scholarly journals Responses of runoff to historical and future climate variability over China

2018 ◽  
Vol 22 (3) ◽  
pp. 1971-1991 ◽  
Author(s):  
Chuanhao Wu ◽  
Bill X. Hu ◽  
Guoru Huang ◽  
Peng Wang ◽  
Kai Xu
Keyword(s):  
Climate Variability ◽  
Arid Regions ◽  
Eastern China ◽  
Aridity Index ◽  
Future Climate ◽  
Western China ◽  
Climate Projections ◽  
Positive Contribution ◽  
North Eastern ◽  
The Mean

Abstract. China has suffered some of the effects of global warming, and one of the potential implications of climate warming is the alteration of the temporal–spatial patterns of water resources. Based on the long-term (1960–2008) water budget data and climate projections from 28 global climate models (GCMs) of the Coupled Model Intercomparison Project Phase 5 (CMIP5), this study investigated the responses of runoff (R) to historical and future climate variability in China at both grid and catchment scales using the Budyko-based elasticity method. Results show that there is a large spatial variation in precipitation (P) elasticity (from 1.1 to 3.2) and potential evaporation (PET) elasticity (from −2.2 to −0.1) across China. The P elasticity is larger in north-eastern and western China than in southern China, while the opposite occurs for PET elasticity. The catchment properties' elasticity of R appears to have a strong non-linear relationship with the mean annual aridity index and tends to be more significant in more arid regions. For the period 1960–2008, the climate contribution to R ranges from −2.4 to 3.6 % yr−1 across China, with the negative contribution in north-eastern China and the positive contribution in western China and some parts of the south-west. The results of climate projections indicate that although there is large uncertainty involved in the 28 GCMs, most project a consistent change in P (or PET) in China at the annual scale. For the period 2071–2100, the mean annual P is projected to increase in most parts of China, especially the western regions, while the mean annual PET is projected to increase in all of China, particularly the southern regions. Furthermore, greater increases are projected for higher emission scenarios. Overall, due to climate change, the arid regions and humid regions of China are projected to become wetter and drier in the period 2071–2100, respectively (relative to the baseline 1971–2000).

scholarly journals Responses of runoff to historical and future climate variability over China

2017 ◽  
Author(s):  
Chuanhao Wu ◽  
Bill X. Hu ◽  
Guoru Huang ◽  
Peng Wang ◽  
Kai Xu
Keyword(s):  
Climate Variability ◽  
Arid Regions ◽  
Southern China ◽  
Aridity Index ◽  
Global Climate Models ◽  
Future Climate ◽  
Western China ◽  
Climate Projections ◽  
Positive Contribution ◽  
The Mean

Abstract. China has suffered some of the effects of global warming, and one of the potential implications of climate warming is the alteration of the temporal-spatial patterns of water resources. Based on the long-term (1960–2012) water budget data and climate projections from 28 Global Climate Models (GCMs) of the Coupled Model Intercomparison Project Phase 5 (CMIP5), this study investigated the responses of runoff (R) to historical and future climate variability in China at both grid and catchment scales using the Budyko-based elasticity method. Results show that there is a large spatial variation in precipitation (P) elasticity (from 1.2 to 3.3) and potential evaporation (PET) elasticity (from −2.3 to −0.2) across China. The P elasticity is larger in northeast and western China than in southern China, while the opposite occurs for PET elasticity. The catchment properties elasticity of R appears to have a strong non-linear relationship with the mean annual aridity index and tends to be more significant in more arid regions. For the period 1960–2012, the climate contribution to R ranges from −2.4 % a−1 to 3.3 % a−1 across China, with the negative contribution in the North China plain and the positive contribution in western China and some parts of the southwest. The results of climate projections indicate that although there is large uncertainty involved in the 28 GCMs, most project a consistent change in P (or PET) in China at the annual scale. For the period 2071–2100, the mean annual P will likely increase in most parts of China, especially the western regions, while the mean annual PET will likely increase in all of China, particularly the southern regions. Furthermore, greater increases are projected for higher emission scenarios. Overall, due to climate change, the arid regions and humid regions of China will likely become wetter and drier in the period 2071–2100, respectively (relative to the baseline 1971–2000).

CHARACTERIZATION OF FUTURE CLIMATE VARIABILITY IN OROMIA SPECIAL ZONE, NORTH EASTERN ETHIOPIA

2021 ◽  
Vol 12 (09) ◽  
pp. 450-465
Author(s):  
Yimer Mohammed ◽  
Gashaw Bimrew ◽  
Lisanwork Nigatu
Keyword(s):  
Climate Variability ◽  
Software Tool ◽  
Analysis Data ◽  
Future Climate ◽  
Eastern Ethiopia ◽  
Web Based ◽  
North Eastern ◽  
Arc Gis ◽  
Special Zone

This study was undertaken in Oromia special zone of nort eastern Ethiopia to analyze future climate variability. Downscale future rainfall and temperature data from ensemble of three GCMs by RCP4.5 emission scenario using a web based software tool (Marksim GCM). Standard statistical descriptors and statistical software like Instat V3.37, MAKESENS, XLSTAT 2014 and Arc GIS 10.1 were employed for the analysis data.

scholarly journals Long-Term Climate Variability in the Mediterranean Region

Atmosphere ◽  
2020 ◽  
Vol 11 (11) ◽  
pp. 1172
Author(s):  
M. Carmen Alvarez-Castro ◽  
Pedro Ribera
Keyword(s):  
Climate Variability ◽  
Mediterranean Region ◽  
Future Climate ◽  
Climate Projections ◽  
Special Issue ◽  
Past Climate ◽  
The Past ◽  
Climate Evolution ◽  
The Mediterranean

The Mediterranean region is an area where prediction at different timescales (subseasonal to decadal or even longer) is challenging. In order to help constrain future projections, the study of past climate is crucial. By improving our knowledge about the past and current climate, our confidence in understanding the future climate will be improved. In this Special Issue, information about long-term climate variability in the Mediterranean region is assessed, including in particular historical climatology and model applications to assess past climate variability, present climate evolution, and future climate projections. The seven articles included in this Special Issue explore observations, proxies, re-analyses, and models for assessing the main characteristics, processes, and variability of the Mediterranean climate. The temporal range of these articles not only covers a wide period going from the present day to as far back as 25 centuries into the past but also covers projections of future climate over the next century.

An Analysis of Cloud-to-Ground Lightning in China during 2010–13

2015 ◽  
Vol 30 (6) ◽  
pp. 1537-1550 ◽  
Author(s):  
Xinlin Yang ◽  
Jianhua Sun ◽  
Wanli Li
Keyword(s):  
Southern China ◽  
Eastern China ◽  
Warm Season ◽  
Temporal Distribution ◽  
Cold Season ◽  
Western China ◽  
Southeastern China ◽  
The Mean ◽  
High Elevations ◽  
Cg Lightning

Abstract The cloud-to-ground (CG) lightning data being detected by the China Lightning Detection Network between 2010 and 2013 are employed to gain insight into the spatial and temporal distribution of CG lightning in China. There are clear interannual and seasonal variations of CG lightning activity. The mean total CG and positive CG (PCG) flashes in 2010–13 are approximately 6.44 million and 0.42 million, respectively, and the mean percentage of PCG (PPCG) is 6.6%. CG and PCG flashes predominately occur during summer, with August being the peak month for CG and June for PCG. PPCG in the cold season is considerably greater than in the warm season; its maximum of 56.2% is in January and the minimum value of 4.0% is found in August. The centers of maximum mean annual CG density are scattered throughout southern China, the Sichuan basin, and the south of Jiangsu Province. The CG density in the high elevations and arid regions of western China is less than that in the low elevations and coastal regions of southeastern China. In addition, daily CG density and CG lightning days in southeastern China are greater than in northwestern China, but PPCG in western China is apparently greater than that in eastern China. Areas experiencing more than 30 CG lightning days per year are primarily south of 30°N, with 10–30 lightning days per year in northern and northeastern China, and approximately 10–20 lightning days per year over the central Tibetan Plateau.

scholarly journals Factors affecting health care users’ first contact with primary health care facilities in north eastern China, 2008–2018

2021 ◽  
Vol 6 (2) ◽  
pp. e003907
Author(s):  
Ran Liao ◽  
Yaqian Liu ◽  
Shunzhuang Peng ◽  
Xing Lin Feng
Keyword(s):  
Health Care ◽  
Primary Health Care ◽  
Eastern China ◽  
Medical System ◽  
Health Care Facilities ◽  
Factors Affecting ◽  
Primary Health ◽  
North Eastern ◽  
First Contact ◽  
Hierarchical Medical System

BackgroundChina set out the vision to establishing a hierarchical medical system, with primary health care (PHC) facilities serving health care users’ first contact. Common ailments were listed, supported by a series of auxiliary policy measures. We aim to assess whether these policies were effective to prompt users’ preference to PHCs within these contexts.MethodsUsing data from three waves of National Health Service Survey, we examined trends in care users’ first contact with PHC facilities in Jilin, a north eastern province, during 2008–2018. We analysed trends and factors affecting care users’ choices, stratified by type of diseases and urban–rural settings.ResultsFrom 38 823 respondents, the survey identified 3302 health care users who sought outpatient care. 54.92% and 82.49% with diseases recommended to PHC, in urban and rural Jilin, respectively, contacted PHC facilities first. While 33.51% and 61.19% with diseases not recommended to PHC did so. Care users’ first contact with PHC facilities followed an inverse U shape during 2008–2018. Such trends were more profound among care users with hypertension and/or diabetes. Neither social health insurance coverage nor contracting with family doctors was associated with care users’ first contacts. Only 1.25% care users had referral experiences. Low perceived quality was the main barrier to choose PHC facilities.ConclusionHealth care users sought PHC in a chaotic manner in Jilin. None of the recent efforts seemed effective in prompting their preference to PHC facilities. Without levering quality of PHC, an effective hierarchical medical system could be hardly forged in China.

scholarly journals Clinical profiles of diabetic foot ulcer patients undergoing major limb amputation at a tertiary care center in North-eastern Tanzania

BMC Surgery ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Ahmed Shabhay ◽  
Pius Horumpende ◽  
Zarina Shabhay ◽  
Andrew Mganga ◽  
Jeff Van Baal ◽  
...  
Keyword(s):  
Blood Glucose ◽  
Diabetic Foot ◽  
Care Center ◽  
Tertiary Care ◽  
Limb Amputation ◽  
Foot Ulcers ◽  
Diabetic Foot Ulcers ◽  
Random Blood Glucose ◽  
North Eastern ◽  
The Mean

Abstract Background Diabetic foot ulcers complications are the major cause of non-traumatic major limb amputation. We aimed at assessing the clinical profiles of diabetic foot ulcer patients undergoing major limb amputation in the Surgical Department at Kilimanjaro Christian Medical Centre (KCMC), a tertiary care hospital in North-eastern Tanzania. Methods A cross—sectional hospital-based study was conducted from September 2018 through March 2019. Demographic data were obtained from structured questionnaires. Diabetic foot ulcers were graded according to the Meggitt-Wagner classification system. Hemoglobin and random blood glucose levels data were retrieved from patients’ files. Results A total of 60 patients were recruited in the study. More than half (31/60; 51.67%) were amputated. Thirty-five (58.33%) were males. Fifty-nine (98.33%) had type II diabetes. Nearly two-thirds (34/60; 56.67%) had duration of diabetes for more than 5 years. The mean age was 60.06 ± 11.33 years (range 30–87). The mean haemoglobin level was 10.20 ± 2.73 g/dl and 9.84 ± 2.69 g/dl among amputees. Nearly two thirds (42/60; 70.00%) had a haemoglobin level below 12 g/dl, with more than a half (23/42; 54.76%) undergoing major limb amputation. Two thirds (23/31; 74.19%) of all patients who underwent major limb amputation had mean hemoglobin level below 12 g/dl. The mean Random Blood Glucose (MRBG) was 13.18 ± 6.17 mmol/L and 14.16 ± 6.10 mmol/L for amputees. Almost two thirds of the study population i.e., 42/60(70.00%) had poor glycemic control with random blood glucose level above 10.0 mmol/L. More than half 23/42 (54.76%) of the patients with poor glycemic control underwent some form of major limb amputation; which is nearly two thirds (23/31; 74.19%) of the total amputees. Twenty-eight (46.67%) had Meggitt-Wagner classification grade 3, of which nearly two thirds (17:60.71%) underwent major limb amputation. Conclusion In this study, the cohort of patients suffering from diabetic foot ulcers treated in a tertiary care center in north-eastern Tanzania, the likelihood of amputation significantly correlated with the initial grade of the Meggit-Wagner ulcer classification. High blood glucose levels and anaemia seem to be also important risk factors but correlation did not reveal statistical significance.

scholarly journals Sensitivity of projected climate impacts to climate model weighting: multi-sector analysis in eastern Africa

2021 ◽  
Vol 164 (3-4) ◽  
Author(s):  
Seshagiri Rao Kolusu ◽  
Christian Siderius ◽  
Martin C. Todd ◽  
Ajay Bhave ◽  
Declan Conway ◽  
...  
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Investment Decisions ◽  
Climate Impacts ◽  
Future Climate ◽  
Eastern Africa ◽  
Climate Projections ◽  
Systematic Effect ◽  
Risk Profiles ◽  
Model Weighting

AbstractUncertainty in long-term projections of future climate can be substantial and presents a major challenge to climate change adaptation planning. This is especially so for projections of future precipitation in most tropical regions, at the spatial scale of many adaptation decisions in water-related sectors. Attempts have been made to constrain the uncertainty in climate projections, based on the recognised premise that not all of the climate models openly available perform equally well. However, there is no agreed ‘good practice’ on how to weight climate models. Nor is it clear to what extent model weighting can constrain uncertainty in decision-relevant climate quantities. We address this challenge, for climate projection information relevant to ‘high stakes’ investment decisions across the ‘water-energy-food’ sectors, using two case-study river basins in Tanzania and Malawi. We compare future climate risk profiles of simple decision-relevant indicators for water-related sectors, derived using hydrological and water resources models, which are driven by an ensemble of future climate model projections. In generating these ensembles, we implement a range of climate model weighting approaches, based on context-relevant climate model performance metrics and assessment. Our case-specific results show the various model weighting approaches have limited systematic effect on the spread of risk profiles. Sensitivity to climate model weighting is lower than overall uncertainty and is considerably less than the uncertainty resulting from bias correction methodologies. However, some of the more subtle effects on sectoral risk profiles from the more ‘aggressive’ model weighting approaches could be important to investment decisions depending on the decision context. For application, model weighting is justified in principle, but a credible approach should be very carefully designed and rooted in robust understanding of relevant physical processes to formulate appropriate metrics.

Sign in / Sign up

Export Citation Format

Share Document