Predicting growth of plantation conifers in the Adirondack Mountains in response to climate change

1995 ◽  
Vol 25 (1) ◽  
pp. 48-56 ◽  
Author(s):  
Yude Pan ◽  
Dudley J. Raynal
Keyword(s):  
Climate Change ◽  
Tree Growth ◽  
Climate Models ◽  
Growth Models ◽  
Future Climate Change ◽  
Adirondack Mountains ◽  
Growth Responses ◽  
Conifer Species ◽  
Climatic Effects ◽  
Extrinsic Factors

Three conifer species grown in plantations in the southeastern Adirondack Mountains of New York were chosen to model tree growth. Annual growth of trees was decomposed into several components that reflect various intrinsic or extrinsic factors. Growth signals indicative of climatic effects were used to construct growth-climate models using both multivariate regression analysis and Kalman filter methods. Two growth models were used to simulate tree growth response to future climate change projected by GCMs. The consistent results of both models indicate that different conifer species have individualistic growth responses to future climatic change. The response behaviors of trees are affected greatly by local stand conditions and species tolerance to drought.

scholarly journals Predicted Future Benefits for an Endemic Rodent in the Irano-Turanian Region

Climate ◽  
2021 ◽  
Vol 9 (1) ◽  
pp. 16
Author(s):  
Suzanna Meeussen ◽  
Anouschka Hof
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Species Distribution Modelling ◽  
Geographic Range ◽  
Future Climate ◽  
Future Climate Change ◽  
Distribution Ranges ◽  
Bioclimatic Variables ◽  
Suitable Area ◽  
The Impact

Climate change is expected to have an impact on the geographical distribution ranges of species. Endemic species and those with a restricted geographic range may be especially vulnerable. The Persian jird (Meriones persicus) is an endemic rodent inhabiting the mountainous areas of the Irano-Turanian region, where future desertification may form a threat to the species. In this study, the species distribution modelling algorithm MaxEnt was used to assess the impact of future climate change on the geographic distribution range of the Persian jird. Predictions were made under two Representative Concentration Pathways and five different climate models for the years 2050 and 2070. It was found that both bioclimatic variables and land use variables were important in determining potential suitability of the region for the species to occur. In most cases, the future predictions showed an expansion of the geographic range of the Persian jird which indicates that the species is not under immediate threat. There are however uncertainties with regards to its current range. Predictions may therefore be an over or underestimation of the total suitable area. Further research is thus needed to confirm the current geographic range of the Persian jird to be able to improve assessments of the impact of future climate change.

Assess 21st century Flash Drought in the United States using high resolution regional climate models

2021 ◽  
Author(s):  
Brandi Gamelin ◽  
Jiali Wang ◽  
V. Rao Kotamarthi
Keyword(s):  
Climate Change ◽  
United States ◽  
Soil Moisture ◽  
Climate Models ◽  
Wrf Model ◽  
The United States ◽  
Future Climate Change ◽  
Climate Change Scenarios ◽  
Regional Variability ◽  
Groundwater Levels

<p>Flash droughts are the rapid intensification of drought conditions generally associated with increased temperatures and decreased precipitation on short time scales.  Consequently, flash droughts are responsible for reduced soil moisture which contributes to diminished agricultural yields and lower groundwater levels. Drought management, especially flash drought in the United States is vital to address the human and economic impact of crop loss, diminished water resources and increased wildfire risk. In previous research, climate change scenarios show increased growing season (i.e. frost-free days) and drying in soil moisture over most of the United States by 2100. Understanding projected flash drought is important to assess regional variability, frequency and intensity of flash droughts under future climate change scenarios. Data for this work was produced with the Weather Research and Forecasting (WRF) model. Initial and boundary conditions for the model were supplied by CCSM4, GFDL-ESM2G, and HadGEM2-ES and based on the 8.5 Representative Concentration Pathway (RCP8.5). The WRF model was downscaled to a 12 km spatial resolution for three climate time frames: 1995-2004 (Historical), 2045-2054 (Mid), and 2085-2094 (Late).  A key characteristic of flash drought is the rapid onset and intensification of dry conditions. For this, we identify onset with vapor pressure deficit during each time frame. Known flash drought cases during the Historical run are identified and compared to flash droughts in the Mid and Late 21<sup>st</sup> century.</p>

scholarly journals An Assessment of Recent and Future Temperature Change over the Sichuan Basin, China, Using CMIP5 Climate Models

2017 ◽  
Vol 30 (17) ◽  
pp. 6701-6722 ◽  
Author(s):  
Daniel Bannister ◽  
Michael Herzog ◽  
Hans-F. Graf ◽  
J. Scott Hosking ◽  
C. Alan Short
Keyword(s):  
Climate Change ◽  
Sichuan Basin ◽  
Climate Models ◽  
Distribution Functions ◽  
Future Climate ◽  
First Century ◽  
Future Climate Change ◽  
Change Scenario ◽  
The Sichuan Basin ◽  
Twenty First Century

The Sichuan basin is one of the most densely populated regions of China, making the area particularly vulnerable to the adverse impacts associated with future climate change. As such, climate models are important for understanding regional and local impacts of climate change and variability, like heat stress and drought. In this study, climate models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) are validated over the Sichuan basin by evaluating how well each model can capture the phase, amplitude, and variability of the regionally observed mean, maximum, and minimum temperature between 1979 and 2005. The results reveal that the majority of the models do not capture the basic spatial pattern and observed means, trends, and probability distribution functions. In particular, mean and minimum temperatures are underestimated, especially during the winter, resulting in biases exceeding −3°C. Models that reasonably represent the complex basin topography are found to generally have lower biases overall. The five most skillful climate models with respect to the regional climate of the Sichuan basin are selected to explore twenty-first-century temperature projections for the region. Under the CMIP5 high-emission future climate change scenario, representative concentration pathway 8.5 (RCP8.5), the temperatures are projected to increase by approximately 4°C (with an average warming rate of +0.72°C decade−1), with the greatest warming located over the central plains of the Sichuan basin, by 2100. Moreover, the frequency of extreme months (where mean temperature exceeds 28°C) is shown to increase in the twenty-first century at a faster rate compared to the twentieth century.

scholarly journals Projecting malaria hazard from climate change in eastern Africa using large ensembles to estimate uncertainty

2016 ◽  
Vol 11 (1s) ◽  
Author(s):  
Joseph Leedale ◽  
Adrian M. Tompkins ◽  
Cyril Caminade ◽  
Anne E. Jones ◽  
Grigory Nikulin ◽  
...  
Keyword(s):  
Climate Change ◽  
Malaria Transmission ◽  
Climate Models ◽  
Climate Model ◽  
Eastern Africa ◽  
Future Climate Change ◽  
Climate Projections ◽  
Model Ensemble ◽  
East African Community ◽  
Recent Climate

The effect of climate change on the spatiotemporal dynamics of malaria transmission is studied using an unprecedented ensemble of climate projections, employing three diverse bias correction and downscaling techniques, in order to partially account for uncertainty in climate- driven malaria projections. These large climate ensembles drive two dynamical and spatially explicit epidemiological malaria models to provide future hazard projections for the focus region of eastern Africa. While the two malaria models produce very distinct transmission patterns for the recent climate, their response to future climate change is similar in terms of sign and spatial distribution, with malaria transmission moving to higher altitudes in the East African Community (EAC) region, while transmission reduces in lowland, marginal transmission zones such as South Sudan. The climate model ensemble generally projects warmer and wetter conditions over EAC. The simulated malaria response appears to be driven by temperature rather than precipitation effects. This reduces the uncertainty due to the climate models, as precipitation trends in tropical regions are very diverse, projecting both drier and wetter conditions with the current state-of-the-art climate model ensemble. The magnitude of the projected changes differed considerably between the two dynamical malaria models, with one much more sensitive to climate change, highlighting that uncertainty in the malaria projections is also associated with the disease modelling approach.

scholarly journals Robust increase of Indian monsoon rainfall and its variability under future warming in CMIP-6 models

2020 ◽  
Author(s):  
Anja Katzenberger ◽  
Jacob Schewe ◽  
Julia Pongratz ◽  
Anders Levermann
Keyword(s):  
Climate Change ◽  
Global Warming ◽  
Climate Models ◽  
Monsoon Rainfall ◽  
Global Climate ◽  
Coupled Model ◽  
Global Climate Models ◽  
Future Climate Change ◽  
Global Mean Temperature ◽  
Almost All

Abstract. The Indian summer monsoon is an integral part of the global climate system. As its seasonal rainfall plays a crucial role in India's agriculture and shapes many other aspects of life, it affects the livelihood of a fifth of the world's population. It is therefore highly relevant to assess its change under potential future climate change. Global climate models within the Coupled Model Intercomparison Project Phase 5 (CMIP-5) indicated a consistent increase in monsoon rainfall and its variability under global warming. Since the range of the results of CMIP-5 was still large and the confidence in the models was limited due to partly poor representation of observed rainfall, the updates within the latest generation of climate models in CMIP-6 are of interest. Here, we analyse 32 models of the latest CMIP-6 exercise with regard to their annual mean monsoon rainfall and its variability. All of these models show a substantial increase in June-to-September (JJAS) mean rainfall under unabated climate change (SSP5-8.5) and most do also for the other three Shared Socioeconomic Pathways analyzed (SSP1-2.6, SSP2-4.5, SSP3-7.0). Moreover, the simulation ensemble indicates a linear dependence of rainfall on global mean temperature with high agreement between the models and independent of the SSP; the multi-model mean for JJAS projects an increase of 0.33 mm/day and 5.3 % per degree of global warming. This is significantly higher than in the CMIP-5 projections. Most models project that the increase will contribute to the precipitation especially in the Himalaya region and to the northeast of the Bay of Bengal, as well as the west coast of India. Interannual variability is found to be increasing in the higher-warming scenarios by almost all models. The CMIP-6 simulations largely confirm the findings from CMIP-5 models, but show an increased robustness across models with reduced uncertainties and updated magnitudes towards a stronger increase in monsoon rainfall.

scholarly journals Reduced global warming from CMIP6 projections when weighting models by performance and independence

2020 ◽  
Vol 11 (4) ◽  
pp. 995-1012
Author(s):  
Lukas Brunner ◽  
Angeline G. Pendergrass ◽  
Flavio Lehner ◽  
Anna L. Merrifield ◽  
Ruth Lorenz ◽  
...  
Keyword(s):  
Climate Change ◽  
Retrospective Analysis ◽  
Climate Models ◽  
Cmip5 Models ◽  
Future Climate Change ◽  
Historical Period ◽  
Climate Change Scenarios ◽  
Uncertainty Range ◽  
Future Warming ◽  
The Mean

Abstract. The sixth Coupled Model Intercomparison Project (CMIP6) constitutes the latest update on expected future climate change based on a new generation of climate models. To extract reliable estimates of future warming and related uncertainties from these models, the spread in their projections is often translated into probabilistic estimates such as the mean and likely range. Here, we use a model weighting approach, which accounts for the models' historical performance based on several diagnostics as well as model interdependence within the CMIP6 ensemble, to calculate constrained distributions of global mean temperature change. We investigate the skill of our approach in a perfect model test, where we use previous-generation CMIP5 models as pseudo-observations in the historical period. The performance of the distribution weighted in the abovementioned manner with respect to matching the pseudo-observations in the future is then evaluated, and we find a mean increase in skill of about 17 % compared with the unweighted distribution. In addition, we show that our independence metric correctly clusters models known to be similar based on a CMIP6 “family tree”, which enables the application of a weighting based on the degree of inter-model dependence. We then apply the weighting approach, based on two observational estimates (the fifth generation of the European Centre for Medium-Range Weather Forecasts Retrospective Analysis – ERA5, and the Modern-Era Retrospective analysis for Research and Applications, version 2 – MERRA-2), to constrain CMIP6 projections under weak (SSP1-2.6) and strong (SSP5-8.5) climate change scenarios (SSP refers to the Shared Socioeconomic Pathways). Our results show a reduction in the projected mean warming for both scenarios because some CMIP6 models with high future warming receive systematically lower performance weights. The mean of end-of-century warming (2081–2100 relative to 1995–2014) for SSP5-8.5 with weighting is 3.7 ∘C, compared with 4.1 ∘C without weighting; the likely (66%) uncertainty range is 3.1 to 4.6 ∘C, which equates to a 13 % decrease in spread. For SSP1-2.6, the weighted end-of-century warming is 1 ∘C (0.7 to 1.4 ∘C), which results in a reduction of −0.1 ∘C in the mean and −24 % in the likely range compared with the unweighted case.

scholarly journals Past temperature reconstructions from deep ice cores: relevance for future climate change

2006 ◽  
Vol 2 (2) ◽  
pp. 145-165 ◽  
Author(s):  
V. Masson-Delmotte ◽  
G. Dreyfus ◽  
P. Braconnot ◽  
S. Johnsen ◽  
J. Jouzel ◽  
...  
Keyword(s):  
Climate Change ◽  
Temperature Change ◽  
Climate Models ◽  
Ice Core ◽  
Ice Cores ◽  
Future Climate ◽  
Future Climate Change ◽  
Interglacial Period ◽  
Temperature Reconstructions

Abstract. Ice cores provide unique archives of past climate and environmental changes based only on physical processes. Quantitative temperature reconstructions are essential for the comparison between ice core records and climate models. We give an overview of the methods that have been developed to reconstruct past local temperatures from deep ice cores and highlight several points that are relevant for future climate change. We first analyse the long term fluctuations of temperature as depicted in the long Antarctic record from EPICA Dome C. The long term imprint of obliquity changes in the EPICA Dome C record is highlighted and compared to simulations conducted with the ECBILT-CLIO intermediate complexity climate model. We discuss the comparison between the current interglacial period and the long interglacial corresponding to marine isotopic stage 11, ~400 kyr BP. Previous studies had focused on the role of precession and the thresholds required to induce glacial inceptions. We suggest that, due to the low eccentricity configuration of MIS 11 and the Holocene, the effect of precession on the incoming solar radiation is damped and that changes in obliquity must be taken into account. The EPICA Dome C alignment of terminations I and VI published in 2004 corresponds to a phasing of the obliquity signals. A conjunction of low obliquity and minimum northern hemisphere summer insolation is not found in the next tens of thousand years, supporting the idea of an unusually long interglacial ahead. As a second point relevant for future climate change, we discuss the magnitude and rate of change of past temperatures reconstructed from Greenland (NorthGRIP) and Antarctic (Dome C) ice cores. Past episodes of temperatures above the present-day values by up to 5°C are recorded at both locations during the penultimate interglacial period. The rate of polar warming simulated by coupled climate models forced by a CO2 increase of 1% per year is compared to ice-core-based temperature reconstructions. In Antarctica, the CO2-induced warming lies clearly beyond the natural rhythm of temperature fluctuations. In Greenland, the CO2-induced warming is as fast or faster than the most rapid temperature shifts of the last ice age. The magnitude of polar temperature change in response to a quadrupling of atmospheric CO2 is comparable to the magnitude of the polar temperature change from the Last Glacial Maximum to present-day. When forced by prescribed changes in ice sheet reconstructions and CO2 changes, climate models systematically underestimate the glacial-interglacial polar temperature change.

scholarly journals Atmospheric Dynamics Feedback: Concept, Simulations, and Climate Implications

2018 ◽  
Vol 31 (8) ◽  
pp. 3249-3264 ◽  
Author(s):  
Michael P. Byrne ◽  
Tapio Schneider
Keyword(s):  
Climate Change ◽  
Atmospheric Circulation ◽  
Radiative Forcing ◽  
Large Scale ◽  
Climate Models ◽  
Atmospheric Dynamics ◽  
Future Climate Change ◽  
Coupled Models ◽  
Near Surface ◽  
Circulation Changes

AbstractThe regional climate response to radiative forcing is largely controlled by changes in the atmospheric circulation. It has been suggested that global climate sensitivity also depends on the circulation response, an effect called the “atmospheric dynamics feedback.” Using a technique to isolate the influence of changes in atmospheric circulation on top-of-the-atmosphere radiation, the authors calculate the atmospheric dynamics feedback in coupled climate models. Large-scale circulation changes contribute substantially to all-sky and cloud feedbacks in the tropics but are relatively less important at higher latitudes. Globally averaged, the atmospheric dynamics feedback is positive and amplifies the near-surface temperature response to climate change by an average of 8% in simulations with coupled models. A constraint related to the atmospheric mass budget results in the dynamics feedback being small on large scales relative to feedbacks associated with thermodynamic processes. Idealized-forcing simulations suggest that circulation changes at high latitudes are potentially more effective at influencing global temperature than circulation changes at low latitudes, and the implications for past and future climate change are discussed.

scholarly journals Are Commonly Measured Functional Traits Involved in Tropical Tree Responses to Climate?

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Fabien Wagner ◽  
Vivien Rossi ◽  
Christopher Baraloto ◽  
Damien Bonal ◽  
Clément Stahl ◽  
...  
Keyword(s):  
Functional Traits ◽  
Tree Growth ◽  
Water Availability ◽  
Growth Response ◽  
Climate Models ◽  
Growth Strategy ◽  
Limiting Factor ◽  
Maximum Height ◽  
Growth Strategies ◽  
Growth Responses

Climate models predict significant rainfall reduction in Amazonia, reducing water availability for trees. We present how functional traits modulate the tree growth response to climate. We used data from 3 years of bimestrial growth measurements for 204 trees of 53 species in the forest of Paracou, French Guiana. We integrated climate variables from an eddy covariance tower and functional trait values describing life history, leaf, and stem economics. Our results indicated that the measured functional traits are to some extent linked to the response of trees to climate but they are poor predictors of the tree climate-induced growth variation. Tree growth was affected by water availability for most of the species with different species growth strategies in drought conditions. These strategies were linked to some functional traits, especially maximum height and wood density. These results suggest that (i) trees seem adapted to the dry season at Paracou but they show different growth responses to drought, (ii) drought response is linked to growth strategy and is partly explained by functional traits, and (iii) the limited part of the variation of tree growth explained by functional traits may be a strong limiting factor for the prediction of tree growth response to climate.

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