ecology. Here, soil water, evapotranspiration and meteorological data from several observational and model-based data sources is used to assess events, trends and drivers of summer drought in Switzerland in the period 1981‒2020. 2003 and 2018 are identified as the driest summers followed by somewhat weaker drought conditions in 2020, 2015 and 2011. We find clear evidence for an increasing summer drying in Switzerland. The observed climatic water balance (-39.2 mm/decade) and 0-1 m soil water from reanalysis (ERA5-Land: -4.7 mm/decade; ERA5: -7.2 mm/decade) show a clear tendency towards summer drying with decreasing trends in most months. Increasing evapotranspiration (potential evapotranspiration: +21.0 mm/decade; ERA5-Land actual evapotranspiration: +15.1 mm/decade) is identified as important driver which scales excellently (+4 to +7%/K) with the observed strong warming of about 2°C. An insignificant decrease in precipitation further enhanced the tendency towards drier conditions. Most simulations of the EURO-CORDEX regional climate model ensemble underestimate the changes in summer drying. They underestimate both, the observed recent summer warming and the small decrease in precipitation. The changes in temperature and precipitation are negatively correlated, i.e. simulations with stronger warming tend to show (weak) decreases in precipitation. However, most simulations and the reanalysis overestimate the correlation between temperature and precipitation and the precipitation-temperature scaling on the interannual time scale. Our results emphasize that the analysis of the regional summer drought evolution and its drivers remains challenging especially with regional climate model data but considerable uncertainties also exist in reanalysis data sets.</p>

scholarly journals Currency crises in EU candidate countries: An early warning system approach

2015 ◽  
Vol 62 (4) ◽  
pp. 493-510 ◽  
Author(s):  
Vesna Bucevska
Keyword(s):  
Early Warning ◽  
Early Warning System ◽  
Currency Crises ◽  
Warning System ◽  
Growth Potential ◽  
Short Term ◽  
Gdp Growth Rate ◽  
Fiscal Balance ◽  
Eu Candidate Countries ◽  
External Indebtedness

The purpose of this paper is to develop an econometric model of early warning system (EWS) for predicting currency crises in EU candidate countries. Using actual quarterly panel data for three EU candidate countries (Croatia, Macedonia and Turkey) in the period January 2005 - June 2010, we estimate a binomial logit model, which accurately predicts potential episodes of outbreak of currency crisis. In addition, we find that real GDP growth rate, participation in an IMF loan program, current account and fiscal balance and short-term external indebtedness are the most significant common predictors of currency crises across EU candidate countries. These results imply implementing policy measures aimed at raising the growth potential of the domestic economies of EU candidate countries, monitoring their short-term external indebtedness, improving their external competitiveness, cutting public spending and increasing the confidence of residents and non-residents in their domestic banking sectors.

scholarly journals PREDICTING DAILY PM2.5 USING WEIGHTED LONG SHORT-TERM MEMORY NEURAL NETWORK MODEL

2020 ◽  
Vol XLIII-B3-2020 ◽  
pp. 1451-1455
Author(s):  
H. Fan ◽  
M. Yang ◽  
F. Xiao ◽  
K. Zhao
Keyword(s):  
Neural Network ◽  
Air Pollution ◽  
Short Term Memory ◽  
Meteorological Data ◽  
Series Data ◽  
Wind Condition ◽  
Short Term ◽  
Term Memory ◽  
Long Short Term Memory ◽  
Pm2.5 Concentration

Abstract. Over the past few decades, air pollution has caused serious damage on public health, thus making accurate predictions of PM2.5 crucial. Due to the transportation of air pollutants among areas, the PM2.5 concentration is strongly spatiotemporal correlated. However, the distribution of air pollution monitoring sites is not even, making the spatiotemporal correlation between the central site and surrounding sites varies with different density of sites, and this was neglected by most existing methods. To tackle this problem, this study proposed a weighted long short-term memory neural network extended model (WLSTME), which addressed the issue that how to consider the effect of the density of sites and wind condition on the spatiotemporal correlation of air pollution concentration. First, several the nearest surrounding sites were chosen as the neighbour sites to the central station, and their distance as well as their air pollution concentration and wind condition were input to multi-layer perception (MLP) to generate weighted historical PM2.5 time series data. Second, historical PM2.5 concentration of the central site and weighted PM2.5 series data of neighbour sites were input into LSTM to address spatiotemporal dependency simultaneously and extract spatiotemporal features. Finally, another MLP was utilized to integrate spatiotemporal features extracted above with the meteorological data of central site to generate the forecasts future PM_2.5 concentration of the central site. Daily PM_2.5 concentration and meteorological data on Beijing–Tianjin–Hebei from 2015 to 2017 were collected to train models and evaluate the performance. Experimental results with 3 other methods showed that the proposed WLSTME model has the lowest RMSE (40.67) and MAE (26.10) and the highest p (0.59). This finding confirms that WLSTME can significantly improve the PM2.5 prediction accuracy.

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