Effects of snow ratio on annual runoff within the Budyko framework

Abstract. A warmer climate may lead to less precipitation falling as snow in cold seasons. Such a switch in the state of precipitation not only alters temporal distribution of intra-annual runoff but also tends to yield less total annual runoff. Long-term water balance for 282 catchments across China is investigated, showing that a decreasing snow ratio reduces annual runoff for a given total precipitation. Within the Budyko framework, we develop an equation to quantify the relationship between snow ratio and annual runoff from a water–energy balance viewpoint. Based on the proposed equation, attribution of runoff change during the past several decades and possible runoff change induced by projected snow ratio change using climate experiment outputs archived in the Coupled Model Intercomparison Project Phase 5 (CMIP5) are analyzed. Results indicate that annual runoff in northwestern mountainous and northern high-latitude areas are sensitive to snow ratio change. The proposed model is applicable to other catchments easily and quantitatively for analyzing the effects of possible change in snow ratio on available water resources and evaluating the vulnerability of catchments to climate change.

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Effects of snow ratio on annual runoff within Budyko framework

Hydrology and Earth System Sciences Discussions ◽

10.5194/hessd-12-939-2015 ◽

2015 ◽

Vol 12 (1) ◽

pp. 939-973 ◽

Cited By ~ 2

Author(s):

D. Zhang ◽

Z. Cong ◽

G. Ni ◽

D. Yang ◽

S. Hu

Keyword(s):

Coupled Model ◽

Temporal Distribution ◽

Winter Precipitation ◽

Annual Runoff ◽

Proposed Model ◽

Runoff Change ◽

Ratio Change ◽

Intercomparison Project ◽

The Relationship

Abstract. Warmer climate may lead to less winter precipitation falling as snow. Such a switch in the state of precipitation not only alters temporal distribution of intra-annual runoff, but tends to yield less total annual runoff. Long-term water balance for 282 catchments across China is investigated, showing that decreasing snow ratio reduces annual runoff for a given total precipitation. Within the Budyko framework, we develop an equation to quantify the relationship between snow ratio and annual runoff from a water–energy balance viewpoint. Based on the proposed equation, attribution of runoff change during past several decades and possible runoff change induced by projected snow ratio change using climate experiment outputs archived in the Coupled Model Intercomparison Project Phase 5 are analyzed. Results indicate that annual runoff in northwest mountainous and north high-latitude areas are sensitive to snow ratio change. The proposed model is applicable to other catchments easily and quantitatively for analyzing the effects of possible change in snow ratio on available water resources and evaluating the vulnerability of catchments to climate change.

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Assessing the Spatial and Spatio-Temporal Distribution of Forest Species via Bayesian Hierarchical Modeling

Forests ◽

10.3390/f9090573 ◽

2018 ◽

Vol 9 (9) ◽

pp. 573 ◽

Cited By ~ 6

Author(s):

Óscar Rodríguez de Rivera ◽

Antonio López-Quílez ◽

Marta Blangiardo

Keyword(s):

Hierarchical Modeling ◽

Temporal Distribution ◽

Short Term ◽

Distribution Models ◽

Address Climate Change ◽

Bayesian Hierarchical ◽

Temporal Models ◽

Spatio Temporal ◽

The Relationship

Climatic change is expected to affect forest development in the short term, as well as the spatial distribution of species in the long term. Species distribution models are potentially useful tools for guiding species choices in reforestation and forest management prescriptions to address climate change. The aim of this study is to build spatial and spatio-temporal models to predict the distribution of four different species present in the Spanish Forest Inventory. We have compared the different models and showed how accounting for dependencies in space and time affect the relationship between species and environmental variables.

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Innovativeness in the context of technological and market dynamism

Journal of Organizational Change Management ◽

10.1108/jocm-04-2016-0068 ◽

2017 ◽

Vol 30 (4) ◽

pp. 548-568 ◽

Cited By ~ 10

Author(s):

Job Rodrigo-Alarcón ◽

Pedro Manuel García-Villaverde ◽

Gloria Parra-Requena ◽

María José Ruiz-Ortega

Keyword(s):

Network Theory ◽

Interactive Effect ◽

Interactive Effects ◽

Network Density ◽

Critical Aspect ◽

Content Type ◽

Proposed Model ◽

The Relationship ◽

Positive Effect

Purpose Innovativeness is a critical aspect for the survival and success of the company in the long term. The purpose of this paper is to study how the density of the network in which the company is immersed influences the relationship between environment, dynamism and innovativeness. More specifically, the authors analyse whether the network density acts in a heterogeneous way, worsening or improving the effects of technological and market dynamism on innovativeness, respectively. Design/methodology/approach The empirical study was conducted on a sample of 292 companies in the agri-food industry in Spain. In order to test the proposed model, the authors used partial least squares. Findings The results show that technological dynamism has a positive effect on the generation and development of a firm’s innovativeness. However, market dynamism does not influence innovativeness. The authors also observe that the interactive effects between network density and dynamism are significant, but in a divergent way. Whereas the interactive effect between density and technological dynamism is negative, the interaction between density and market dynamism is positive. Originality/value The main contribution of the study is to show how the level of network density alters the effect of technological and market dynamism on innovativeness. The authors highlight the relevance of network theory to explain the contextual background to innovativeness. The authors also stress the importance of differentiating between the market and technological components of dynamism to further elucidate their effects.

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Anthropogenic and Natural Contributions to the Lengthening of the Summer Season in the Northern Hemisphere

Journal of Climate ◽

10.1175/jcli-d-17-0643.1 ◽

2018 ◽

Vol 31 (17) ◽

pp. 6803-6819 ◽

Cited By ~ 3

Author(s):

Bo-Joung Park ◽

Yeon-Hee Kim ◽

Seung-Ki Min ◽

Eun-Pa Lim

Keyword(s):

Northern Hemisphere ◽

Coupled Model ◽

Atlantic Multidecadal Oscillation ◽

Summer Season ◽

Season Length ◽

The Past ◽

External Forcings ◽

Regional Trends ◽

Intercomparison Project

Observed long-term variations in summer season timing and length in the Northern Hemisphere (NH) continents and their subregions were analyzed using temperature-based indices. The climatological mean showed coastal–inland contrast; summer starts and ends earlier inland than in coastal areas because of differences in heat capacity. Observations for the past 60 years (1953–2012) show lengthening of the summer season with earlier summer onset and delayed summer withdrawal across the NH. The summer onset advance contributed more to the observed increase in summer season length in many regions than the delay of summer withdrawal. To understand anthropogenic and natural contributions to the observed change, summer season trends from phase 5 of the Coupled Model Intercomparison Project (CMIP5) multimodel simulations forced with the observed external forcings [anthropogenic plus natural forcing (ALL), natural forcing only (NAT), and greenhouse gas forcing only (GHG)] were analyzed. ALL and GHG simulations were found to reproduce the overall observed global and regional lengthening trends, but NAT had negligible trends, which implies that increased greenhouse gases were the main cause of the observed changes. However, ALL runs tend to underestimate the observed trend of summer onset and overestimate that of withdrawal, the causes of which remain to be determined. Possible contributions of multidecadal variabilities, such as Pacific decadal oscillation and Atlantic multidecadal oscillation, to the observed regional trends in summer season length were also assessed. The results suggest that multidecadal variability can explain a moderate portion (about ±10%) of the observed trends in summer season length, mainly over the high latitudes.

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Long-term Surface Temperature (LoST) database as a complement for GCM preindustrial simulations

Climate of the Past ◽

10.5194/cp-15-1099-2019 ◽

2019 ◽

Vol 15 (3) ◽

pp. 1099-1111 ◽

Cited By ~ 1

Author(s):

Francisco José Cuesta-Valero ◽

Almudena García-García ◽

Hugo Beltrami ◽

Eduardo Zorita ◽

Fernando Jaume-Santero

Keyword(s):

Surface Temperature ◽

General Circulation ◽

Ground Surface ◽

Coupled Model ◽

Circulation Model ◽

Research Unit ◽

Large Spread ◽

Intercomparison Project ◽

Past Millennium

Abstract. Estimates of climate sensitivity from general circulation model (GCM) simulations still present a large spread despite the continued improvements in climate modeling since the 1970s. This variability is partially caused by the dependence of several long-term feedback mechanisms on the reference climate state. Indeed, state-of-the-art GCMs present a large spread of control climate states probably due to the lack of a suitable reference for constraining the climatology of preindustrial simulations. We assemble a new gridded database of long-term ground surface temperatures (LoST database) obtained from geothermal data over North America, and we explore its use as a potential reference for the evaluation of GCM preindustrial simulations. We compare the LoST database with observations from the Climate Research Unit (CRU) database, as well as with five past millennium transient climate simulations and five preindustrial control simulations from the third phase of the Paleoclimate Modelling Intercomparison Project (PMIP3) and the fifth phase of the Coupled Model Intercomparison Project (CMIP5). The database is consistent with meteorological observations as well as with both types of preindustrial simulations, which suggests that LoST temperatures can be employed as a reference to narrow down the spread of surface temperature climatologies on GCM preindustrial control and past millennium simulations.

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The Double-ITCZ Bias in CMIP6 Models

10.5194/egusphere-egu2020-21375 ◽

2020 ◽

Author(s):

Baijun Tian

Keyword(s):

Climate Models ◽

Global Climate ◽

Coupled Model ◽

Global Climate Models ◽

Cmip5 Models ◽

Tropical Precipitation ◽

Double Itcz ◽

Intercomparison Project ◽

Fully Coupled

<p>The double-Intertropical Convergence Zone (ITCZ) bias is one of the most outstanding problems in climate models. This study seeks to examine the double-ITCZ bias in the latest state-of-the-art fully coupled global climate models that participated in Coupled Model Intercomparison Project (CMIP) Phase 6 (CMIP6) in comparison to their previous generations (CMIP3 and CMIP5 models). To that end, we have analyzed the long-term annual mean tropical precipitation distributions and several precipitation bias indices that quantify the double-ITCZ biases in 75 climate models including 24 CMIP3 models, 25 CMIP3 models, and 26 CMIP6 models. We find that the double-ITCZ bias and its big inter-model spread persist in CMIP6 models but the double-ITCZ bias is slightly reduced from CMIP3 or CMIP5 models to CMIP6 models.</p>

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Observational and Model Estimates of Cloud Amount Feedback over the Indian and Pacific Oceans

Journal of Climate ◽

10.1175/jcli-d-13-00165.1 ◽

2014 ◽

Vol 27 (2) ◽

pp. 925-940 ◽

Cited By ~ 22

Author(s):

Katinka Bellomo ◽

Amy C. Clement ◽

Joel R. Norris ◽

Brian J. Soden

Keyword(s):

Coupled Model ◽

Cloud Amount ◽

Western Indian Ocean ◽

Model Intercomparison ◽

Central Pacific ◽

Radiative Impact ◽

Southern Central ◽

Intercomparison Project ◽

Very High

AbstractConstraining intermodel spread in cloud feedback with observations is problematic because available cloud datasets are affected by spurious behavior in long-term variability. This problem is addressed by examining cloud amount in three independent ship-based [Extended Edited Cloud Reports Archive (EECRA)] and satellite-based [International Satellite Cloud Climatology Project (ISCCP) and Advanced Very High Resolution Radiometer Pathfinder Atmosphere–Extended (PATMOS-X)] observational datasets, and models from phase 5 of the Coupled Model Intercomparison Project (CMIP5). The three observational datasets show consistent cloud variability in the overlapping years of coverage (1984–2007). The long-term cloud amount change from 1954 to 2005 in ship-based observations shares many of the same features with the multimodel mean cloud amount change of 42 CMIP5 historical simulations, although the magnitude of the multimodel mean is smaller. The radiative impact of cloud changes is estimated by computing an observationally derived estimate of cloud amount feedback. The observational estimates of cloud amount feedback are statistically significant over four regions: the northeast Pacific subtropical stratocumulus region and equatorial western Pacific, where cloud amount feedback is found to be positive, and the southern central Pacific and western Indian Ocean, where cloud amount feedback is found to be negative. Multimodel mean cloud amount feedback is consistent in sign but smaller in magnitude than in observations over these four regions because models simulate weaker cloud changes. Individual models, however, can simulate cloud amount feedback of the same magnitude if not larger than observed. Focusing on the regions where models and observations agree can lead to improved understanding of the mechanisms of cloud amount changes and associated radiative impact.

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Development Of Strategic Organizational Learning As A Competitive Advantage In The "Paladars" Of The Sector Sme’s Horeca In The Havana, Cuba

European Scientific Journal ESJ ◽

10.19044/esj.2016.v12n13p67 ◽

2016 ◽

Vol 12 (13) ◽

pp. 67

Author(s):

Héctor Nuricumbo-Castro ◽

Manuel Moguel-Liévano ◽

Manuel González-Pérez

Keyword(s):

Organizational Culture ◽

Organizational Learning ◽

Knowledge Transfer ◽

Competitive Advantage ◽

Transfer Equation ◽

Cross Sectional ◽

Institutional Knowledge ◽

Proposed Model ◽

The Relationship

The research develops a model of Strategic Organizational Learning (SOL) to acquire and build institutional knowledge as a long-term competitive advantage in family businesses known as paladars. It aims to consolidate and strengthen the SME Horeca sector in Havana, Cuba. The proposed methodology is not experimental and correlational cross-sectional. The Knowledge Transfer equation was implemented to measure the SOL based on the proposed model. Also, it was used to determine the relationship between learning and competition. The equation was validated. The results indicated that most paladars present an SOL Medium/Regular, and independence exists between competition and learning. However, there is great ignorance to foster the organizational culture in the HORECA sector. This study suggests that the arrival of US competition causes these establishments perish.

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Evaluating permafrost physics in the Coupled Model Intercomparison Project 6 (CMIP6) models and their sensitivity to climate change

The Cryosphere ◽

10.5194/tc-14-3155-2020 ◽

2020 ◽

Vol 14 (9) ◽

pp. 3155-3174 ◽

Cited By ~ 1

Author(s):

Eleanor J. Burke ◽

Yu Zhang ◽

Gerhard Krinner

Keyword(s):

Climate Change ◽

Air Temperature ◽

High Latitude ◽

Soil Profile ◽

Coupled Model ◽

The Arctic ◽

Model Intercomparison ◽

Model Ensemble ◽

Northern High Latitude ◽

Intercomparison Project

Abstract. Permafrost is a ubiquitous phenomenon in the Arctic. Its future evolution is likely to control changes in northern high-latitude hydrology and biogeochemistry. Here we evaluate the permafrost dynamics in the global models participating in the Coupled Model Intercomparison Project (present generation – CMIP6; previous generation – CMIP5) along with the sensitivity of permafrost to climate change. Whilst the northern high-latitude air temperatures are relatively well simulated by the climate models, they do introduce a bias into any subsequent model estimate of permafrost. Therefore evaluation metrics are defined in relation to the air temperature. This paper shows that the climate, snow and permafrost physics of the CMIP6 multi-model ensemble is very similar to that of the CMIP5 multi-model ensemble. The main differences are that a small number of models have demonstrably better snow insulation in CMIP6 than in CMIP5 and a small number have a deeper soil profile. These changes lead to a small overall improvement in the representation of the permafrost extent. There is little improvement in the simulation of maximum summer thaw depth between CMIP5 and CMIP6. We suggest that more models should include a better-resolved and deeper soil profile as a first step towards addressing this. We use the annual mean thawed volume of the top 2 m of the soil defined from the model soil profiles for the permafrost region to quantify changes in permafrost dynamics. The CMIP6 models project that the annual mean frozen volume in the top 2 m of the soil could decrease by 10 %–40 %∘C-1 of global mean surface air temperature increase.

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Future shift of the relative roles of precipitation and temperature in controlling annual runoff in the conterminous United States

10.5194/hess-2017-392 ◽

2017 ◽

Author(s):

Kai Duan ◽

Ge Sun ◽

Steven G. McNulty ◽

Peter V. Caldwell ◽

Erika C. Cohen ◽

...

Keyword(s):

United States ◽

Climate Models ◽

Coupled Model ◽

Annual Runoff ◽

Dominant Factor ◽

Future Climate Change ◽

Primary Control ◽

Evaporative Demand ◽

South Central ◽

Runoff Change

Abstract. This study examines the relative roles of climatic variables in altering annual runoff in the conterminous United States (CONUS) in the 21st century, using an ecohydrological model driven with historical records and future scenarios constructed from 20 Coupled Model Intercomparison Project Phase 5 (CMIP5) climate models. The results suggest that precipitation has been the primary control of runoff variation during the latest decades, but the role of temperature will outweigh that of precipitation in most regions if future climate change follows the projections of climate models instead of the historical tendencies. Besides these two key factors, increasing humidity is projected to partially offset the additional evaporative demand caused by warming and consequently enhance runoff. Overall, the projections from 20 climate models suggest a high degree of consistency on the increasing trends in temperature, precipitation, and humidity, which will be the major climatic driving factors accounting for 43 % ~ 50 %, 20 % ~ 24 %, and 16 % ~ 23 % of runoff change, respectively. Spatially, while temperature rise is recognized as the largest contributor in most of the CONUS, precipitation is expected to be the dominant factor driving runoff to increase across the Pacific Coast and the Southwest. The combined effects of increasing humidity and precipitation may also surpass the detrimental effects of warming and result in a hydrologically wetter future in the East. However, severe runoff depletion is more likely to occur in the Midwest and South-Central.

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