scholarly journals Quality Assurance Framework Development Based on Six New ECV Data Products to Enhance User Confidence for Climate Applications

2018 ◽  
Vol 10 (8) ◽  
pp. 1254 ◽  
Author(s):  
Joanne Nightingale ◽  
Klaas Boersma ◽  
Jan-Peter Muller ◽  
Steven Compernolle ◽  
Jean-Christopher Lambert ◽  
...  
Keyword(s):  
Climate Change ◽  
Quality Assurance ◽  
Climate Model ◽  
Earth Observation ◽  
Evidence Based ◽  
Climate Data ◽  
Area Index ◽  
Data Products ◽  
Reference Measurements ◽  
Framework Development

Data from Earth observation (EO) satellites are increasingly used to monitor the environment, understand variability and change, inform evaluations of climate model forecasts, and manage natural resources. Policymakers are progressively relying on the information derived from these datasets to make decisions on mitigating and adapting to climate change. These decisions should be evidence based, which requires confidence in derived products, as well as the reference measurements used to calibrate, validate, or inform product development. In support of the European Union’s Earth Observation Programmes Copernicus Climate Change Service (C3S), the Quality Assurance for Essential Climate Variables (QA4ECV) project fulfilled a gap in the delivery of climate quality satellite-derived datasets, by prototyping a generic system for the implementation and evaluation of quality assurance (QA) measures for satellite-derived ECV climate data record products. The project demonstrated the QA system on six new long-term, climate quality ECV data records for surface albedo, leaf area index (LAI), fraction of absorbed photosynthetically active radiation (FAPAR), nitrogen dioxide (NO2), formaldehyde (HCHO), and carbon monoxide (CO). The provision of standardised QA information provides data users with evidence-based confidence in the products and enables judgement on the fitness-for-purpose of various ECV data products and their specific applications.

scholarly journals Quality Assurance Framework Development Based on Six New ECV Data Products to Enhance User Confidence for Climate Applications

2018 ◽  
Author(s):  
Joanne Nightingale ◽  
Folkert Boersma ◽  
Jan-Peter Muller ◽  
Steven Compernolle ◽  
Jean-Christopher Lambert ◽  
...  
Keyword(s):  
Climate Change ◽  
Quality Assurance ◽  
Climate Model ◽  
Earth Observation ◽  
Evidence Based ◽  
The European Union ◽  
Climate Data ◽  
Area Index ◽  
Data Products ◽  
Reference Measurements

Data from Earth Observation (EO) satellites are increasingly used to monitor the environment, understand variability and change, inform evaluations of climate model forecasts and manage natural resources. Policy makers are progressively relying on the information derived from these datasets to make decisions on mitigating and adapting to climate change. These decisions should be evidence based, which requires confidence in derived products as well as the reference measurements used to calibrate, validate or inform product development. In support of the European Union’s Earth Observation Programmes Copernicus Climate Change Service, the Quality Assurance for Essential Climate Variables (QA4ECV) project fulfilled a gap in the delivery of climate quality satellite derived datasets by prototyping a robust, generic system for the implementation and evaluation of Quality Assurance (QA) measures for satellite-derived ECV climate data record products. The project demonstrated the QA system on six new long-term, climate quality ECV data records for surface Albedo, Leaf Area Index, FAPAR, NO2, HCHO and CO. Provision of standardized QA information provides data users with evidence-based confidence in the products and enables judgement on the fitness-for-purpose of various ECV data products their specific applications.

scholarly journals Ten Priority Science Gaps in Assessing Climate Data Record Quality

2019 ◽  
Vol 11 (8) ◽  
pp. 986 ◽  
Author(s):  
Joanne Nightingale ◽  
Jonathan P.D. Mittaz ◽  
Sarah Douglas ◽  
Dick Dee ◽  
James Ryder ◽  
...  
Keyword(s):  
Climate Change ◽  
Quality Assurance ◽  
Data Sets ◽  
Climate Data ◽  
Science Knowledge ◽  
Knowledge Gaps ◽  
Quality Aspects ◽  
Data Products ◽  
In Situ Observations

Decision makers need accessible robust evidence to introduce new policies to mitigate and adapt to climate change. There is an increasing amount of environmental information available to policy makers concerning observations and trends relating to the climate. However, this data is hosted across a multitude of websites often with inconsistent metadata and sparse information relating to the quality, accuracy and validity of the data. Subsequently, the task of comparing datasets to decide which is the most appropriate for a certain purpose is very complex and often infeasible. In support of the European Union’s Copernicus Climate Change Service (C3S) mission to provide authoritative information about the past, present and future climate in Europe and the rest of the world, each dataset to be provided through this service must undergo an evaluation of its climate relevance and scientific quality to help with data comparisons. This paper presents the framework for Evaluation and Quality Control (EQC) of climate data products derived from satellite and in situ observations to be catalogued within the C3S Climate Data Store (CDS). The EQC framework will be implemented by C3S as part of their operational quality assurance programme. It builds on past and present international investment in Quality Assurance for Earth Observation initiatives, extensive user requirements gathering exercises, as well as a broad evaluation of over 250 data products and a more in-depth evaluation of a selection of 24 individual data products derived from satellite and in situ observations across the land, ocean and atmosphere Essential Climate Variable (ECV) domains. A prototype Content Management System (CMS) to facilitate the process of collating, evaluating and presenting the quality aspects and status of each data product to data users is also described. The development of the EQC framework has highlighted cross-domain as well as ECV specific science knowledge gaps in relation to addressing the quality of climate data sets derived from satellite and in situ observations. We discuss 10 common priority science knowledge gaps that will require further research investment to ensure all quality aspects of climate data sets can be ascertained and provide users with the range of information necessary to confidently select relevant products for their specific application.

Future humidity extremes in an urban-rural context - using regional climate model projections down to convection permitting scales for Berlin

2021 ◽  
Author(s):  
Gaby S. Langendijk ◽  
Diana Rechid ◽  
Daniela Jacob
Keyword(s):  
Climate Change ◽  
Urban Areas ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Climate Change Impacts ◽  
Regional Climate Models ◽  
Climate Projections ◽  
Climate Data ◽  
Urban Rural

<p>Urban areas are prone to climate change impacts. A transition towards sustainable and climate-resilient urban areas is relying heavily on useful, evidence-based climate information on urban scales. However, current climate data and information produced by urban or climate models are either not scale compliant for cities, or do not cover essential parameters and/or urban-rural interactions under climate change conditions. Furthermore, although e.g. the urban heat island may be better understood, other phenomena, such as moisture change, are little researched. Our research shows the potential of regional climate models, within the EURO-CORDEX framework, to provide climate projections and information on urban scales for 11km and 3km grid size. The city of Berlin is taken as a case-study. The results on the 11km spatial scale show that the regional climate models simulate a distinct difference between Berlin and its surroundings for temperature and humidity related variables. There is an increase in urban dry island conditions in Berlin towards the end of the 21st century. To gain a more detailed understanding of climate change impacts, extreme weather conditions were investigated under a 2°C global warming and further downscaled to the 3km scale. This enables the exploration of differences of the meteorological processes between the 11km and 3km scales, and the implications for urban areas and its surroundings. The overall study shows the potential of regional climate models to provide climate change information on urban scales.</p>

scholarly journals Projected Changes of Precipitation IDF Curves for Short Duration under Climate Change in Central Vietnam

Hydrology ◽  
2018 ◽  
Vol 5 (3) ◽  
pp. 33 ◽  
Author(s):  
Nguyen Tien Thanh ◽  
Luca Dutto Aldo Remo
Keyword(s):  
Climate Change ◽  
Climate Model ◽  
Southern Oscillation ◽  
Regional Climate ◽  
Extreme Weather Events ◽  
Climate Data ◽  
Rcp Scenarios ◽  
Central Vietnam ◽  
Idf Curves ◽  
Projected Changes

In future years, extreme weather events are expected to frequently increase due to climate change, especially in the combination of climate change and events of El Niño–Southern Oscillation. This pays special attention to the construction of intensity–duration–frequency (IDF) curves at a tempo-spatial scale of sub-daily and sub-grid under a context of climate change. The reason for this is that IDF curves represent essential means to study effects on the performance of drainage systems, damps, dikes and reservoirs. Therefore, the objective of this study is to present an approach to construct future IDF curves with high temporo-spatial resolutions under climate change in central Vietnam, using the case of VuGia-ThuBon. The climate data of historical and future from a regional climate model RegCM4 forced by three global models MPI-ESM-MR, IPSL-CM5A-LR and ICHEC-EC-EARTH are used to re-grid the resolution of 10 km × 10 km grid spacing from 25 km × 25 km on the base of bilinear interpolation. A bias correction method is then applied to the finest resolution of a hydrostatic climate model for an ensemble of simulations. Furthermore, the IDF curves for short durations of precipitation are constructed for the historical climate and future climates under two representative concentration pathway (RCP) scenarios, RCP4.5 and RCP8.5, based on terms of correlation factors. The major findings show that the projected precipitation changes are expected to significantly increase by about 10 to 30% under the scenarios of RCP4.5 and RCP8.5. The projected changes of a maximum of 1-, 2-, and 3-days precipitation are expected to increase by about 30–300 mm/day. More importantly, for all return periods (i.e., 10, 20, 50, 100, and 200 years), IDF curves completely constructed for short durations of precipitation at sub-daily show an increase in intensities for the RCP4.5 and RCP8.5 scenarios.

scholarly journals Climate Change Impacts on the Future of Forests in Great Britain

2021 ◽  
Vol 9 ◽  
Author(s):  
Jianjun Yu ◽  
Pam Berry ◽  
Benoit P. Guillod ◽  
Thomas Hickler
Keyword(s):  
Climate Change ◽  
Great Britain ◽  
Tree Species ◽  
Net Primary Productivity ◽  
Climate Model ◽  
Climate Change Impacts ◽  
Physiological Effects ◽  
Area Index ◽  
Projected Change ◽  
The Mean

Forests provide important ecosystem services but are being affected by climate change, not only changes in temperature and precipitation but potentially also directly through the plant-physiological effects of increases in atmospheric CO2. We applied a tree-species-based dynamic model (LPJ-GUESS) at a high 5-km spatial resolution to project climate and CO2 impacts on tree species and thus forests in Great Britain. Climatic inputs consisted of a novel large climate scenario ensemble derived from a regional climate model (RCM) under an RCP 8.5 emission scenario. The climate change impacts were assessed using leaf area index (LAI) and net primary productivity (NPP) for the 2030s and the 2080s compared to baseline (1975–2004). The potential CO2 effects, which are highly uncertain, were examined using a constant CO2 level scenario for comparison. Also, a climate vulnerability index was developed to assess the potential drought impact on modeled tree species. In spite of substantial future reductions in rainfall, the mean projected LAI and NPP generally showed an increase over Britain, with a larger increment in Scotland, northwest England, and west Wales. The CO2 increase led to higher projected LAI and NPP, especially in northern Britain, but with little effect on overall geographical patterns. However, without accounting for plant-physiological effects of elevated CO2, NPP in Southern and Central Britain and easternmost parts of Wales showed a decrease relative to 2011, implying less ecosystem service provisioning, e.g., in terms of timber yields and carbon storage. The projected change of LAI and NPP varied from 5 to 100% of the mean change, due to the uncertainty arising from natural weather-induced variability, with Southeast England being most sensitive to this. It was also the most susceptible to climate change and drought, with reduced suitability for broad-leaved trees such as beech, small-leaved lime, and hornbeam. These could lead to important changes in woodland composition across Great Britain.

scholarly journals Assessment of Impacts of Climate Change and Adaptation Measures for Maize Production in East Sikkim, India

2016 ◽  
Vol 9 (1) ◽  
pp. 15-27
Author(s):  
Proloy Deb ◽  
S. Babel
Keyword(s):  
Climate Change ◽  
Climate Model ◽  
Global Climate Model ◽  
Maize Yield ◽  
Future Climate ◽  
Yield Response ◽  
Climate Data ◽  
North East ◽  
The Impact ◽  
Impacts Of Climate Change

An investigation was carried out to assess the impacts of climate change on rainfed maize yield using a yield response to water stress model (AquaCrop) and to identify suitable adaptation options to minimize the negative impacts on maize yield in East Sikkim, North East India. Crop management and yield data was collected from the field experimental plots for calibration and validation of the model for the study area. The future climate data was developed for two IPCC emission scenarios A2 and B2 based on the global climate model HadCM3 with downscaling of climate to finer spatial resolution using the statistical downscaling model, SDSM. The impact study revealed that there is an expected reduction in maize yield of 12.8, 28.3 and 33.9% for the A2 scenario and 7.5, 19.9 and 29.9% for the B2 scenario during 2012-40, 2041-70 and 2071-99 respectively compared to the average yield simulated during the period of 1961-1990 with observed climate data. The maize yield of same variety under future climate can be maintained or improved from current level by changing planting dates, providing supplement irrigation and managing optimum nutrient.Journal of Hydrology and Meteorology, Vol. 9(1) 2015, p.15-27

scholarly journals Climate Data to Undertake Hygrothermal and Whole Building Simulations Under Projected Climate Change Influences for 11 Canadian Cities

Data ◽  
2019 ◽  
Vol 4 (2) ◽  
pp. 72 ◽  
Author(s):  
Abhishek Gaur ◽  
Michael Lacasse ◽  
Marianne Armstrong
Keyword(s):  
Climate Change ◽  
Snow Cover ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Internal Variability ◽  
Climatic Conditions ◽  
Climate Data ◽  
Wide Range ◽  
The Future

Buildings and homes in Canada will be exposed to unprecedented climatic conditions in the future as a consequence of global climate change. To improve the climate resiliency of existing and new buildings, it is important to evaluate their performance over current and projected future climates. Hygrothermal and whole building simulation models, which are important tools for assessing performance, require continuous climate records at high temporal frequencies of a wide range of climate variables for input into the kinds of models that relate to solar radiation, cloud-cover, wind, humidity, rainfall, temperature, and snow-cover. In this study, climate data that can be used to assess the performance of building envelopes under current and projected future climates, concurrent with 2 °C and 3.5 °C increases in global temperatures, are generated for 11 major Canadian cities. The datasets capture the internal variability of the climate as they are comprised of 15 realizations of the future climate generated by dynamically downscaling future projections from the CanESM2 global climate model and thereafter bias-corrected with reference to observations. An assessment of the bias-corrected projections suggests, as a consequence of global warming, future increases in the temperatures and precipitation, and decreases in the snow-cover and wind-speed for all cities.

Climate Change Explorer: Extracting localized data for developing Climate Services

2021 ◽  
Author(s):  
Christine Nam ◽  
Bente Tiedje ◽  
Susanne Pfeifer ◽  
Diana Rechid ◽  
Daniel Eggert
Keyword(s):  
Climate Change ◽  
Regional Climate Model ◽  
Climate Model ◽  
Regional Climate ◽  
Heavy Precipitation ◽  
Climate Projections ◽  
Climate Data ◽  
Climate Services ◽  
Mitigation And Adaptation ◽  
Data Formats

<p>Everyone, politicians, public administrations, business owners, and citizens want to know how climate changes will affect them locally. Having such knowledge offers everyone the opportunity to make informed choices and take action towards mitigation and adaptation.</p><p> </p><p>In order to develop locally relevant climate service products and climate advisory services, as we do at GERICS, we must extract localized climate change information from Regional Climate Model ensemble simulations.</p><p> </p><p>Common challenges associated with developing such services include the transformation of petabytes of data from physical quantities such as precipitation, temperature, or wind, into user-applicable quantities such as return periods of heavy precipitation, e.g. for legislative or construction design frequency. Other challenges include the technical and physical barriers in the use and interpretation of climate data, due to large data volume, unfamiliar software and data formats, or limited technical infrastructure. The interpretation of climate data also requires scientific background knowledge, which limit or influence the interpretation of results.</p><p> </p><p>These barriers hinder the efficient and effective transformation of big data into user relevant information in a timely and reliable manner. To enable our society to adapt and become more resilient to climate change, we must overcome these barriers. In the Helmholtz funded Digital Earth project we are tackling these challenges by developing a Climate Change Workflow.</p><p> </p><p>In the scope of this Workflow, the user can <span>easily define a region of interest and extract </span><span>the</span><span> relevant </span><span>climate data </span><span>from the simulations available </span><span>at</span><span> the Earth System Grid Federation (ESGF). Following which, </span><span>a general overview of the projected changes, in precipitation </span><span>for example, for multiple climate projections is presented</span><span>. It conveys the bandwidth, </span><span>i.e. </span><span>the minimum/maximum range by an ensemble of regional climate model projections. </span><span>We implemented the sketched workflow in a web-based tool called </span><span>The Climate Change Explorer. </span><span>It</span> addresses barriers associated with extracting locally relevant climate data from petabytes of data, in unfamilar data formats, and deals with interpolation issues, using a more intuitive and user-friendly web interface.</p><p> </p><p>Ultimately, the Climate Change Explorer provides concise information on the magnitude of projected climate change and the range of these changes for individually defined regions, such as found in GERICS ‘Climate Fact Sheets’. This tool has the capacity to also improve other workflows of climate services, allowing them to dedicate more time in deriving user relevant climate indicies; enabling politicians, public administrations, and businesses to take action.</p>

Building synergies in regional climate services for Southeast Asia: The ASEAN Regional Climate Data, Analysis and Projections (ARCDAP) workshop series.

2020 ◽  
Author(s):  
Gerald Lim ◽  
Aurel Moise ◽  
Raizan Rahmat ◽  
Bertrand Timbal
Keyword(s):  
Climate Change ◽  
Data Analysis ◽  
Southeast Asia ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Regional Climate ◽  
Early Warning Systems ◽  
Climate Data ◽  
Climate Services

<p>Southeast Asia (SEA) is a rapidly developing and densely populated region that is home to over 600 million people. This, together with the region’s high sensitivity, exposure and low adaptive capacities, makes it particularly vulnerable to climate change and extremes such as floods, droughts and tropical cyclones. While the last decade saw some countries in SEA develop their own climate change projections, studies were largely uncoordinated and most countries still lack the capability to independently produce robust future climate information. Following a proposal from the World Meteorological Organisation (WMO) Regional Association (RA) V working group on climate services, the ASEAN Regional Climate Data, Analysis and Projections (ARCDAP) workshop series was conceived in 2017 to bridge these gaps in regional synergies. The ARCDAP series has been organised annually since 2018 by the ASEAN Specialised Meteorological Centre (hosted by Meteorological Service Singapore) with support from WMO through the Canada-funded Climate Risk and Early Warning Systems (Canada-CREWS) initiative.</p><p>This presentation will cover the activities and outcomes from the first two workshops, as well as the third which will be held in February 2020. The ARCDAP series has so far brought together representatives from ASEAN National Meteorological and Hydrological Services (NMHSs), climate scientists and end-users from policy-making and a variety of vulnerability and impact assessment (VIA) sectors, to discuss and identify best practices regarding the delivery of climate change information, data usage and management, advancing the science etc. Notable outputs include two comprehensive workshop reports and a significant regional contribution to the HadEX3 global land in-situ-based dataset of temperature and precipitation extremes, motivated by work done with the ClimPACT2 software.</p><p>The upcoming third workshop will endeavour to encourage the uptake of the latest ensemble of climate simulations from the Coupled Model Intercomparison Project (CMIP6) using CMIP-endorsed tools such as ESMValTool. This will address the need for ASEAN climate change practitioners to upgrade their knowledge of the latest global climate model database. It is anticipated that with continued support from WMO, the series will continue with the Fourth workshop targeting the assessment of downscaling experiments in 2021.</p>

GBOV (Ground-Based Observation for Validation): A Copernicus service for validation of Land Products

2020 ◽  
Author(s):  
Gabriele Bai ◽  
Christophe Lerebourg ◽  
Marco Clerici ◽  
Nadine Gobron ◽  
Jan-Peter Muller ◽  
...  
Keyword(s):  
Land Surface ◽  
Data Access ◽  
Earth Observation ◽  
Free Access ◽  
In Situ Observation ◽  
Area Index ◽  
First Case ◽  
New Instrumentation ◽  
Reference Measurements

<p>Copernicus is a European Union Earth Observation program, dedicated to monitor our planet and its environment, giving free access to remote sensing data and derived Earth Observation products. For proper use in environmental monitoring and scientific applications, it is fundamental to guarantee high quality and consistency of these satellite derived products. One of the possibilities to ensure product quality is to perform quantitative comparisons of satellite derived products with the corresponding in situ observation. Two options can then be considered for ground data sources: through intensive field campaigns or making use of permanent ground stations deployed and maintained on the long term. In the first case, a large variety of variable can be assessed, but logistical challenges and financial resources limit in time and space the products validation. More over meteorological constrains often limit the number of data that can actually be used for Earth Observation products. The second option is from far the most cost effective although it is not yet possible to cover all ground variables with permanent field deployment.</p><p>To achieve these objectives of systematic and long-term data validation, the <strong>Ground-Based Observations for Validation</strong> (GBOV) service has been implemented, facilitating the use of observations from operational ground-based monitoring networks and their comparison to EO products. The service is guaranteed through 3 different components:</p><ul><li>Collection of multi-year ground-based observations (<strong>Reference Measurements</strong> - RMs) of high relevance for the understanding of land surface processes from more than 50 existing sites. These RMs are then upscaled to generate <strong>Land Products</strong> (LPs), in order to validate the Copernicus products. In particular, the LPs distributed through the GBOV portal are: Top of Canopy Reflectance (ToC-R), surface albedo, Leaf Area Index (LAI), Fraction of Absorbed Photosynthetically Available Radiation (FAPAR), Fraction of Covered ground (FCover), Surface Soil Moisture (SSM) and Land Surface Temperature (LST).</li> <li>Upgrade of existing sites with new instrumentation or establishing entirely new monitoring sites to close thematic or geographical gaps. In 2019 new instrumentation has been installed in three different sites: Hainich (Germany), Valencia (Spain) and Tumbarumba (Australia). Litchfield (Australia), Dahra (Senegal) and Skukuza (South Africa) will be equipped with new instrumentation in the course of 2020.</li> <li>Implementation and maintenance of a database for the distribution of the Reference Measurements and the corresponding Land Products, available through the website https://land.copernicus.eu/global/gbov. GBOV data access is completely free, after registration and acceptation of the terms of use and the data policy.</li> </ul>

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