scholarly journals Evaluation of New CORDEX Simulations Using an Updated Köppen–Trewartha Climate Classification

Atmosphere ◽  
2019 ◽  
Vol 10 (11) ◽  
pp. 726 ◽  
Author(s):  
Armelle Reca Remedio ◽  
Claas Teichmann ◽  
Lars Buntemeyer ◽  
Kevin Sieck ◽  
Torsten Weber ◽  
...  
Keyword(s):  
Climate Change ◽  
Standard Deviation ◽  
Climatic Research Unit ◽  
Mean Annual Precipitation ◽  
Mean Annual Temperature ◽  
Climate Classification ◽  
Climate Services ◽  
Skill Scores ◽  
Observational Uncertainty ◽  
Core Framework

A new ensemble of climate and climate change simulations covering all major inhabited regions with a spatial resolution of about 25 km, from the WCRP CORDEX COmmon Regional Experiment (CORE) Framework, has been established in support of the growing demands for climate services. The main objective of this study is to assess the quality of the simulated climate and its fitness for climate change projections by REMO (REMO2015), a regional climate model of Climate Service Center Germany (GERICS) and one of the RCMs used in the CORDEX-CORE Framework. The CORDEX-CORE REMO2015 simulations were driven by the ECMWF ERA-Interim reanalysis and the simulations were evaluated in terms of biases and skill scores over ten CORDEX Domains against the Climatic Research Unit (CRU) TS version 4.02, from 1981 to 2010, according to the regions defined by the Köppen–Trewartha (K–T) Climate Classification types. The REMO simulations have a relatively low mean annual temperature bias (about ± 0.5 K) with low spatial standard deviation (about ± 1.5 K) in the European, African, North and Central American, and Southeast Asian domains. The relative mean annual precipitation biases of REMO are below ± 50 % in most domains; however, spatial standard deviation varies from ± 30 % to ± 200 %. The REMO results simulated most climate types relatively well with lowest biases and highest skill score found in the boreal, temperate, and subtropical regions. In dry and polar regions, the REMO results simulated a relatively high annual biases of precipitation and temperature and low skill. Biases were traced to: missing or misrepresented processes, observational uncertainty, and uncertainties due to input boundary forcing.

scholarly journals Assessment of Climate Change Effects on Water Resources in the Yellow River Basin, China

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Zhiyong Wu ◽  
Heng Xiao ◽  
Guihua Lu ◽  
Jinming Chen
Keyword(s):  
Climate Change ◽  
Water Resources ◽  
River Basin ◽  
Climate Model ◽  
Yellow River ◽  
Yellow River Basin ◽  
Mean Annual Precipitation ◽  
The Yellow River ◽  
Mean Annual Temperature ◽  
The Yellow River Basin

The water resources in the Yellow River basin (YRB) are vital to social and economic development in North and Northwest China. The basin has a marked continental monsoon climate and its water resources are especially vulnerable to climate change. Projected runoff in the basin for the period from 2001 to 2030 was simulated using the variable infiltration capacity (VIC) macroscale hydrology model. VIC was first calibrated using observations and then was driven by the precipitation and temperature projected by the RegCM3 high-resolution regional climate model under the IPCC scenario A2. Results show that, under the scenario A2, the mean annual temperature of the basin could increase by 1.6°C, while mean annual precipitation could decrease by 2.6%. There could be an 11.6% reduction in annual runoff in the basin according to the VIC projection. However, there are marked regional variations in these climate change impacts. Reductions of 13.6%, 25.7%, and 24.6% could be expected in the regions of Hekouzhen to Longmen, Longmen to Sanmenxia, and Sanmenxia to Huayuankou, respectively. Our study suggests that the condition of water resources in the YRB could become more severe in the period from 2001 to 2030 under the scenario A2.

scholarly journals 1206. Effects of Climatic Variability on Lyme Disease Outbreaks in California

2021 ◽  
Vol 8 (Supplement_1) ◽  
pp. S693-S694
Author(s):  
Raghesh Varot Kangath ◽  
Rajasree Pai Ramachandra ◽  
Buddhika Madurapperuma ◽  
Luke Scaroni
Keyword(s):  
Climate Change ◽  
Lyme Disease ◽  
Temperature Anomaly ◽  
Climatic Factors ◽  
Climatic Variables ◽  
Mean Annual Precipitation ◽  
Mean Annual Temperature ◽  
Northern Coast ◽  
Santa Cruz ◽  
Cca Ordination

Abstract Background Climate change has increased the risk of tick borne infections. The life cycle and prevalence of deer ticks are strongly influenced by temperature. Warmer temperatures associated with climate change are projected to increase the range of suitable tick habitats driving the spread of Lyme disease (LD). Short winters could also increase tick activity increasing the risk of exposure. This study examines the relationship between LD incidence and temperature-precipitation and their anomalies in CA counties. Methods Trends and relationships of Lyme Disease (LD) cases and climatic factors were analyzed among the California counties from 2000 to 2019. Lyme disease tabulate data and climatic data were obtained from Centers for Disease Control, and NOAA, and Climate Data Guide respectively. Canonical correspondence analysis (CCA) was performed using variables: (i) LD cases, (ii) precipitation & anomaly, and temperature & anomaly. The CCA ordination explained the variability between LD cases and climatic variables. Biplots were used to visualize the associations between LD cases and climatic anomalies. Results We compared the countywide LD cases in relation to climatic factors in California from 2000 to 2019. A total of 96 cases in 2000, 117 cases in 2009, and 144 cases in 2019 were reported in the 55 counties of California. Santa Clara reported the highest LD cases in 2003 (23 cases; 16%), followed by Los Angeles in 2013 (20 cases; 18%) and Santa Cruz in 2017 (19 cases; 13%). CCA ordination showed distinguishable clustering patterns between southern California counties (Santa Clara, Santa Cruz, Alameda, and San Diego) and northern coast and Klamath mountains range (Humboldt, Trinity, Shasta, and Siskiyou) regions (Fig. 1). Moderate mean annual temperature (56.5 °F - 62.5 °F) and temperature anomaly (3.8 °F - 5.5 °F) were the most important variable predictor for high LD outbreak. The CCA ordination shows the relationships between Lyme Disease and climatic variables for the 55 Counties of California. The bottom right circle represents Lyme cases positively correlated with temperature anomaly (3.8 °F - 5.5 °F) and moderate annual mean temperature (56.5 °F - 62.5 °F). The upper left circle represents Lyme cases negatively correlated with mean annual precipitation. Conclusion Moderate temperature with low moist spell anomalies in the south neighboring CA counties showed a positive influence on LD outbreak. The climatic conditions in those areas suitable for Oak trees and masting acorn resulting in the establishment of tick and host (deer) populations. We recommend robust surveillance and lab testing for patients with a history of tick bites in these regions. Disclosures All Authors: No reported disclosures

scholarly journals Patterns and controls of soil respiration and its temperature sensitivity in grassland ecosystems across China

2018 ◽  
Author(s):  
Jiguang Feng ◽  
Jingsheng Wang ◽  
Yanjun Song ◽  
Biao Zhu
Keyword(s):  
Climate Change ◽  
Soil Respiration ◽  
Soil Temperature ◽  
Spatial Variation ◽  
Temperature Sensitivity ◽  
Annual Precipitation ◽  
Mean Annual Precipitation ◽  
Mean Annual Temperature ◽  
The Mean ◽  
Grassland Types

Abstract. Soil respiration (Rs), a key process in the terrestrial carbon cycle, is very sensitive to climate change. In this study, we synthesized 54 measurements of annual Rs and 171 estimates of Q10 value (the temperature sensitivity of soil respiration) in grasslands across China. We quantitatively analyzed their spatial patterns and controlling factors in five grassland types, including temperate typical steppe, temperate meadow steppe, temperate desert steppe, alpine grassland, and warm-tropical grassland. Results showed that the mean (± SE) annual Rs was 582.0 ± 57.9 g C m−2 yr−1 across Chinese grasslands. Annual Rs significantly differed among grassland types, and positively correlated with mean annual temperature, mean annual precipitation, soil organic carbon content and aboveground biomass, but negatively correlated with latitude and soil pH (P < 0.05). Among these factors, mean annual precipitation was the primary factor controlling the spatial variation of annual Rs in Chinese grasslands. The mean contributions of growing season Rs and heterotrophic respiration to annual Rs were 78.7 % and 72.8 %, respectively. Moreover, the mean (± SE) of Q10 across Chinese grasslands was 2.60 ± 0.08, ranging from 1.03 to 8.13, and varied largely within and among grassland types, and among soil temperature measurement depths. Generally, the seasonal variation of soil respiration in Chinese grasslands cannot be well explained by soil temperature using the van't Hoff equation. Longitude and altitude were the dominant driving factors and accounted for 26.0 % of the variation in Q10 derived by soil temperature at the depth of 5 cm. Overall, our findings advance our understanding of the spatial variation and environmental control of soil respiration and Q10 across Chinese grasslands, and also improve our ability to predict soil carbon efflux under climate change on the regional scale.

scholarly journals Hydrological Modeling of Climate Change Impacts in a Tropical River Basin: A Case Study of the Cauto River, Cuba

Water ◽  
2018 ◽  
Vol 10 (9) ◽  
pp. 1135 ◽  
Author(s):  
Yalina Montecelos-Zamora ◽  
Tereza Cavazos ◽  
Thomas Kretzschmar ◽  
Enrique Vivoni ◽  
Gerald Corzo ◽  
...  
Keyword(s):  
Climate Change ◽  
River Basin ◽  
Hydrological Modeling ◽  
Climate Model ◽  
Assessment Tool ◽  
Swat Model ◽  
Boreal Summer ◽  
Mean Annual Precipitation ◽  
Mean Annual Temperature ◽  
Aquifer Recharge

The soil and water assessment tool (SWAT) model was applied for the first time in Cuba to assess the potential impacts of climate change on water availability in the Cauto River basin. The model was calibrated (and validated) for the 2001–2006 (2007–2010) period at a monthly timescale in two subbasins La Fuente and Las Coloradas, representative of middle and upper sections of the Cauto basin; the calibrated models showed good performance. The output available for the regional climate Model RegCM4.3 was used to force the calibrated SWAT models to simulate a baseline (1970–2000) period and near-future (2015–2039) hydrologic regimes under the representative concentration pathway (RCP) 8.5 emission scenario. The future projections suggest regional increases of 1.5 °C in mean annual temperature and a 38% decrease in mean annual precipitation in the subbasins. These changes translate to possible reductions in the annual streamflow of up to 61% with respect to the baseline period, whereas the aquifer recharge in the basin is expected to decrease up to 58%, with a consequent reduction of groundwater flow, especially during the boreal summer wet season. These projection scenarios should be of interest to water resources managers in tropical regions.

scholarly journals Tooth Marker of Ecological Abnormality: the Interpretation of Stress in Extinct Mega Herbivores (Proboscideans) of the Siwaliks of Pakistan

2021 ◽  
Author(s):  
Muhammad Ameen ◽  
Abdul Khan ◽  
Rana Ahmad ◽  
Muhammad Ijaz ◽  
Muhammad Imran
Keyword(s):  
Climate Change ◽  
Late Miocene ◽  
Middle Miocene ◽  
Indian Subcontinent ◽  
Climatic Conditions ◽  
C3 Plants ◽  
Mean Annual Precipitation ◽  
Mean Annual Temperature ◽  
Enamel Hypoplasia ◽  
Grassland Ecology

Climate effects habitat and define species physiology. Climatic regimes were different in past and adaptability of different species varied. Climate change causes certain stress on animal, recorded as Enamel Hypoplasia (EH). Proboscideans, the mega herbivores were extensively represented in the Siwaliks of Pakistan between Middle Miocene to Pleistocene (~15.2 – ~1.0Ma). The study is carried out on 15 species from 9 genera and 4 families using 319 teeth from 266 individual quarries. Our results revealed 20.06% (64/319) teeth infected by EH. Family Deinotheriidae faced higher stress during the terminal of middle Miocene (EH 25%). Dental structure indicate that this family preferred soft vegetation like C3 plants and failed to survive in grassland ecology at the onset of Late Miocene (~10-9 Ma). Gomphotheriids (EH 21.05%) and Stegodontids (EH 23.40%) survived through warm and dry climatic conditions of the Late Miocene, but could not survive the cool and dry climate of Plio-Pleistocene where grasslands were abundant with less browsing activity. Family Elephantidae (EH 8.75%) was successful in drier conditions, and utilized the exclusive C4 diet in open grasslands as efficient grazers, indicated by their tooth morphology. Elephantids were dominant of the proboscideans in open grassland and drier climate during Plio-Pleistocene in Indian subcontinent. We assume that change in the Siwalik climate was governed by microclimate as in the present day Siwaliks grasslands are widely distributed at low altitudes with lower mean annual precipitation and forestlands still persist in Myanmar and Nepal which receives more rainfall and have lower mean annual temperature.

scholarly journals Climate change and runoff contribution by hydrological zones of cryosphere catchment of Indus River, Pakistan

2018 ◽  
Author(s):  
Kashif Jamal ◽  
Shakil Ahmad ◽  
Xin Li ◽  
Muhammad Rizwan ◽  
Hongyi Li ◽  
...  
Keyword(s):  
Climate Change ◽  
High Altitude ◽  
High Water ◽  
Mean Annual Precipitation ◽  
Mean Annual Temperature ◽  
Indus River ◽  
Snow Cover Area ◽  
Mountainous Regions ◽  
Changing Climate ◽  
The Mean

Abstract. Climate change has significant impacts on hydrology in high altitude snow and glacier covered mountainous regions. These regions are highly sensitive to changes in climate variables, such as temperature and precipitation and producing high runoffs. Runoff produced from different altitude ranges and their sensitivity to current and changing climate is also unknown. This study was carried out in high altitude mountainous cryosphere Hunza River Catchment (HRC) which is located in Hindukush and Karakoram ranges and is the major tributary of the Indus River Basin. Snowmelt-Runoff Model (SRM) was used to analyse the current and projected hydrological regimes and the sensitivity of Snow Cover Area (SCA) at different altitude levels under current and changing climate. Under the current condition (i.e., 2001–2010 except 2006), the results showed that about half of the mean annual streamflows at the outlet of the HRC is contributed by the altitude ranges of 4500–5500 m a.s.l. Climatic projections under the RCP8.5 and RCP4.5 scenarios were used for the climate change impact assessment. Compared to the baseline climate, the mean annual temperature would increase by 0.7 (0.6), 2.4 (1.3) and 4.6 (1.9) ℃, respectively during 2030s, 2060s and 2090s; and the mean annual precipitation would increase by 63.3 (33.6) mm during 2090s under the RCP8.5 (RCP4.5) projections. Moreover, two SCA scenarios were developed, i.e., the baseline unchanged SCA and the hypothetical change in SCA scenarios. In the first SCA scenario, the results showed that additional streamflows of 43 (34), 153 (83.4) and 304 (115.7) m3 s−1 under RCP8.5 (RCP4.5) will be added into baseline annual streamflows of 269 m3 s−1 during 2030s, 2060s and 2090s, respectively. In the second scenario, we found that 10 % and 15 % decrease in SCA would result in increases (or decrease) in streamflows approximately by 18 (2) % and 42 (7) % under the RCP8.5 (RCP4.5) scenario during 2060s and 2090s, respectively. Whereas altitude range 4500–5500 m a.s.l showed increasing trend during pre-monsoon (April–June) and monsoon (July–August) season under changed SCA scenario for both RCPs scenarios. Current and near future climate pattern is favourable for Indus River regarding high water flows. However, future water flow pattern is declining because of disappearance or decrease in snow and glaciers melt area which correspondingly means that mid/downstream water allocation will be effected or reduced at some extent. Proper adaptations or managements strategies should be executed for upcoming harsh conditions.

scholarly journals Climate services for addressing climate change: Iindication of a climate livable city in China

2021 ◽  
Author(s):  
Wang Yu-Jie ◽  
Chen Yu ◽  
Chris Hewitt ◽  
Ding Wei-Hua ◽  
Song Lian-Chun ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Services

scholarly journals Biological and extrinsic correlates of extinction risk in Chinese lizards

2021 ◽  
Author(s):  
Yuxi Zhong ◽  
Chuanwu Chen ◽  
Yanping Wang
Keyword(s):  
Body Size ◽  
Extinction Risk ◽  
Species Traits ◽  
Geographic Range ◽  
Range Size ◽  
Habitat Specialization ◽  
Mean Annual Precipitation ◽  
Mean Annual Temperature ◽  
Small Range ◽  
Extrinsic Factors

Abstract China is a country with one of the most species rich reptile faunas in the world. However, nearly a quarter of Chinese lizard species assessed by the China Biodiversity Red List are threatened. Nevertheless, to date, no study has explicitly examined the pattern and processes of extinction and threat in Chinese lizards. In this study, we conducted the first comparative phylogenetic analysis of extinction risk in Chinese lizards. We addressed the following three questions: 1) What is the pattern of extinction and threat in Chinese lizards? 2) Which species traits and extrinsic factors are related to their extinction risk? 3) How can we protect Chinese lizards based on our results? We collected data on ten species traits (body size, clutch size, geographic range size, activity time, reproductive mode, habitat specialization, habitat use, leg development, maximum elevation, and elevation range) and seven extrinsic factors (mean annual precipitation, mean annual temperature, mean annual solar insolation, normalized difference vegetation index (NDVI), human footprint, human population density, and human exploitation). After phylogenetic correction, these variables were used separately and in combination to assess their associations with extinction risk. We found that Chinese lizards with small geographic range, large body size, high habitat specialization, and living in high precipitation areas were vulnerable to extinction. Conservation priority should thus be given to species with the above extinction-prone traits so as to effectively protect Chinese lizards. Preventing future habitat destruction should also be a primary focus of management efforts because species with small range size and high habitat specialization are particularly vulnerable to habitat loss.

scholarly journals Altitudinal Vascular Plant Richness and Climate Change in the Alpine Zone of the Lefka Ori, Crete

Diversity ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 22
Author(s):  
George Kazakis ◽  
Dany Ghosn ◽  
Ilektra Remoundou ◽  
Panagiotis Nyktas ◽  
Michael A. Talias ◽  
...  
Keyword(s):  
Climate Change ◽  
Species Richness ◽  
Spatial Scales ◽  
Vascular Plant ◽  
Monitoring Network ◽  
Mediterranean Area ◽  
Mean Annual Temperature ◽  
High Mountain ◽  
Species Loss ◽  
Total Species Richness

High mountain zones in the Mediterranean area are considered more vulnerable in comparison to lower altitudes zones. Lefka Ori massif, a global biodiversity hotspot on the island of Crete is part of the Global Observation Research Initiative in Alpine Environments (GLORIA) monitoring network. The paper examines species and vegetation changes with respect to climate and altitude over a seven-year period (2001–2008) at a range of spatial scales (10 m Summit Area Section-SAS, 5 m SAS, 1 m2) using the GLORIA protocol in a re-survey of four mountain summits (1664 m–2339 m). The absolute species loss between 2001–2008 was 4, among which were 2 endemics. At the scale of individual summits, the highest changes were recorded at the lower summits with absolute species loss 4 in both cases. Paired t-tests for the total species richness at 1 m2 between 2001–2008, showed no significant differences. No significant differences were found at the individual summit level neither at the 5 m SAS or the 10 m SAS. Time series analysis reveals that soil mean annual temperature is increasing at all summits. Linear regressions with the climatic variables show a positive effect on species richness at the 5 m and 10 m SAS as well as species changes at the 5 m SAS. In particular, June mean temperature has the highest predictive power for species changes at the 5 m SAS. Recorded changes in species richness point more towards fluctuations within a plant community’s normal range, although there seem to be more significant diversity changes in higher summits related to aspects. Our work provides additional evidence to assess the effects of climate change on plant diversity in Mediterranean mountains and particularly those of islands which remain understudied.

Spatial Patterns and Drivers of Soil Chemical Properties in a Typical Hickory Plantation

2021 ◽  
Author(s):  
Mengjiao Sun ◽  
Enqing Hou ◽  
Jiasen Wu ◽  
Jianqin Huang ◽  
Xingzhao Huang
Keyword(s):  
Random Forest ◽  
Soil Nutrients ◽  
Spatial Patterns ◽  
Abiotic Factors ◽  
Soil Nutrient ◽  
Parent Material ◽  
Mean Annual Precipitation ◽  
Nutrient Concentrations ◽  
Available Phosphorus ◽  
Mean Annual Temperature

Abstract Background: Soil nutrients play critical roles in regulating and improving the sustainable development of economic forests. Consequently, an elucidation of the spatial patterns and drivers of soil nutrients in these forests is fundamental to their management. For this study, we collected 314 composite soils at a 0-30 cm depth from a typical hickory plantation in Lin 'an, Zhejiang Province, China. We determined the concentrations of macronutrients (i.e., soil organic carbon, hydrolyzed nitrogen, available phosphorus, and available potassium) and micronutrients (i.e., iron, manganese, zinc, and copper.) of the soils. We employed random forest analysis to quantify the relative importance of soil-forming factors to predict the soil nutrient concentrations, which could then be extrapolated to the entire hickory region. Results: Random forest models explained 61%–88% of the variations in soil nutrient concentrations. The mean annual temperature and mean annual precipitation were the most important predictor of soil macronutrient and micronutrient concentrations. Moreover, parent material was another key predictor of soil available phosphorus and micronutrient concentrations. Mapping results demonstrated the importance of climate in controlling the spatial distribution of soil nutrient concentrations at finer scales, as well as the effect of parent material, topography, stand structure, and management measures of hickory plantations. Conclusions: Our study highlights the biotic factors, abiotic factors, and management factors control over soil macronutrient and micronutrient concentrations, which have significant implications for the sustainability of soil nutrients in forest plantations.

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