World Meteorological Organization Research Articles

Severe Weather Warnings for Sofia, Bulgaria: May – September 2010–2019

Severe weather monitoring and forecasting is the prime task of the National Meteorological Services according to World Meteorological Organization Guidelines (WMO). Since 2009 Bulgarian National Institute of Meteorology and Hydrology (NIMH) issues 48 h ahead severe weather warnings as a contribution to the European warning system (METEOALARM). A total of 243 days with warnings for heat, thunderstorms and intense rain were issued for the period May-September 2010–2019. The monthly maximum for heat is 42 days in July, for thunderstorms it is 26 days in June, and for intense rain it is 27 days in June. Objective circulation classification is conducted which shows that the majority of heat warnings are associated with Anticyclonic and West flow circulation types. About 40% of thunderstorm warnings are of Cyclone type followed by 28.6% of Cyclonic Directional types. For rain warnings, most of the days are with Cyclone type (46.2%) and Cyclonic Directional types (27.5%). Analysis of Global Navigation Satellite Systems (GNSS) derived Integrated Water Vapour (IWV), from the Bulgarian station in Sofia, shows consistently higher values for the days with METEOALARM warnings for heat, thunderstorm and rain.

Revising VOC emissions speciation improves the simulation of global background ethane and propane

Abstract. Non-methane volatile organic compounds (NMVOCs) generate ozone (O3) when they are oxidised in the presence of oxides of nitrogen, modulate the oxidative capacity of the atmosphere and can lead to the formation of aerosol. Here, we assess the capability of a chemical transport model (GEOS-Chem) to simulate NMVOC concentrations by comparing ethane, propane and higher-alkane observations in remote regions from the NOAA flask Network and the World Meteorological Organization's Global Atmosphere Watch (GAW) network. Using the Community Emissions Data System (CEDS) inventory, we find a significant underestimate in the simulated concentration of both ethane (35 %) and propane (64 %), consistent with previous studies. We run a new simulation in which the total mass of anthropogenic NMVOC emitted in a grid box is the same as that used in CEDS but with the NMVOC speciation derived from regional inventories. For US emissions, we use the National Emissions Inventory (NEI); for Europe, we use the UK National Atmospheric Emissions Inventory (NAEI); and for China, we use the Multi-resolution Emission Inventory model for Climate and air pollution research (MEIC). These changes lead to a large increase in the modelled concentrations of ethane, improving the mean model bias from −35 % to −4 %. Simulated propane also improves (from −64 % to −48 % mean model bias), but there remains a substantial model underestimate. There were relatively minor changes to other NMVOCs. The low bias in simulated global ethane concentration is essentially removed, resolving one long-term issue in global simulations. Propane concentrations are improved but remain significantly underestimated, suggesting the potential for a missing global propane source. The change in the NMVOC emission speciation results in only minor changes in tropospheric O3 and OH concentrations.

Bringing the Value Chain for High-Impact Weather Warnings into the Classroom

Abstract University students can learn about weather warnings and contribute to a database for the World Meteorological Organization (WMO) project on Value Chain Approaches to Evaluate the End-to-End Warning Chain. The project offers students a way to understand how information about high-impact weather is created, shared, and used within a complete warning system for a selected event. Their contributions are intended to inform researchers and practitioners on what has and what has not worked well in the warning process. The students use a structured questionnaire designed to collect information on observations, forecasting, hazards, impacts, warning communications, and responses. Two institutions took contrasting approaches to using the questionnaire. At the University of Miami, teams of meteorology undergraduates evaluated the value chain for three hurricanes. Among the issues identified were the dynamic nature of the forecasts, misinterpretations of the products, social media influences, demographic factors, and disparities in responses. The Australian Bureau of Meteorology engaged student interns in different disciplines and experience levels to evaluate and contrast the warning value chains for domestic and international events. The students expressed enthusiasm for the exercises. Educational benefits included team collaboration, critical thinking, research and composition skills, a comprehensive view of weather events, understanding information flow, learning about new tools, and identifying gaps in practices. We encourage educators to adopt similar exercises to enable students to develop these skills, adopt value chain ideas, and contribute meaningfully to the community. The level of maintenance is low, and there is flexibility in how the exercises can be developed.

Extremes of Weather Conditions and Child Health

Background: The number of people exposed to extreme heat is growing exponentially due to climate change worldwide. Heat-related mortality for people over 65 years of age and young children has increased by 85% between 2000–2004 and 2017–2021. World Meteorological Organization announced that there’s an 80% chance that the world will exceed the 1.5 °C temperature limit in at least one of the next 5 years. Aim: To review the impact of extremes of climate changes on Children’s health based on cases managed and reported in media. Methods: Material & Methods: This article is a review of the impact of extremes of heat & Cold weather on children, based on personal handling of cases and media reports of the adverse effects of heat this summer, exercising /punishing children in hot and cold weather. Key findings: Most children experience increased thirst, weakness, headache, dizziness or fainting, muscle cramps, nausea and/or vomiting, irritability, prickly heat & heavy sweating. Dehydration in children is more than just being thirsty, as it is a condition where there isn’t enough fluid in the body because children lose more water than they take in. High heat stress also reduces physical work capacity and motor-cognitive performances, with consequences for school attendance for children. The cold weather itself doesn’t cause illness, but it weakens the immune system, making it a lot harder for the child to fight off infections. Conclusion: Temperatures above long-term averages during summer months and heatwaves are associated with cardiorespiratory and other diseases and mental health issues. Very young children are particularly vulnerable to the effects of heat, irrespective of income level or geographical region. Most heat-related mortality and morbidities are preventable with individual efforts like avoidance of exposure, improved community preparedness, and Public Health Advisory.

Special Observing Period (SOP) data for the Year of Polar Prediction site Model Intercomparison Project (YOPPsiteMIP)

Abstract. The rapid changes occurring in the polar regions require an improved understanding of the processes that are driving these changes. At the same time, increased human activities such as marine navigation, resource exploitation, aviation, commercial fishing, and tourism require reliable and relevant weather information. One of the primary goals of the World Meteorological Organization's Year of Polar Prediction (YOPP) project is to improve the accuracy of numerical weather prediction (NWP) at high latitudes. During YOPP, two Canadian “supersites” were commissioned and equipped with new ground-based instruments for enhanced meteorological and system process observations. Additional pre-existing supersites in Canada, the United States, Norway, Finland, and Russia also provided data from ongoing long-term observing programs. These supersites collected a wealth of observations that are well suited to address YOPP objectives. In order to increase data useability and station interoperability, novel Merged Observatory Data Files (MODFs) were created for the seven supersites over two Special Observing Periods (February to March 2018 and July to September 2018). All observations collected at the supersites were compiled into this standardized NetCDF MODF format, simplifying the process of conducting pan-Arctic NWP verification and process evaluation studies. This paper describes the seven Arctic YOPP supersites, their instrumentation, data collection and processing methods, the novel MODF format, and examples of the observations contained therein. MODFs comprise the observational contribution to the model intercomparison effort, termed YOPP site Model Intercomparison Project (YOPPsiteMIP). All YOPPsiteMIP MODFs are publicly accessible via the YOPP Data Portal (Whitehorse: https://doi.org/10.21343/a33e-j150, Huang et al., 2023a; Iqaluit: https://doi.org/10.21343/yrnf-ck57, Huang et al., 2023b; Sodankylä: https://doi.org/10.21343/m16p-pq17, O'Connor, 2023; Utqiaġvik: https://doi.org/10.21343/a2dx-nq55, Akish and Morris, 2023c; Tiksi: https://doi.org/10.21343/5bwn-w881, Akish and Morris, 2023b; Ny-Ålesund: https://doi.org/10.21343/y89m-6393, Holt, 2023; and Eureka: https://doi.org/10.21343/r85j-tc61, Akish and Morris, 2023a), which is hosted by MET Norway, with corresponding output from NWP models.

The Use of Weather, Water, Ice, and Climate (WWIC) Information in the Polar Regions: What Is Known after the Decadelong Polar Prediction Project?

Abstract The polar regions are facing a wide range of compounding challenges, from climate change to increased human activity. Infrastructure, rescue services, and disaster response capabilities are limited in these remote environments. Relevant and usable weather, water, ice, and climate (WWIC) information is vital for safety, activity success, adaptation, and environmental protection. This has been a key focus for the World Meteorological Organization’s (WMO) Polar Prediction Project (PPP), and in particular its “Societal and Economic Research and Applications” (PPP-SERA) Task Team, which together over a decade have sought to understand polar WWIC information use in relation to operational needs, constraints, and decision contexts to inform the development of relevant services. To understand research progress and gaps on WWIC information use during the PPP (2013–23), we undertook a systematic bibliometric review of aligned scholarly peer-reviewed journal articles (n = 43), examining collaborations, topics, methods, and regional differences. Themes to emerge included activity and context, human factors, information needs, situational awareness, experience, local and Indigenous knowledge, and sharing of information. We observed an uneven representation of disciplinary backgrounds, geographic locations, research topics, and sectoral foci. Our review signifies an overall lack of Antarctic WWIC services research and a dominant focus on Arctic sea ice operations and risks. We noted with concern a mismatch between user needs and services provided. Our findings can help to improve WWIC services’ dissemination, communication effectiveness, and actionable knowledge provision for users and guide future research as the critical need for salient weather services across the polar regions remains beyond the PPP. Significance Statement Every day, people in the Arctic and Antarctic use weather, water, ice, and climate information to plan and carry out outdoor activities and operations in a safe way. Despite advances in numerical weather prediction, technology, and product development, barriers to accessing and effectively communicating high-quality usable observations, forecasts, and actionable knowledge remain. Poorer services, prediction accuracy, and interpretation are exacerbated by a lack of integrated social science research on relevant topics and a mismatch between the services provided and user needs. As a result, continued user engagement, research focusing on information use, risk communication, decision-making processes, and the application of science for services remain highly relevant to reducing risks and improving safety for people living, visiting, and working in the polar regions.

Low Tropospheric Wind Forecasts in Aviation: The Potential of Deep Learning for Terminal Aerodrome Forecast Bulletins

In aviation, accurate wind prediction is crucial, especially during takeoff and landing at complex sites like Gran Canaria Airport. This study evaluated five Deep Learning models: Long Short-Term Memory (LSTM), Vanilla Recurrent Neural Network (vRNN), One-Dimensional Convolutional Neural Network (1dCNN), Convolutional Neural Network Long Short-Term Memory (CNN-LSTM), and Gated Recurrent Unit (GRU) for forecasting wind speed and direction. The LSTM model demonstrated the highest precision, particularly for extended forecasting periods, achieving a mean absolute error (MAE) of 1.23 m/s and a circular MAE (cMAE) of 15.80° for wind speed and direction, respectively, aligning with World Meteorological Organization standards for Terminal Aerodrome Forecasts (TAF). While the GRU and CNN-LSTM also showed promising results, and the 1dCNN excelled in wind direction forecasting over shorter intervals, the vRNN lagged in performance. Additionally, the autoregressive integrated moving average model underperformed relative to the DL models, underscoring the potential of DL, particularly LSTM, in enhancing TAF accuracy at airports with intricate wind patterns. This study not only confirms the superiority of DL over traditional methods but also highlights the promise of integrating artificial intelligence into TAF automation.

WMO Global Energy Resilience Atlas—Climate Risk Indices for Hydropower

The importance of energy transition was underlined at COP28 in Dubai, where governments committed to tripling renewables capacities and doubling the rate of energy efficiency by 2030. However, the power generated by climate-dependent energy sources exhibits greater vulnerability to potential climate changes in the long term. Therefore, climate models play a pivotal role in estimating the effects of climate change on renewables in the context of strategic planning for the development and operation of new renewable power plants. In this context, the World Meteorological Organization (WMO) developed a Global Energy Resilience Atlas aimed at providing insights into the climate change risks for the hydropower sector, the largest renewable electricity source for most countries, generating over 4300 TWh globally. This study focuses on defining four Hydro Climate Risk indices (HCRIs) using historical and climate projection precipitation data for three climate scenarios. The final product is a freely available and interactive tool. The developed methodology and tool address how climate changes have historically affected hydropower generation and how they will impact the future at national scales. The final product also addresses the needs of policymakers at national, regional, and global levels in crafting long-term planning for a more secure energy sector, accelerating the energy transition to more sustainable and reliable energies.

Review of the development of hydrological data quality control in Typhoon Committee Members

Nowadays, with the continual development of the science and technology applied in data observation, monitoring and collection, human has more and more means and channels to obtain various data, consequently, the amount of collected and stored data is also getting bigger and bigger. In recent years, hydro-meteorological data have multiplied in some Typhoon Committee (TC) Members. Data-based advanced technology applications in TC, such as application of Artificial Intelligent (AI) and impact-based typhoon disaster forecasting and early warning, has emerged one after another. A consistent and integrated data quality management system is crucial for ensuring accurate hydrological and meteorological analysis and prediction. Considering the importance and urgent necessary, TC working group on hydrology (WGH) conducted a cooperation project on data quality management in the past years with the major objective of improving the capacity of TC Members on integrated data quality control and processing. Despite the significant improvements, the uncertainties and difficulties in processing the full-elements of hydro-meteorological data still persist in hydro-meteorological data. To tackle these challenges and further enhance the data quality management system, the integration of AI technology shows great promise. By examining the data quality management system at World Meteorological Organization (WMO) as a starting point, this paper explored how related organizations in China, Japan, Malaysia, Philippines and Republic of Korea, manage the quality of hydro-meteorological data; reviewed the current status of hydro-meteorological data quality control in TC Members, and discussed the potential areas to be enhanced in future.

Drought Assessment in a Changing Climate: A Review of Climate Normals for Drought Indices

ABSTRACT: Should drought be considered an extreme dry period based on the entire record of available data? Or, should drought be considered a low in precipitation variability within the context of a present, contemporary climate? The two most common reference periods are the full period of record (all observed data or as much as possible) and a 30-year reference climatology. However, climate non-stationarity may render the "all-data" ap-proach an inaccurate or obsolete comparison unless a trend is factored in. The aim of this review is to explore the literature for approaches to addressing these issues. The World Meteorological Organization (WMO) has recommended a 30-year reference period for most climatological applications since 1935, but for drought assessments and drought indices the modus operandi has been to use as much data as possible. However, in the literature, the “all data” approach has been challenged by evident impacts from climate change-induced non-stationarity. Over the past several years, as potential errors in drought assessments became more apparent due to a stationarity assumption when applying drought indices, several studies have adopted shorter reference periods, with 30-years being the most common. Furthermore, several recent papers have recommended using short reference periods with more frequent data updates for drought assessments to be representative of a contemporary climate. Additionally, at least 18 non-stationary drought indices have been proposed in efforts to retain long datasets and account for non-stationarity in the climate system.

Drought Monitoring and Prediction in Agriculture: Employing Earth Observation Data, Climate Scenarios and Data Driven Methods; a Case Study: Mango Orchard in Tamale, Ghana

The study focused on the prediction of the Temperature Vegetation Dryness Index (TVDI), an agricultural drought index, for a Mango orchard in Tamale, Ghana. It investigated the temporal relationship between the meteorological drought index, Standardized Precipitation Index (SPI), and TVDI. The SPI was calculated based on utilizing precipitation data from the World Meteorological Organization (WMO) database (2010–2022) and CMIP6 projected precipitation data (2023–2050) from 35 climate models representing various Shared Socioeconomic Pathway (SSP) climate change scenarios. Concurrently, TVDI was derived from Landsat 8/9 satellite imagery, validated using thermal data obtained from unmanned aerial vehicle (UAV) surveys. A comprehensive cross-correlation analysis between TVDI and SPI was conducted to identify lag times between these indices. Building on this temporal relationship, the TVDI was modeled as a function of SPI, with varying lag times as inputs to the Wavelet-Adaptive Neuro-Fuzzy Inference System (Wavelet-ANFIS). This innovative approach facilitated robust predictions of TVDI as an agricultural drought index, specifically relying on SPI as a predictor of meteorological drought occurrences for the years 2023–2050. The research outcome provides practical insights into the dynamic nature of drought conditions in the Tamale mango orchard region. The results indicate significant water stress projected for different time frames: 186 months for SSP126, 183 months for SSP245, and 179 months for both SSP370 and SSP585. This corresponds to a range of 55–57% of the projected months. These insights are crucial for formulating proactive and sustainable strategies for agricultural practices. For instance, implementing supplemental irrigation systems or crop adaptations can be effective measures. The anticipated outcomes contribute to a nuanced understanding of drought impacts, facilitating informed decision-making for agricultural planning and resource allocation.

Two Decades of Integrated Flood Management: Status, Barriers, and Strategies

Losses from flood disasters are increasing globally due to climate-driven forces and human factors such as migration and land use changes. The risks of such floods involve multiple factors and stakeholders, and frameworks for integrated approaches have attracted a global community of experts. The paper reviews the knowledge base for integrated flood risk management frameworks, including more than twenty bibliometric reviews of their elements. The knowledge base illustrates how integrated strategies for the reduction of flood risk are required at different scales and involve responses ranging from climate and weather studies to the construction of infrastructure, as well as collective action for community resilience. The Integrated Flood Management framework of the Associated Programme on Flood Management of the World Meteorological Organization was developed more than twenty years ago and is explained in some detail, including how it fits within the Integrated Water Resources Management concept that is managed by the Global Water Partnership. The paper reviews the alignment of the two approaches and how they can be used in tandem to reduce flood losses. Success of both integrated management approaches depends on governance and institutional capacity as well as technological advances. The knowledge base for flood risk management indicates how technologies are advancing, while more attention must be paid to social and environmental concerns, as well as government measures to increase participation, awareness, and preparedness. Ultimately, integrated flood management will involve solutions tailored for individual situations, and implementation may be slow, such that perseverance and political commitment will be needed.

КӨПЖЫЛДЫҚ ГИДРОМЕТЕОРОЛОГИЯЛЫҚ МӘЛІМЕТТЕРІ НЕГІЗІНДЕ ЖАЙЫҚ-КАСПИЙ СУШАРУАШЫЛЫҚ АЛАБЫНДАҒЫ ГИДРОЛОГИЯЛЫҚ ҚҰРҒАҚШЫЛЫҚТЫ БАҒАЛАУ

The article considers the problem of effective detection of the beginning and end of hydrological drought in the territory of Zhayk-Caspian water basin. Standardized Precipitation index (SPI) recommended by the World Meteorological Organization selected as drought predictor indicator. Based on the SPI Generator Application determined the characteristics of severe and extreme droughts from the beginning of instrumental observations to 2020 year. The results of the studies showed the effectiveness of the SPI index in detecting dry periods of the area under consideration, which allowed a differentiated diagnosis of hydrological droughts and their timing. The findings have practical relevance for agriculture and other water-dependent industries, information on the types and timing of droughts can be used to develop effective strategies to manage the water resources of the region and minimize the negative impacts of hydrological droughts.

Observed Global Changes in Sector‐Relevant Climate Extremes Indices—An Extension to HadEX3

AbstractGlobal gridded data sets of observed extremes indices underpin assessments of changes in climate extremes. However, similar efforts to enable the assessment of indices relevant to different sectors of society have been missing. Here we present a data set of sector‐specific indices, based on daily station data, that extends the HadEX3 data set of climate extremes indices. These additional indices, which can be used singly or in combinations, have been recommended by the World Meteorological Organization and are intended to empower decision makers in different sectors with accurate historical information about how sector‐relevant measures of the climate are changing, especially in regions where in situ daily temperature and rainfall data are hard to come by. The annual and/or monthly indices have been interpolated on to a 1.875° × 1.25° longitude‐latitude grid for 1901–2018. We show changes in globally‐averaged time series of these indices in comparison with reanalysis products. Changes in temperature‐based indices are consistent with global scale warming, with days with Tmax > 30°C (TXge30) increasing virtually everywhere with potential impacts on crop fertility. At the other end of the scale, the number of days with Tmin < −2°C (TNltm2) are reducing, decreasing potential damage from frosts. Changes in heat wave characteristics show increases in the number, duration and intensity of these extreme events in most places. The gridded netCDF files and, where possible, the underlying station indices are available from https://www.metoffice.gov.uk/hadobs/hadex3 and https://www.climdex.org.

Climatological reference stations: Definitions and requirements

AbstractGround‐based stations are one of many observing systems contributing to the generation of data to evaluate climate trends and variations locally and globally. Networks of stations are made of various numbers of observing sites, equipped with different typologies and varieties of instruments, differently managed and maintained. Among such networks a limited number of stations are required as a reference, to provide top quality traceable measurements and as the top level of a tiered approach; it is these stations which are here designated as Climatological Reference Stations (CRS). At present, there is no agreed definition of the key instrumental and technical features of a CRS, nor are there defined reference measurement procedures. This leads to the situation of a multitude of approaches among different National Meteorological and Hydrological Services (NMHSs), research institutes and other agencies that reduces the comparability of results in space and in time. The lack of CRSs, moreover, is a major contributor to the huge efforts required to harmonize data and detect biases locally, regionally and globally, as in their absence there is a need to fall back on other stations which are more likely to have such biases. This article reports on the outcomes of the work of a group of experts, nominated by the World Meteorological Organization (WMO) Commission for Climatology (CCI), tasked to promote a standardized and agreed concept about the definitions, specifications and technical characteristics of climate reference data and stations for ground‐based networks, with the addition of a practical example of climatological reference station installed in the framework of an European funded project, with the purpose of comparing and confirming the prescribed characteristics and guidance, with respect to practical field use and available instrumentation. The adoption of a unique definition and prescription on the technical setup, measurement procedures and uncertainty evaluation will substantially progress towards a common approach in detecting climate trends. This will improve data comparability in space and time and allow a more robust understanding of climate evolution locally and globally.

Climate change and heatwaves: Improving Ontario’s harmonized heat warning and information system

Created in 2015, Ontario’s Harmonized Heat Warning and Information System (HWIS) has never been evaluated for its processes and implementation. This paper evaluated the HWIS’s processes using a guidance report published by the World Meteorological Organization and World Health Organization. It also evaluated public health units’ implementation of the HWIS using information found on their websites. The results showed the HWIS lacks monthly threshold values, evaluation processes, and a wider action plan. In the implementation of the HWIS, public health units have failed to post on their websites all 15 heat health messages and locations and hours of local interventions. Six recommendations are made to Public Health Ontario, public health units, and Ontario Ministry of Health to improve on the processes and implementation of the HWIS. As climate change increases the frequency and intensity of heatwaves, an improved HWIS can reduce the incidence of heat-related illness and deaths in Ontario.

Deep Learning for Postprocessing Global Probabilistic Forecasts on Subseasonal Time Scales

Abstract Subseasonal weather forecasts are becoming increasingly important for a range of socioeconomic activities. However, the predictive ability of physical weather models is very limited on these time scales. We propose four postprocessing methods based on convolutional neural networks to improve subseasonal forecasts by correcting systematic errors of numerical weather prediction models. Our postprocessing models operate directly on spatial input fields and are therefore able to retain spatial relationships and to generate spatially homogeneous predictions. They produce global probabilistic tercile forecasts for biweekly aggregates of temperature and precipitation for weeks 3–4 and 5–6. In a case study based on a public forecasting challenge organized by the World Meteorological Organization, our postprocessing models outperform the bias-corrected forecasts from the European Centre for Medium-Range Weather Forecasts (ECMWF), and achieve improvements over climatological forecasts for all considered variables and lead times. We compare several model architectures and training modes and demonstrate that all approaches lead to skillful and well-calibrated probabilistic forecasts. The good calibration of the postprocessed forecasts emphasizes that our postprocessing models reliably quantify the forecast uncertainty based on deterministic input information in the form of ECMWF ensemble mean forecast fields only.

Tailored Investments Needed to Support Weather, Water, Ice, and Climate Services in the Polar Regions

Abstract The Polar Prediction Project (PPP), one of the flagship programs of the World Meteorological Organization’s (WMO) World Weather Research Programme (WWRP), has come to an end after a decade of intensive and coordinated international observing, modeling, verification, user engagement, and education activities. While PPP facilitated many advancements in modeling and forecasting, critical investment is now required to turn prediction science into salient environmental services for the polar regions. In this commentary, the members of the Societal and Economic Research and Applications task team of PPP, a group of social scientists and service delivery specialists, identify a number of insights and lessons that are critical for the implementation of the follow-up program Polar Coupled Analysis and Prediction for Services (PCAPS). We argue that in order to raise the societal value of polar environmental services, we need to better understand the diversity of highly specific user contexts; to tailor the actionability of weather, water, ice, and climate (WWIC) service development in the polar regions through inclusive transdisciplinary approaches to coproduction; to assess the societal impact of improved environmental services in the polar regions; and to invest and provide dedicated funding for involving the social sciences in research and tailoring processes across all the polar regions.

Impacts of anemometer changes, site relocations and processing methods on wind speed trends in China

Abstract. In situ surface wind observation is a critical meteorological data source for various research fields. However, data quality is affected by factors such as surface friction changes, station relocations and anemometer updates. Previous methods to address discontinuities have been insufficient, and processing methods have not always adhered to World Meteorological Organization (WMO) World Climate Programme guidelines. We analyzed data discontinuity caused by anemometer changes and station relocations in China's daily in situ near-surface (∼ 10 m) wind speed observations and the impact of the processing methods on wind speed trends. By comparing the wind speed discontinuities with the recorded location changes, we identified 90 stations that showed abnormally increasing wind speeds due to relocation. After removing those stations, we followed a standard quality control method recommended by the World Meteorological Organization to improve the data reliability and applied Thiessen polygons to calculate the area-weighted average wind speed. The result shows that China's recent reversal of wind speed was reduced by 41 % after removing the problematic stations, with an increasing trend of 0.017 m s−1 yr−1 (R2 = 0.64, P < 0.05), emphasizing the importance of robust quality control and homogenization protocols in wind trend assessments.

Analisis Emisi Karbon di Kesatuan Hidrologi Gambut Sungai Mendahara - Sungai Batanghari

Global Warming Due to Carbon Emissions is a threat to life on earth. According to the World Meteorological Organization, the earth's temperature rose by 1.06 °C to 1.26 °C above pre-industrial levels (1850–1900). According to the IPCC report (2021), the impacts of climate change will reach all regions in the world without exception. Indonesia's commitment to reduce carbon emissions by 29% with its efforts and 41% with international cooperation until 2030. Analysis of land cover uses the Unsupervised Classification, the method for calculating carbon emissions above the surface uses the IPCC method, namely the stock differential and the method for analyzing emissions of peat decomposition uses the Hooijer formula et al. (2006, 2010) with estimated water level from the TMAT BRGM data regression equation with NDWI Landsat 8 values then total carbon emissions by adding emissions from above and below the surface. Based on the results of the analysis of land cover at the research location, the area was dominated by plantations at 37.8%, while the forest area was only 7.9%. Ground carbon emissions average 0.23 Mt CO2-eq per year, below Ground carbon emissions are 9.94 Mt CO2-eq and total carbon emissions are 10.17 Mt CO2-eq with total emissions from 2013 - 2022 of 91.6 Mt CO2-eq Carbon emissions in KHG Sungai Mendahara - Batanghari graphically fluctuate, there is an increase and decrease but tends to increase until 2022 this is due to land conversion and massive land clearing in forest areas and the biggest contributor to carbon emissions from decomposition peatlands.