Copernicus Sectoral Information System for the Biodiversity Sector

2020 ◽  
Author(s):  
Koen De Ridder ◽  
Filip Lefebre ◽  
Eline Vanuytrecht ◽  
Julie Berckmans ◽  
Hendrik Wouters
Keyword(s):  
Climate Change ◽  
Information System ◽  
High Resolution ◽  
Global Climate ◽  
Future Climate ◽  
Use Cases ◽  
Climate Projections ◽  
Climate Data ◽  
Climate Conditions ◽  
Climate Suitability

<p>Biodiversity is increasingly under pressure from climate change, which affects the habitat suitability for species as well as the efficiency of ecosystem services. Management of these issues, for instance through ecosystem restoration or species dispersal measures, is often hindered by a lack of appropriate information about (future) climate conditions.  To address this, an operational Sectoral Information System (SIS) for the Biodiversity sector (SIS Biodiversity) is designed within the Copernicus programme Climate Change Service (C3S). This new SIS provides tailored bio-climatic indicators and applications, and delivers novel evidence regarding impacts of past, present and future climate. As such, it provides support to decision making challenges that are currently facing unmet climate data needs.<br> <br>The new climate service for SIS Biodiversity will be demonstrated, including the outline, workflow and outcomes of the use cases. The service is built upon the Copernicus Data Store platform (CDS; ), and takes into account (1) the barriers in ongoing bio-climate assessments and (2) the user requirements of diverse stakeholders (e.g. researcher institutes, local NGO’s, the International Union for Conservation of Nature and Natural Resources (IUCN),…). These have been collected during workshops and bilateral meetings in 2019. A common barrier is the lack of reliable and high-resolution information about states and dynamics of the soil, sea, ice and air for the past and the future climate. Therefore, the service provides relevant bio-climatic indicators on the basis of a wealth of available variables from the latest ERA5 reanalysis datasets and the CMIP5 global climate projections available in CDS. In order to provide information at high resolution and minimize inconsistencies between observed and modelled variables, different downscaling and bias-correction techniques are applied. A common requirement is a universal and flexible interface to the bio-climatic indicators in an easy-to-use and coherent platform that is applicable for different fauna and flora species of interest. Therefore, different applications have been developed within CDS for generating bio-climate suitability envelopes from the high-resolution indicators and to evaluate climate suitability and impacts for the species under present and future climate. Finally, the service is currently tested and refined on the basis of specific use cases. Special attention is given to their transferability to other global and topical studies, hence maximizing external user uptake throughout existing research and policy networks.</p>

scholarly journals Evaluating the Tourist Climate Comfortable Period of China in a Changing Climate

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Dan-Dan Yu ◽  
Shan Li ◽  
Zhong-Yang Guo
Keyword(s):  
Climate Change ◽  
Global Climate ◽  
Scientific Evidence ◽  
Climatic Conditions ◽  
Climate Index ◽  
Climate Indices ◽  
Climate Data ◽  
Climate Conditions ◽  
Positive Effects ◽  
Changing Climate

The evaluation of climate comfort for tourism can provide information for tourists selecting destinations and tourism operators. Understanding how climate conditions for tourism evolve is increasingly important for strategic tourism planning, particularly in rapidly developing tourism markets like China in a changing climate. Multidimensional climate indices are needed to evaluate climate for tourism, and previous studies in China have used the much criticized “climate index” with low resolution climate data. This study uses the Holiday Climate Index (HCI) and daily data from 775 weather stations to examine interregional differences in the tourist climate comfortable period (TCCP) across China and summarizes the spatiotemporal evolution of TCCP from 1981 to 2010 in a changing climate. Overall, most areas in China have an “excellent” climate for tourism, such that tourists may visit anytime with many choices available. The TCCP in most regions shows an increasing trend, and China benefits more from positive effects of climate change in climatic conditions for tourism, especially in spring and autumn. These results can provide some scientific evidence for understanding human settlement environmental constructions and further contribute in improving local or regional resilience responding to global climate change.

scholarly journals A comparison between direct and indirect frameworks to evaluate impacts of climate change on streamflows: case study of Karkheh River basin in Iran

2017 ◽  
Vol 8 (4) ◽  
pp. 652-674 ◽  
Author(s):  
Mohsen Nasseri ◽  
Banafsheh Zahraie ◽  
Leila Forouhar
Keyword(s):  
Climate Change ◽  
River Basin ◽  
Hydrological Modeling ◽  
Future Climate ◽  
Multivariate Adaptive Regression Splines ◽  
Group Method ◽  
Climate Projections ◽  
Climate Conditions ◽  
Karkheh River Basin ◽  
Impacts Of Climate Change

Abstract In this paper, two approaches to assess the impacts of climate change on streamflows have been used. In the first approach (direct), a statistical downscaling technique was utilized to predict future streamflows based on large-scale data of general circulation models (GCMs). In the second approach (indirect), GCM outputs were downscaled to produce local climate conditions which were then used as inputs to a hydrological simulation model. In this article, some data-mining methods such as model-tree, multivariate adaptive regression splines and group method of data handling were utilized for direct downscaling of streamflows. Projections of HadCM3 model for A2 and B2 SRES scenarios were also used to simulate future climate conditions. These evaluations were done over three sub-basins of Karkheh River basin in southwest Iran. To achieve a comprehensive assessment, a global uncertainty assessment method was used to evaluate the results of the models. The results indicated that despite simplifications included in the direct downscaling, this approach is accurate enough to be used for assessing climate change impacts on streamflows without computational efforts of hydrological modeling. Furthermore, comparing future climate projections, the uncertainty associated with elimination of hydrological modeling is estimated to be high.

Projecting future vegetation change for northeast China using CMIP6

2020 ◽  
Author(s):  
Wei Yuan ◽  
Shuang-ye Wu ◽  
Shugui Hou
Keyword(s):  
Climate Change ◽  
Vegetation Change ◽  
Management Strategies ◽  
Future Climate ◽  
Future Climate Change ◽  
Vegetation Changes ◽  
Emission Scenarios ◽  
Climate Data ◽  
Climate Conditions ◽  
Temperature And Precipitation

<p>This study aims to establish future vegetation changes in the east and central of northern China (ECNC), an ecologically sensitive region in the transition zonal from humid monsoonal to arid continental climate. The region has experienced significant greening in the past several decades. However, few studies exist on how vegetation will change with future climate change, and great uncertainties exist due to complex, and often spatially non-stationary, relationships between vegetation and climate. In this study, we first used historical NDVI and climate data to model this spatially variable relationship with Geographically Weighted Logit Regression. We found that temperature and precipitation could explain, on average, 43% of NDVI variance, and they could be used to model NDVI fairly well. We then establish future climate change using the output of 11 CMIP6 models for the medium (SSP245) and high (SSP585) emission scenarios for the mid-century (2041-2070) and late-century (2071-2100). The results show that for this region, both temperature and precipitation will increase under both scenarios. By late-century under SSP585, precipitation is projected to increase by 25.12% and temperature is projected to increase 5.87<sup>o</sup>C in ECNC. Finally, we used future climate conditions as input for the regression models to project future vegetation (indicated by NDVI). We found that NDVI will increase under climate change. By mid-century, the average NDVI in ECNC will increase by 0.024 and 0.021 under SSP245 and SSP585. By late-century, it will increase by 0.016 and 0.006 under SSP245 and SSP585 respectively. Although NDVI is projected to increase, the magnitude of increase is likely to diminish with higher emission scenarios, possibly due to the benefit of precipitation increase being gradually encroached by the detrimental effects of temperature increase. Moreover, despite the overall NDVI increase, the area likely to suffer vegetation degradation will also expands, particularly in the western part of ECNC. With higher emissions and later into the century, region with low NDVI is likely to shift and/or expand north-forward. Our results could provide important information on possible vegetation changes, which could help to develop effective management strategies to ensure ecological and economic sustainability in the future.</p>

scholarly journals Forecasting the impacts of chemical pollution and climate change interactions on the health of wildlife

2015 ◽  
Vol 61 (4) ◽  
pp. 669-689 ◽  
Author(s):  
Pamela D. Noyes ◽  
Sean C. Lema
Keyword(s):  
Climate Change ◽  
Environmental Changes ◽  
Global Climate ◽  
Climatic Conditions ◽  
Future Climate ◽  
Chemical Pollution ◽  
Climate Scenarios ◽  
Chemical Toxicity ◽  
Climate Conditions ◽  
Chemical Exposures

Abstract Global climate change is impacting organisms, biological communities and ecosystems around the world. While most research has focused on characterizing how the climate is changing, including modeling future climatic conditions and predicting the impacts of these conditions on biodiversity, it is also the case that climate change is altering the environmental impacts of chemical pollution. Future climate conditions are expected to influence both the worldwide distribution of chemicals and the toxicological consequences of chemical exposures to organisms. Many of the environmental changes associated with a warming global climate (e.g., increased average – and possibly extreme – temperatures; intense periods of drier and wetter conditions; reduced ocean pH; altered salinity dynamics in estuaries) have the potential to enhance organism susceptibility to chemical toxicity. Additionally, chemical exposures themselves may impair the ability of organisms to cope with the changing environmental conditions of the shifting climate. Such reciprocity in the interactions between climate change and chemicals illustrates the complexity inherent in predicting the toxicological consequences of chemical exposures under future climate scenarios. Here, we summarize what is currently known about the potential reciprocal effects of climate change and chemical toxicity on wildlife, and depict current approaches and ongoing challenges for incorporating climate effects into chemical testing and assessment. Given the rapid pace of new man-made chemistries, the development of accurate and rapid methods to evaluate multiple chemical and non-chemical stressors in an ecologically relevant context will be critical to understanding toxic and endocrine-disrupting effects of chemical pollutants under future climate scenarios.

scholarly journals Impacts of future climate change on potential yields of major crops in China

2014 ◽  
Vol 5 (1) ◽  
pp. 617-647
Author(s):  
Y. Yin ◽  
Q. Tang ◽  
X. Liu
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Models ◽  
Future Climate ◽  
Future Climate Change ◽  
Yield Reduction ◽  
Climate Data ◽  
Potential Yield ◽  
Crop Models

Abstract. Climate change may affect crop development and yield, and consequently cast a shadow of doubt over China's food self-sufficiency efforts. In this study we used the model projections of a couple of global gridded crop models (GGCMs) to assess the effects of future climate change on the potential yields of the major crops (i.e. wheat, rice, maize and soybean) over China. The GGCMs were forced with the bias-corrected climate data from 5 global climate models (GCMs) under the Representative Concentration Pathways (RCP) 8.5 which were made available by the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP). The results show that the potential yields of rice may increase over a large portion of China. Climate change may benefit food productions over the high-altitude and cold regions where are outside current main agricultural area. However, the potential yield of maize, soybean and wheat may decrease in a large portion of the current main crop planting areas such as North China Plain. Development of new agronomic management strategy may be useful for coping with climate change in the areas with high risk of yield reduction.

scholarly journals Agro-ecological suitability assessment of Chinese Medicinal Yam under future climate change

2019 ◽  
Vol 42 (3) ◽  
pp. 987-1000 ◽  
Author(s):  
Dongli Fan ◽  
Honglin Zhong ◽  
Biao Hu ◽  
Zhan Tian ◽  
Laixiang Sun ◽  
...  
Keyword(s):  
Public Health ◽  
Climate Change ◽  
Future Climate ◽  
Living Standard ◽  
Future Climate Change ◽  
Climate Projections ◽  
Significant Shift ◽  
Potential Yield ◽  
Climate Conditions ◽  
Suitability Assessment

Abstract Chinese Medicinal Yam (CMY) has been prescribed as medicinal food for thousand years in China by Traditional Chinese Medicine (TCM) practitioners. Its medical benefits include nourishing the stomach and spleen to improve digestion, replenishing lung and kidney, etc., according to the TCM literature. As living standard rises and public health awareness improves in recent years, the potential medicinal benefits of CMY have attracted increasing attention in China. It has been found that the observed climate change in last several decades, together with the change in economic structure, has driven significant shift in the pattern of the traditional CMY planting areas. To identify suitable planting area for CMY in the near future is critical for ensuring the quality and supply quantity of CMY, guiding the layout of CMY industry, and safeguarding the sustainable development of CMY resources for public health. In this study, we first collect 30-year records of CMY varieties and their corresponding phenology and agro-meteorological observations. We then consolidate these data and use them to enrich and update the eco-physiological parameters of CMY in the agro-ecological zone (AEZ) model. The updated CMY varieties and AEZ model are validated using the historical planting area and production under observed climate conditions. After the successful validation, we use the updated AEZ model to simulate the potential yield of CMY and identify the suitable planting regions under future climate projections in China. This study shows that regions with high ecological similarity to the genuine and core producing areas of CMY mainly distribute in eastern Henan, southeastern Hebei, and western Shandong. The climate suitability of these areas will be improved due to global warming in the next 50 years, and therefore, they will continue to be the most suitable CMY planting regions.

scholarly journals Predicting impacts of future climate change on the distribution of the widespread selaginellas (Selaginella ciliaris and S. plana) in Southeast Asia

2018 ◽  
Vol 19 (5) ◽  
pp. 1960-1977
Author(s):  
AHMAD DWI SETYAWAN ◽  
JATNA SUPRIATNA ◽  
NISYAWATI NISYAWATI ◽  
SUTARNO SUTARNO ◽  
ILYAS NURSAMSI
Keyword(s):  
Climate Change ◽  
Southeast Asia ◽  
Global Climate ◽  
Early Period ◽  
Climatic Conditions ◽  
Future Climate ◽  
Future Climate Change ◽  
High Plains ◽  
Suitable Habitat ◽  
Climate Conditions

Abstract. Setyawan AD, Supriatna J, Nisyawati, Sutarno, Sugiyarto, Nursamsi I. 2018. Predicting impacts of future climate change on the distribution of the widespread selaginellas (Selaginella ciliaris and S. plana) in Southeast Asia. Biodiversitas 19: 1960-1977. The current global climate is moving towards dangerous and unprecedented conditions that have been seen as a potentially devastating threat to the environment and all living things. Selaginella is a fern-allies that needs water as a medium for fertilization, hence its distribution is presumed to be affected by climate change. In Southeast Asia (SEA), there are two widely distributed selaginellas, namely Selaginella ciliaris and S. plana. S. ciliaris is a small herb (up to 4 cm), annual, abundant during the rainy season, and found in the middle-high plains, whereas S. plana is a stout large herb (up to 80 cm), perennial, and mainly found in the lowlands. The purpose of this study was to determine the potential niche distribution of S. ciliaris and S. plana under current climatic conditions, and to predict its future distribution under the impacts of climate change. We used Maxent software along with bioclimatic, edaphic, and UV radiation variables to model the potential niche distribution of those two selaginellas under current and future predictions climate conditions. We generated future predictions under four detailed bioclimatic scenarios (i.e., RCP 2.6, RCP 4.5, RCP 6.0, and RCP 8.5) over three times intervals (2030, 2050, 2080). The results showed that future climatic conditions in the SEA had been predicted to significantly disrupt the distribution of suitable habitat of S. ciliaris and S. plana, and alter their geographic distribution patterns. Although some areas were predicted to become suitable habitat in the early period of future climate change, the overall projections show adverse effects of future climate conditions on the suitable habitat distribution of S. ciliaris and S. plana, as estimated losses of suitable habitat will be higher than the gains.

scholarly journals High-Resolution Climate Projections for a Densely Populated Mediterranean Region

2020 ◽  
Vol 12 (9) ◽  
pp. 3684
Author(s):  
Mohamed Salem Nashwan ◽  
Shamsuddin Shahid ◽  
Eun-Sung Chung
Keyword(s):  
Climate Change ◽  
High Resolution ◽  
Bias Correction ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Models ◽  
Future Climate Change ◽  
Climate Projections ◽  
Near Future ◽  
Far Future

The present study projected future climate change for the densely populated Central North region of Egypt (CNE) for two representative concentration pathways (RCPs) and two futures (near future: 2020–2059, and far future: 2060–2099), estimated by a credible subset of five global climate models (GCMs). Different bias correction models have been applied to correct the bias in the five interpolated GCMs’ outputs onto a high-resolution horizontal grid. The 0.05° CNE datasets of maximum and minimum temperatures (Tmx, and Tmn, respectively) and the 0.1° African Rainfall Climatology (ARC2) datasets represented the historical climate. The evaluation of bias correction methodologies revealed the better performance of linear and variance scaling for correcting the rainfall and temperature GCMs’ outputs, respectively. They were used to transfer the correction factor to the projections. The five statistically bias-corrected climate projections presented the uncertainty range in the future change in the climate of CNE. The rainfall is expected to increase in the near future but drastically decrease in the far future. The Tmx and Tmn are projected to increase in both future periods reaching nearly a maximum of 5.50 and 8.50 °C for Tmx and Tmn, respectively. These findings highlighted the severe consequence of climate change on the socio-economic activities in the CNE aiming for better sustainable development.

scholarly journals Inter-annual variability in the tropical Atlantic from the Last Glacial Maximum into future climate projections simulated by CMIP5/PMIP3

2018 ◽  
Vol 14 (10) ◽  
pp. 1377-1390 ◽  
Author(s):  
Chris Brierley ◽  
Ilana Wainer
Keyword(s):  
Climate Change ◽  
Last Glacial Maximum ◽  
Global Climate ◽  
Glacial Maximum ◽  
Future Climate ◽  
Climate Projections ◽  
Tropical Atlantic ◽  
Last Glacial ◽  
The Last Glacial Maximum ◽  
The Last Glacial

Abstract. Tropical Atlantic variability (TAV) plays an important role in driving year-to-year changes in rainfall over Africa and South America. In this study, its response to global climate change is investigated through a series of multi-model experiments. We explore the leading modes of TAV during the historical, Last Glacial Maximum, mid-Holocene, and future simulations in the multi-model ensemble known as PMIP3/CMIP5. Despite their known sea surface temperature biases, most of the models are able to capture the tropical Atlantic's two leading modes of SST variability patterns – the Atlantic Meridional Mode (AMM) and the Atlantic zonal mode (also called the Atlantic Niño or ATL3). The ensemble suggests that AMM amplitude was less during the mid-Holocene and increased during the Last Glacial Maximum, but is equivocal about future changes. ATL3 appears stronger under both the Last Glacial Maximum and future climate changes, with no consistent message about the mid-Holocene. The patterns and the regions under the influence of the two modes alter a little under climate change in concert with changes in the mean climate state. In the future climate experiment, the equatorial mode weakens, and the whole Northern Hemisphere warms up, while the South Atlantic displays a hemisphere-wide weak oscillating pattern. For the LGM, the AMM projects onto a pattern that resembles the pan-Atlantic decadal oscillation. No robust relationships between the amplitude of the zonal and meridional temperature gradients and their respective variability was found.

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