World Weather Research Articles

THORPEX Research and the Science of Prediction

AbstractThe Observing System Research and Predictability Experiment (THORPEX) was a 10-yr, international research program organized by the World Meteorological Organization’s World Weather Research Program. THORPEX was motivated by the need to accelerate the rate of improvement in the accuracy of 1-day to 2-week forecasts of high-impact weather for the benefit of society, the economy, and the environment. THORPEX, which took place from 2005 to 2014, was the first major international program focusing on the advancement of global numerical weather prediction systems since the Global Atmospheric Research Program, which took place almost 40 years earlier, from 1967 through 1982. The scientific achievements of THORPEX were accomplished through bringing together scientists from operational centers, research laboratories, and the academic community to collaborate on research that would ultimately advance operational predictive skill. THORPEX included an unprecedented effort to make operational products readily accessible to the broader academic research community, with community efforts focused on problems where challenging science intersected with the potential to accelerate improvements in predictive skill. THORPEX also collaborated with other major programs to identify research areas of mutual interest, such as topics at the intersection of weather and climate. THORPEX research has 1) increased our knowledge of the global-to-regional influences on the initiation, evolution, and predictability of high-impact weather; 2) provided insight into how predictive skill depends on observing strategies and observing systems; 3) improved data assimilation and ensemble forecast systems; 4) advanced knowledge of high-impact weather associated with tropical and polar circulations and their interactions with midlatitude flows; and 5) expanded society’s use of weather information through applied and social science research.

The Subseasonal to Seasonal (S2S) Prediction Project Database

Abstract Demands are growing rapidly in the operational prediction and applications communities for forecasts that fill the gap between medium-range weather and long-range or seasonal forecasts. Based on the potential for improved forecast skill at the subseasonal to seasonal time range, the Subseasonal to Seasonal (S2S) Prediction research project has been established by the World Weather Research Programme/World Climate Research Programme. A main deliverable of this project is the establishment of an extensive database containing subseasonal (up to 60 days) forecasts, 3 weeks behind real time, and reforecasts from 11 operational centers, modeled in part on the The Observing System Research and Predictability Experiment (THORPEX) Interactive Grand Global Ensemble (TIGGE) database for medium-range forecasts (up to 15 days). The S2S database, available to the research community since May 2015, represents an important tool to advance our understanding of the subseasonal to seasonal time range that has been considered for a long time as a “desert of predictability.” In particular, this database will help identify common successes and shortcomings in the model simulation and prediction of sources of subseasonal to seasonal predictability. For instance, a preliminary study suggests that the S2S models significantly underestimate the amplitude of the Madden–Julian oscillation (MJO) teleconnections over the Euro-Atlantic sector. The S2S database also represents an important tool for case studies of extreme events. For instance, a multimodel combination of S2S models displays higher probability of a landfall over the islands of Vanuatu 2–3 weeks before Tropical Cyclone Pam devastated the islands in March 2015.

Upper-Level Winds over Southern Ontario: O-QNet Wind Profiler and NARR Comparisons

ABSTRACTUpper-level winds are primarily measured by tracking the position of radiosonde balloons as they rise through the atmosphere. Radiosondes are released from a global network at 0000 utc and 1200 utc each day, and data are quickly available to the world's weather services, as well as to the public. The network is relatively coarse spatially, and there are normally only two soundings per day. In an endeavour to provide better spatial and temporal upper-level regional wind measurements, the O-QNet (a demonstration very high frequency wind profiler network for Ontario and Quebec) was installed and has been operated by York, Western, and McGill Universities with support from Mardoc Inc., The Weather Network, and Environment and Climate Change Canada. Initial funding was provided by the Canada Foundation for Innovation, the Ontario Innovation Trust, and Mardoc Inc. The present paper reports primarily on comparisons between winds measured by the O-QNet profilers and the winds reported in the North American Regional Reanalysis (NARR). There is good agreement between the two, which provides support for the use of NARR data to investigate longer term variations in upper-level winds associated with climate change for this region.

Impact of climate change on heating and cooling energy demand in houses in Brazil

Energy consumption and thermal comfort in buildings are heavily affected by weather conditions. This study investigated the impact of climate change on thermal comfort conditions and on heating and cooling energy demand in dwellings in three cities in Brazil. Scenario A2 of the Intergovernmental Panel on Climate Change was selected to be used in the study. To quantify the impact, the Climate Change World Weather File Generator was used to produce weather data for future typical meteorological years, such as 2020, 2050 and 2080. The EnergyPlus computer programme was used to estimate the indoor air temperature and the annual heating and cooling energy demand in the future. In order to maintain the energy consumption in the houses at the level it is nowadays, passive design strategies such as solar shading, low absorptance and thermal insulation were assessed. Results show that there will be an increase in the annual energy demand ranging from 19%–65% among the three cities in 2020; 56%–112% in 2050; and 112%–185% in 2080. In the coldest city, the annual heating energy demand will decrease by 94% in 2080 due to an increase in the average temperature and global solar radiation. The use of passive design strategies may reduce up to 50% the future annual cooling and heating energy demand in houses in Brazil.

A Novel Visibility Restoration Technique for Hazy Videos Captured in Real - World Weather Conditions

A Novel Visibility Restoration Technique for Hazy Videos Captured in Real - World Weather Conditions

Intense convection over West Africa during AMMA SOP3 experiment

ERA-Interim product from the European Center for Medium-Range Weather Forecast (ECMWF) assimilation of African Monsoon Multidisciplinary Analysis (AMMA) resources, Meteosat satellite images, and synoptic observations were used to study local- and regional-scale environments associated with intense convective systems during the AMMA-SOP3 experiment over West Africa in the Northern Hemisphere of summer 2006. The convective system, from the 21st to 23rd of August 2006, was more active at 0000 and 1800UTC showing diurnal cycle of deep convection over West Africa where the African easterly waves (AEWs) are developed downstream. Downstream barotropic and baroclinic energy conversions associated with strong AEWs are important for the maintenance of AEW activity in West Africa. Barotropic energy conversions dominate south of the African easterly jet (AEJ), while baroclinic energy conversions are most important north of the AEJ. From a dynamical viewpoint, the low-level vorticity presents strong positive values over the sea and Sahara zone, indicating that exists on the cyclonic shear side of the African easterly jet, which is consistent with baroclinic growth. The 925-hPa equivalent potential temperature structure show a maximum over the Sahara which corresponds to the depression observed in this region. A mosaic of three hourly infrared (IR) satellite images, depicts a very distinct signal from an initial region of convection, developing through several stages and moving off the African coast. These observations, along with those available from the World Weather Watch, provide an opportunity to carry out numerical weather prediction (NWP) studies over West Africa utilizing high resolution limited area models.

Analyzing Personal Happiness from Global Survey and Weather Data: A Geospatial Approach.

Past studies have shown that personal subjective happiness is associated with various macro- and micro-level background factors, including environmental conditions, such as weather and the economic situation, and personal health behaviors, such as smoking and exercise. We contribute to this literature of happiness studies by using a geospatial approach to examine both macro and micro links to personal happiness. Our geospatial approach incorporates two major global datasets: representative national survey data from the International Social Survey Program (ISSP) and corresponding world weather data from the National Oceanic and Atmospheric Administration (NOAA). After processing and filtering 55,081 records of ISSP 2011 survey data from 32 countries, we extracted 5,420 records from China and 25,441 records from 28 other countries. Sensitivity analyses of different intervals for average weather variables showed that macro-level conditions, including temperature, wind speed, elevation, and GDP, are positively correlated with happiness. To distinguish the effects of weather conditions on happiness in different seasons, we also adopted climate zone and seasonal variables. The micro-level analysis indicated that better health status and eating more vegetables or fruits are highly associated with happiness. Never engaging in physical activity appears to make people less happy. The findings suggest that weather conditions, economic situations, and personal health behaviors are all correlated with levels of happiness.

A Review on Methods of Image Dehazing

Literature survey is an important for understanding and gaining much more knowledge about the specific area of a subject. The outdoor images captured in inclement weather are degraded due to the presence of haze, fog, rain and so on. Images of scenes captured in bad weather have poor contrasts and colors. This may cause difficulty in detecting the objects in the captured hazy images. Due to haze there is a trouble to many computer vision applications as it diminishes the visibility of the scene. This paper presents a study about different image dehazing methods to remove the haze from the hazy images captured in real world weather conditions to recover a fast and improved quality of haze free images. There is a improvement in terms of contrast, visible range and color fidelity. All these techniques are widely used in many applications such as outdoor Surveillance, object detection, underwater images, etc. General Terms Bad weather conditions, Haze, Airlight, Direct attenuation, contrast, color fidelity, Haze model.

Emergent Tropicality: Cyclone Mahina, Bathurst Bay 1899

In 1899 a Category 5 cyclone destroyed almost the entire pearling fleet of Bathurst Bay in North Queensland, sinking 55 ships and killing 307 people (approximately). Its historical status, however, is complicated. Measured by the numbers of lives lost, it is the most severe natural disaster in Australian history since European settlement. But most of the pearlers were either indigenous or foreign, excluded from the national imaginary. Hence the acknowledgement of Mahina’s status in national weather history had continually to be postponed. This is despite the fact that, in world weather history, Mahina holds the record for a storm surge, estimated at 13 metres (43 feet). It also contributed in a major way to making the personal history of the Queensland Government Meteorologist, Clement Wragge, who named it, for it was the first cyclone in world history to be given a personal (rather than a place) name. Wragge gave the cyclone the name of a Polynesian woman, predicting nonetheless that it would “not prove so soft and gentle as the Tahitian maiden of that name.” (For tropical cyclones he preferred female names; for the “cold, blustery cyclones on the polar front” he reserved masculine names (mostly of politicians who refused to subsidise his work). Focusing on Cyclone Mahina and its aftermath, this essay explores the entanglements of meterology and indigeneity in colonial governance in colonial Qyeensland on the eve of Federation. In the context of these historical entanglements, the paper reads Ian Townsend's "tropical gothic" novel, The Devil's Eye, as a remembering and imagining of the nation as it was and might have been.

Variability in thermal and phototactic preferences in Drosophila may reflect an adaptive bet-hedging strategy.

Organisms use various strategies to cope with fluctuating environmental conditions. In diversified bet‐hedging, a single genotype exhibits phenotypic heterogeneity with the expectation that some individuals will survive transient selective pressures. To date, empirical evidence for bet‐hedging is scarce. Here, we observe that individual Drosophila melanogaster flies exhibit striking variation in light‐ and temperature‐preference behaviors. With a modeling approach that combines real world weather and climate data to simulate temperature preference‐dependent survival and reproduction, we find that a bet‐hedging strategy may underlie the observed interindividual behavioral diversity. Specifically, bet‐hedging outcompetes strategies in which individual thermal preferences are heritable. Animals employing bet‐hedging refrain from adapting to the coolness of spring with increased warm‐seeking that inevitably becomes counterproductive in the hot summer. This strategy is particularly valuable when mean seasonal temperatures are typical, or when there is considerable fluctuation in temperature within the season. The model predicts, and we experimentally verify, that the behaviors of individual flies are not heritable. Finally, we model the effects of historical weather data, climate change, and geographic seasonal variation on the optimal strategies underlying behavioral variation between individuals, characterizing the regimes in which bet‐hedging is advantageous.

Commentary: Communicating climate complexity

Commentary: Communicating climate complexity

FROST-2014 project and meteorological support of the Sochi-2014 Olympics

In order to provide weather services to the 2014 Winter Olympics, the observational network in the Sochi region was strengthened with more than 40 automatic weather stations, the dual polarization Doppler radar, temperature and wind profilers, micro-rain radars, ets. These observation facilities allowed using the Sochi testbed for the development, testing, and intercomparison of various technologies of nowcasting and short-range numerical weather forecast. It was accomplished in the framework of the international project of the World Weather Research Program of WMO called FROST-2014 (Forecast and Research in the Olympic Sochi Testbed). The prognostic products of the FROST-2014 project was used for the operational meteorological servicing of Olympic events. Presented are the main research directions and the project preliminary results.

WWOSC 2014: research needs for better health resilience to weather hazards.

The first World Weather Open Science Conference (WWOSC, held from 17–21 August 2014 in Montreal, Québec), provided an open forum where the experience and perspective of a variety of weather information providers and users was combined with the latest application advances in social sciences. A special session devoted to health focused on how best the most recent weather information and communication technologies (ICT) could improve the health emergency responses to disasters resulting from natural hazards. Speakers from a plenary presentation and its corresponding panel shared lessons learnt from different international multidisciplinary initiatives against weather-related epidemics, such as malaria, leptospirosis and meningitis and from public health responses to floods and heat waves such as in Ontario and Quebec, Canada. Participants could bear witness to recent progress made in the use of forecasting tools and in the application of increased spatiotemporal resolutions in the management of weather related health risks through anticipative interventions, early alert and warning and early responses especially by vulnerable groups. There was an agreement that resilience to weather hazards is best developed based on evidence of their health impact and when, at local level, there is a close interaction between health care providers, epidemiologists, climate services, public health authorities and communities. Using near real time health data (such as hospital admission, disease incidence monitoring…) combined with weather information has been recommended to appraise the relevance of decisions and the effectiveness of interventions and to make adjustments when needed. It also helps appraising how people may be more or less vulnerable to a particular hazard depending on the resilience infrastructures and services. This session was mainly attended by climate, environment and social scientists from North American and European countries. Producing a commentary appears to be an effective way to share this session’s conclusions to research institutions and public health experts worldwide. It also advocates for better linking operational research and decision making and for appraising the impact of ICT and public health interventions on health.

Assessment of the Reliability of World Weather Online Forecasts for Kadoma Community

In recent times weather related catastrophes have become a commonplace. Many weather forecasters have taken the lead in furnishing individuals, corporate and governments with information. Consequently, little has been done to verify the accuracy of the weather reports and forecasts. This study therefore, compared and assessed the accuracy of forecasts given by World Weather Online with those of Meteorological Services Department for the case of Kadoma in Zimbabwe. The study also investigated the extent to which people benefit from using weather information as well as the challenges faced in accessing this information. Both quantitative and qualitative methods were used to gather data. Internet data mining, questionnaire and interview were used. Temperature and rainfall data were statistically analyzed while benefits and challenges were qualitatively assessed. The WWO forecasts for minimum temperatures had an accuracy of 96% while those for maximum temperature had an accuracy of 91.4% (percentage error of 8.6%). Rainfall forecasts showed a percentage correct of 60% and 56.7% for MSD and 70% and 66.7% for WWO for one day and twoday lead times, respectively. The researcher therefore recommended that the MSD defragment its regions into smaller areas to increase accuracy of forecasts. Awareness campaigns by all stakeholders were also seen as necessary in fostering understanding of weather reports and forecasts by the all people.

Effect of the temperature variation between Mediterranean Sea and Syrian deserts on the dust storm occurrence in the western half of Iran

Recent dust storms have caused crises in western Iran, which necessitate the prediction of these storms a few days before their occurrence. This is the first study of its type that analyzes the effect of temperature differences between the Mediterranean Sea surface and Syrian deserts (creation zone of the dusts storms) on the formation of dust storms in the west of Iran. The study also seeks to identify any changes in the atmospheric temperature created by the extreme dust storm of July 5, 2009 in west of Iran (Sanandaj City). In this study, the MODIS images from 2000 to 2008, and particulate matter data of the Sanandaj station from 2008 to 2012 were utilized to identify the dust storm days. The Mediterranean Sea surface temperature data were extracted from NOAA satellites for dust storm days up to four days preceding them. The web site of world weather was used to obtain the temperature of Damascus, Syria station as the selected land station. According to the results, significant differences were acquired between surface temperatures of Damascus station and the Mediterranean Sea in the dust storm days and up to three days before them. As the dust storm days approached, a rising trend was observed in changes of the temperature difference between land and sea. Thermal map analysis of the atmosphere of the Syrian deserts on July 5, 2009 showed significant decrease in the levels of 1000hPa and 500hPa but for the days preceding it no significant changes were observed. It can be concluded that the temperature difference between the Mediterranean Sea surface and the Syrian deserts four days before the dust storm occurrences is the important factor in predicting this event.

Opportunities and challenges in monsoon prediction in a changing climate

The South Asian monsoon is the pulse and life-line of over two billion inhabitants of the Indian subcontinent. The socio-economic development in this part of the world heavily depends on reliable predictions of the seasonal monsoon rainfall. Notwithstanding notable progress made in seasonal prediction of tropical climate during the past few decades, reliable forecasting of the South Asian summer monsoon has remained a ‘grand challenge’ problem. The problem gets more complicated in a warming environment with possible further degradation of the potential predictability. To define a way forward, an international Conference on “Opportunities and Challenges in Monsoon Prediction in a Changing Climate” (OCHAMP-2012) was organized during the period 21–25 February, 2012 at Pune, India, by the Indian Institute of Tropical Meteorology in association with World Climate Research Programme and World Weather Research Programme of World Meteorological Organization (WMO). The Conference was organized also to commemorate the Golden Jubilee of the Indian Institute of Tropical Meteorology

A Study on Water Demand Load Estimation by Using Unit of Living Water - Focused on Micro Water Supply Area in Daegu City

Water supply capability has been significantly reduced as water demand has been increased due to changes of the world's weather, causing the increase of drought frequency, and urbanization. In terms of water production, water can be secured by construction a dam or procuring substitute water. However, the study approaches in terms of management of water supply area to control the existing water efficiently. Therefore, water demand was estimated by buildings, by which water load of micro water supply area was calculated. As a result, the deviation of water demand for 1,357 micro water supply areas could be calculated while the alternatives to dissolve the spatial demand unbalance were suggested by two types. From the study, firstly, we could anticipate the total water supply demand from the total sum by filtration plants but it was not possible to anticipate the characteristics of distribution within urban areas. For this, the study attempted to anticipate the demand of each 250 thousands of buildings, comprehending the demand of micro areas. Secondly, based on the built results, we suggest the directions to dissolve the water demand unbalance between and among regions, which could be the foundation to suggest the concrete methodology in the future.

Root Reasons behind the Unusual Behaviors of the Earth climate thus the causes of Natural Disasters

Natural disaster have a number of root causes, but today with global warming, natural disasters have as their root cause, the change in the environment triggered by increasing differences in heat and cold. Greenhouse gases increase overall temperatures and this is masked by particles that contribute to global dimming. At the local level, global dimming causes drops in temperature and in areas where this is not the major factor, temperatures increase. As the atmosphere seeks to balance extremes, violent weather phenomena that contribute to natural disasters become more frequent. The results are more floods, drying leading to fire-storms, high winds, unseasonal freezes, ice-pack break up and meltdown, super hurricanes and rising sea levels that are a significant proportion of natural disasters today. Other natural disasters like tsunamis, solar dimming, volcanoes and impacts from space are not man made at this point in history and these will be not considered here. It comes as no surprise to many people today that there are records. In this article I have pointed out the main reason why the world weather is behaving rough.

Effect of lateral boundary perturbations on the breeding method and the local ensemble transform Kalman filter for mesoscale ensemble prediction

The effect of lateral boundary perturbations (LBPs) on the mesoscale breeding (MBD) method and the local ensemble transform Kalman filter (LETKF) as the initial perturbations generators for mesoscale ensemble prediction systems (EPSs) was examined. A LBPs method using the Japan Meteorological Agency's (JMA's) operational one-week global ensemble prediction was developed and applied to the mesoscale EPS of the Meteorological Research Institute for the World Weather Research Programme, Beijing 2008 Olympics Research and Development Project. The amplitude of the LBPs was adjusted based on the ensemble spread statistics considering the difference of the forecast times of the JMA's one-week EPS and the associated breeding/ensemble Kalman filter (EnKF) cycles. LBPs in the ensemble forecast increase the ensemble spread and improve the accuracy of the ensemble mean forecast. In the MBD method, if LBPs were introduced in its breeding cycles, the growth rate of the generated bred vectors is increased, and the ensemble spread and the root mean square errors (RMSEs) of the ensemble mean are further improved in the ensemble forecast. With LBPs in the breeding cycles, positional correspondences to the meteorological disturbances and the orthogonality of the bred vectors are improved. Brier Skill Scores (BSSs) also showed a remarkable effect of LBPs in the breeding cycles. LBPs showed a similar effect with the LETKF. If LBPs were introduced in the EnKF data assimilation cycles, the ensemble spread, ensemble mean accuracy, and BSSs for precipitation were improved, although the relative advantage of LETKF as the initial perturbations generator against MDB was not necessarily clear. LBPs in the EnKF cycles contribute not to the orthogonalisation but to prevent the underestimation of the forecast error near the lateral boundary.The accuracy of the LETKF analyses was compared with that of the mesoscale 4D-VAR analyses. With LBPs in the LETKF cycles, the RMSEs of the forecasts from the LETKF analysis were improved and some of them became comparable to those of the mesoscale 4D-VAR analyses based on the JMA's operational data assimilation system. These results show the importance of LBPs in the MBD method and LETKF. LBPs are critical not only to ameliorate the underestimation of the ensemble spread in the ensemble forecast but also to produce better initial perturbations and to improve the LETKF analysis.

Science of Nowcasting Olympic Weather for Vancouver 2010 (SNOW-V10): a World Weather Research Programme Project

A World Weather Research Programme (WWRP) project entitled the Science of Nowcasting Olympic Weather for Vancouver 2010 (SNOW-V10) was developed to be associated with the Vancouver 2010 Olympic and Paralympic Winter Games conducted between 12 February and 21 March 2010. The SNOW-V10 international team augmented the instrumentation associated with the Winter Games and several new numerical weather forecasting and nowcasting models were added. Both the additional observational and model data were available to the forecasters in real time. This was an excellent opportunity to demonstrate existing capability in nowcasting and to develop better techniques for short term (0–6 h) nowcasts of winter weather in complex terrain. Better techniques to forecast visibility, low cloud, wind gusts, precipitation rate and type were evaluated. The weather during the games was exceptionally variable with many periods of low visibility, low ceilings and precipitation in the form of both snow and rain. The data collected should improve our understanding of many physical phenomena such as the diabatic effects due to melting snow, wind flow around and over terrain, diurnal flow reversal in valleys associated with daytime heating, and precipitation reductions and increases due to local terrain. Many studies related to these phenomena are described in the Special Issue on SNOW-V10 for which this paper was written. Numerical weather prediction and nowcast models have been evaluated against the unique observational data set now available. It is anticipated that the data set and the knowledge learned as a result of SNOW-V10 will become a resource for other World Meteorological Organization member states who are interested in improving forecasts of winter weather.