Downscaling regional climate model outputs for the Caribbean using a weather generator

Locally relevant scenarios of daily weather variables that represent the best knowledge of the present climate and projections of future climate change are needed by planners and managers to inform management and adaptation to climate change decisions. Information of this kind for the future is only readily available for a few developed country regions of the world. For many less-developed regions, it is often difficult to find series of observed daily weather data to assist in planning decisions. This study applies a previously developed single-site weather generator (WG) to the Caribbean, using examples from Belize in the west to Barbados in the east. The purpose of this development is to provide users in the region with generated sequences of possible future daily weather that they can use in a number of impact sectors. The WG is first calibrated for a number of sites across the region and the goodness of fit of the WG against the daily station observations assessed. Particular attention is focussed on the ability of the precipitation component of the WG to generate realistic extreme values for the calibration or control period. The WG is then modified using change factors (CFs) derived from regional climate model projections (control and future) to simulate future 30-year scenarios centred on the 2020s, 2050s and 2080s. Changes between the control period and the three futures are illustrated not just by changes in average temperatures and precipitation amounts but also by a number of well-used measures of extremes (very warm days/nights, the heaviest 5-day precipitation total in a month, counts of the number of precipitation events above specific thresholds and the number of consecutive dry days)

An ECOOP web portal for visualising and comparing distributed coastal oceanography model and in situ data

As part of a large European coastal operational oceanography project (ECOOP), we have developed a web portal for the display and comparison of model and in situ marine data. The distributed model and in situ datasets are accessed via an Open Geospatial Consortium Web Map Service (WMS) and Web Feature Service (WFS) respectively. These services were developed independently and readily integrated for the purposes of the ECOOP project, illustrating the ease of interoperability resulting from adherence to international standards. The key feature of the portal is the ability to display co-plotted timeseries of the in situ and model data and the quantification of misfits between the two. By using standards-based web technology we allow the user to quickly and easily explore over twenty model data feeds and compare these with dozens of in situ data feeds without being concerned with the low level details of differing file formats or the physical location of the data. Scientific and operational benefits to this work include model validation, quality control of observations, data assimilation and decision support in near real time. In these areas it is essential to be able to bring different data streams together from often disparate locations

Using ERA-Interim reanalysis for creating datasets of energy-relevant climate variables

The construction of a bias-adjusted dataset of climate variables at the near surface using ERA-Interim reanalysis is presented. A number of different, variable-dependent, bias-adjustment approaches have been proposed. Here we modify the parameters of different distributions (depending on the variable), adjusting ERA-Interim based on gridded station or direct station observations. The variables are air temperature, dewpoint temperature, precipitation (daily only), solar radiation, wind speed, and relative humidity. These are available on either 3 or 6 h timescales over the period 1979–2016. The resulting bias-adjusted dataset is available through the Climate Data Store (CDS) of the Copernicus Climate Change Data Store (C3S) and can be accessed at present from ftp://ecem.climate.copernicus.eu. The benefit of performing bias adjustment is demonstrated by comparinginitial and bias-adjusted ERA-Interim data against gridded observational fields

DRIHM - An Infrastructure To Advance Hydro-Meteorological Research

One of the main challenges in hydro-meteorological research (HMR) is predicting the impact of weather and climate changes on the environment, society and economy, including local severe hazards such as floods and landslides. At the heart of this challenge lies the ability to have easy access to hydro-meteorological data and models, and facilitate the collaboration across discipline boundaries. Within the DRIHM project (Distributed Research Infrastructure for Hydro-Meteorology, www.drihm.eu, EC funded FP7 project 2011-2015) we develop a prototype e-Science environment to facilitate this collaboration and provide end-to-end HMR services (models, datasets, and post-processing tools) at the European level, with the ability to expand to global scale. The objectives of DRIHM are to lead the definition of a common long-term strategy, to foster the development of new HMR models, workflows and observational archives for the study of severe hydro-meteorological events, to promote the execution and analysis of high-end simulations, and to support the dissemination of predictive models as decision analysis tools. For this we implement a service portal to construct heterogeneous simulation workflows that can include deterministic and ensemble runs on a heterogeneous infrastructure consisting of HPC, grid and Windows cloud resources. Via another FP7 project called DRIHM2US (www.drihm2us.eu) we collaborate with the NSF funded SCIHM project (www.scihm.org) to build a wider international collaborative network. This contribution will provide a sketch of the DRIHM architecture and show some use cases such as the November 2011 Genoa flooding

Perceptions and experiences of perinatal mental disorders in rural, predominantly ethnic minority communities in northern Vietnam

BACKGROUND: Preliminary research has suggested that perinatal mental disorders (PMDs), including post-partum depression, are prevalent in Vietnam. However the extent to which these disorders are recognized at the community level remains largely undocumented in the literature. PMDs have also never been investigated within Vietnam’s significant ethnic minority populations, who are known to bear a greater burden of maternal and infant health challenges than the ethnic majority. OBJECTIVE: To investigate knowledge and perceptions of PMDs and their treatments at the community level in a rural, predominantly ethnic minority region of northern Vietnam. METHODS: Qualitative semi-structured interviews were conducted on the topic of common PMDs. Participant groups were primary health workers (PHWs) working at local community health centers, and pregnant or postpartum women enrolled in a program for maternal and infant health that was not mental health related. Interviews included vignette scenarios that asked respondents to interpret cases of women experiencing PMDs, as well as open-ended questions about mental disorders and their treatments. RESULTS: Twelve PHWs and 14 perinatal women completed the study. Major themes that emerged from the interviews included (1) Family relationships impact psychological well-being, (2) Nutrition contributes to perinatal mental health, (3) Both traditional and western medicine play roles in perinatal health, (4) There was a lack of personal experience with women experiencing PMDs, (5) Descriptions of mental health symptoms focused on behaviours, and (6) Community care is the primary mental health support. CONCLUSIONS: PHWs reported having almost never treated a woman with a PMD. However, anecdotal evidence from the women interviewed suggests that there are incidents of mental disorders during the perinatal period that go largely unaddressed. Willingness to present to primary care appears to be high, and presents an opportunity to address this need by training PHWs in effective screening, treatment, and referral. Such training should account for culturally specific presentations of mental disorders as well as the importance of the patient’s social context. To the best of the author’s knowledge, this research presents the first evidence of a PMD burden within Vietnam’s ethnic minority communities

Selection and integration of earth observation-based data for an operational disease forecasting system

The current increase in the volume and quality of Earth Observation (EO) data being collected by satellites offers the potential to contribute to applications across a wide range of scientific domains. It is well established that there are correlations between characteristics that can be derived from EO satellite data, such as land surface temperature or land cover, and the incidence of some diseases. Thanks to the reliable frequent acquisition and rapid distribution of EO data it is now possible for this field to progress from using EO in retrospective analyses of historical disease case counts to using it in operational forecasting systems. However, bringing together EO-based and non-EO-based datasets, as is required for disease forecasting and many other fields, requires carefully designed data selection, formatting and integration processes. Similarly, it requires careful communication between collaborators to ensure that the priorities of that design process match the requirements of the application. Here we will present work from the D-MOSS (Dengue forecasting MOdel Satellite-based System) project. D-MOSS is a dengue fever early warning system for South and South East Asia that will allow public health authorities to identify areas at high risk of disease epidemics before an outbreak occurs in order to target resources to reduce spreading of epidemics and improve disease control. The D-MOSS system uses EO, meteorological and seasonal weather forecast data, combined with disease statistics and static layers such as land cover, as the inputs into a dengue fever model and a water availability model. Water availability directly impacts dengue epidemics due to the provision of mosquito breeding sites. The datasets are regularly updated with the latest data and run through the models to produce a new monthly forecast. For this we have designed a system to reliably feed standardised data to the models. The project has involved a close collaboration between remote sensing scientists, geospatial scientists, hydrologists and disease modelling experts. We will discuss our approach to the selection of data sources, data source quality assessment, and design of a processing and ingestion system to produce analysis-ready data for input to the disease and water availability models

Creating a proof-of-concept climate service to assess future renewable energy mixes in Europe: an overview of the C3S ECEM project

The EU Copernicus Climate Change Service (C3S) European Climatic Energy Mixes (ECEM) has produced, in close collaboration with prospective users, a proof-of-concept climate service, or Demonstrator, designed to enable the energy industry and policy makers assess how well different energy supply mixes in Europe will meet demand, over different time horizons (from seasonal to long-term decadal planning), focusing on the role climate has on the mixes. The concept of C3S ECEM, its methodology and some results are presented here. The first part focuses on the construction of reference data sets for climate variables based on the ERA-Interim reanalysis. Subsequently, energy variables were created by transforming the bias-adjusted climate variables using a combination of statistical and physically-based models. A comprehensive set of measured energy supply and demand data was also collected, in order to assess the robustness of the conversion to energy variables. Climate and energy data have been produced both for the historical period (1979–2016) and for future projections (from 1981 to 2100, to also include a past reference period, but focusing on the 30 year period 2035–2065). The skill of current seasonal forecast systems for climate and energy variables has also been assessed. The C3S ECEM project was designed to provide ample opportunities for stakeholders to convey their needs and expectations, and assist in the development of a suitable Demonstrator. This is the tool that collects the output produced by C3S ECEM and presents it in a user-friendly and interactive format, and it therefore constitutes the essence of the C3S ECEM proof-of-concept climate service