scholarly journals Ancient Ocean Floor Seashells Improve Model of Past Glaciers

Eos ◽  
2016 ◽  
Author(s):  
Emily Underwood
Keyword(s):  
Climate Change ◽  
Ice Sheets ◽  
Future Climate ◽  
Ocean Floor ◽  
Future Climate Change ◽  
The Past ◽  
Improve Model ◽  
Accurate Reconstruction

More accurate reconstruction of ice sheets over the past 150,000 years could help scientists predict future climate change.

Past and future climate change: response by mixed deciduous–coniferous forest ecosystems in northern Michigan

1992 ◽  
Vol 22 (11) ◽  
pp. 1727-1738 ◽  
Author(s):  
Allen M. Solomon ◽  
Patrick J. Bartlein
Keyword(s):  
Climate Change ◽  
Vegetation Dynamics ◽  
Climate Model ◽  
Coniferous Forest ◽  
Mixed Forest ◽  
Future Climate ◽  
Forest Composition ◽  
Future Climate Change ◽  
The Past ◽  
Gap Models

During the 21st century, global climate change is expected to become a significant force redefining global biospheric boundaries and vegetation dynamics. In the northern hardwood–boreal forest transition forests, it should, at the least, control reproductive success and failure among unmanaged mixed forest stands. One means by which to predict future responses by the mixed forests is to examine the way in which they have responded to climate changes in the past. We used proxy climate data derived from Holocene (past 10 000 years) pollen records in the western Upper Peninsula of Michigan to drive forest gap models, in an effort to define regional prehistoric vegetation dynamics on differing soils. The gap models mimic forest reproduction and growth as a successional process and, hence, are appropriate for defining long-term tree and stand dynamics. The modeled period included a mid-postglacial period that was warmer than today's climate. Model failures, made apparent from the exercise, were corrected and the simulations were repeated until the model behaved credibly. Then, the same gap model was used to simulate potential future vegetation dynamics, driven by projections of a future climate that was controlled by greenhouse gases. This provided us with the same "measure" of vegetation in the past, present, and future, generating a continuously comparable record of change and stability in forest composition and density. The resulting projections of vegetation response to climate change appear to be affected more by the rate than by the magnitude of climate change.

Climate Change in Eastern Africa

2021 ◽  
Author(s):  
Rob Marchant
Keyword(s):  
Climate Change ◽  
Climate Variability ◽  
East Africa ◽  
Future Climate ◽  
Eastern Africa ◽  
Future Climate Change ◽  
Human Populations ◽  
The Past ◽  
Tropical Conditions ◽  
Convergence Zones

The climatology of East Africa results from the complex interaction between major global convergence zones with more localized regional feedbacks to the climate system; these in turn are moderated by a diverse land surface characterized by coastal to land transitions, high mountains, and large lakes. The main climatic character of East Africa, and how this varies across the region, takes the form of seasonal variations in rainfall that can fall as one, two, or three rainy seasons, the times and duration of which will be determined by the interplay between major convergence zones with more localized regional feedbacks. One of the key characteristics of East Africa are climatic variations with altitude as climates change along an altitudinal gradient that can extend from hot, dry, “tropical” conditions to cool, wet, temperate conditions and on the highest mountains “polar” climates with permanent ice caps. With this complex and variable climate landscape of the present, as scientists move through time to explore past climatic variability, it is apparent there have been a series of relatively rapid and high-magnitude environmental shifts throughout East Africa, particularly characterized by changing hydrological budgets. How climate change has impacted on ecosystems, and how those ecosystems have responded and interacted with human populations, can be unearthed by drawing on evidence from the sedimentary and archaeological record of the past six thousand years. As East African economies, and the livelihoods of millions of people in the region, have been clearly heavily affected by climate variability in the past, so it is expected that future climate variability will impact on ecosystem functioning and the preparedness of communities for future climate change.

scholarly journals Warm climates of the past—a lesson for the future?

2013 ◽  
Vol 371 (2001) ◽  
pp. 20130146 ◽  
Author(s):  
D. J. Lunt ◽  
H. Elderfield ◽  
R. Pancost ◽  
A. Ridgwell ◽  
G. L. Foster ◽  
...  
Keyword(s):  
Climate Change ◽  
Numerical Models ◽  
Future Climate ◽  
Future Climate Change ◽  
Climate Data ◽  
Comprehensive Overview ◽  
Past Climate ◽  
The Past ◽  
The Future ◽  
Warm Climates

This Discussion Meeting Issue of the Philosophical Transactions A had its genesis in a Discussion Meeting of the Royal Society which took place on 10–11 October 2011. The Discussion Meeting, entitled ‘Warm climates of the past: a lesson for the future?’, brought together 16 eminent international speakers from the field of palaeoclimate, and was attended by over 280 scientists and members of the public. Many of the speakers have contributed to the papers compiled in this Discussion Meeting Issue. The papers summarize the talks at the meeting, and present further or related work. This Discussion Meeting Issue asks to what extent information gleaned from the study of past climates can aid our understanding of future climate change. Climate change is currently an issue at the forefront of environmental science, and also has important sociological and political implications. Most future predictions are carried out by complex numerical models; however, these models cannot be rigorously tested for scenarios outside of the modern, without making use of past climate data. Furthermore, past climate data can inform our understanding of how the Earth system operates, and can provide important contextual information related to environmental change. All past time periods can be useful in this context; here, we focus on past climates that were warmer than the modern climate, as these are likely to be the most similar to the future. This introductory paper is not meant as a comprehensive overview of all work in this field. Instead, it gives an introduction to the important issues therein, using the papers in this Discussion Meeting Issue, and other works from all the Discussion Meeting speakers, as exemplars of the various ways in which past climates can inform projections of future climate. Furthermore, we present new work that uses a palaeo constraint to quantitatively inform projections of future equilibrium ice sheet change.

scholarly journals Determining the response of African biota to climate change: using the past to model the future

2013 ◽  
Vol 368 (1625) ◽  
pp. 20120491 ◽  
Author(s):  
K. J. Willis ◽  
K. D. Bennett ◽  
S. L. Burrough ◽  
M. Macias-Fauria ◽  
C. Tovar
Keyword(s):  
Climate Change ◽  
Regional Scale ◽  
Future Climate ◽  
Future Climate Change ◽  
Tropical Africa ◽  
The Past ◽  
Community Turnover ◽  
Climate Change Information ◽  
Vegetation Models ◽  
Huge Variation

Prediction of biotic responses to future climate change in tropical Africa tends to be based on two modelling approaches: bioclimatic species envelope models and dynamic vegetation models. Another complementary but underused approach is to examine biotic responses to similar climatic changes in the past as evidenced in fossil and historical records. This paper reviews these records and highlights the information that they provide in terms of understanding the local- and regional-scale responses of African vegetation to future climate change. A key point that emerges is that a move to warmer and wetter conditions in the past resulted in a large increase in biomass and a range distribution of woody plants up to 400–500 km north of its present location, the so-called greening of the Sahara. By contrast, a transition to warmer and drier conditions resulted in a reduction in woody vegetation in many regions and an increase in grass/savanna-dominated landscapes. The rapid rate of climate warming coming into the current interglacial resulted in a dramatic increase in community turnover, but there is little evidence for widespread extinctions. However, huge variation in biotic response in both space and time is apparent with, in some cases, totally different responses to the same climatic driver. This highlights the importance of local features such as soils, topography and also internal biotic factors in determining responses and resilience of the African biota to climate change, information that is difficult to obtain from modelling but is abundant in palaeoecological records.

scholarly journals Better calibration of cloud parameterizations and subgrid effects increases the fidelity of E3SM Atmosphere Model version 1

2021 ◽  
Author(s):  
Po-Lun Ma ◽  
Bryce E. Harrop ◽  
Vincent E. Larson ◽  
Richard Neale ◽  
Andrew Gettelman ◽  
...  
Keyword(s):  
Climate Change ◽  
Surface Temperature ◽  
Cloud Microphysics ◽  
Future Climate ◽  
Future Climate Change ◽  
Physical Mechanisms ◽  
The Past ◽  
Model Version ◽  
Atmosphere Model ◽  
Global Mean

Abstract. Realistic simulation of the Earth’s mean state climate remains a major challenge and yet it is crucial for predicting the climate system in transition. Deficiencies in models’ process representations, propagation of errors from one process to another, and associated compensating errors can often confound the interpretation and improvement of model simulations. These errors and biases can also lead to unrealistic climate projections as well as incorrect attribution of the physical mechanisms governing the past and future climate change. Here we show that a significantly improved global atmospheric simulation can be achieved by focusing on the realism of process assumptions in cloud calibration and subgrid effects using the Energy Exascale Earth System Model (E3SM) Atmosphere Model version 1 (EAMv1). The calibration of clouds and subgrid effects informed by our understanding of physical mechanisms leads to significant improvements in clouds and precipitation climatology, reducing common and longstanding biases across cloud regimes in the model. The improved cloud fidelity in turn reduces biases in other aspects of the system. Furthermore, even though the recalibration does not change the global mean aerosol and total anthropogenic effective radiative forcings (ERFs), the sensitivity of clouds, precipitation, and surface temperature to aerosol perturbations is significantly reduced. This suggests that it is possible to achieve improvements to the historical evolution of surface temperature over EAMv1 and that precise knowledge of global mean ERFs is not enough to constrain historical or future climate change. Cloud feedbacks are also significantly reduced in the recalibrated model, suggesting that there would be a lower climate sensitivity when running as part of the fully coupled E3SM. This study also compares results from incremental changes to cloud microphysics, turbulent mixing, deep convection, and subgrid effects to understand how assumptions in the representation of these processes affect different aspects of the simulated atmosphere as well as its response to forcings. We conclude that the spectral composition and geographical distribution of the ERFs and cloud feedback as well as the fidelity of the simulated base climate state are important for constraining the climate in the past and future.

scholarly journals Will climate change affect sugar beet establishment of the 21st century? Insights from a simulation study using a crop emergence model

2019 ◽  
Author(s):  
Jay Ram Lamichhane ◽  
Julie Constantin ◽  
Jean-Noël Aubertot ◽  
Carolyne Dürr
Keyword(s):  
Climate Change ◽  
Sugar Beet ◽  
Sowing Date ◽  
Crop Model ◽  
Future Climate ◽  
Future Climate Change ◽  
Crop Establishment ◽  
The Past ◽  
Cumulative Rainfall ◽  
Sowing Dates

AbstractOngoing climate change has been reported to have far-reaching impact on crop development and yield in many regions of the globe including Europe. However, little is known about the potential impact of climate change on specific stages of the crop cycle including crop establishment, although it is a crucial stage of the annual crop cycles. For the first time, we performed a simulation study to pinpoint how sugar beet sowing conditions of the next eight decades will be altered under future climate change and if these variations will affect sowing dates, germination and emergence as well as bolting rates of this crop. We chose Northern France as an important study site, representative of sugar beet growing basin in Northern Europe. Sugar beet emergence simulations were performed for a period between 2020 and 2100, taking into account five sowing dates (mid-February, 1st March, mid-March, 1st April and mid-April). Soil water contents and temperatures in the 0-10 cm soil horizon were first simulated with the STICS soil-crop model using the most pessimistic IPCC scenario (RCP 8.5) to feed the SIMPLE crop emergence model. We also evaluated the probability of field access for the earlier sowings, based on the amount of cumulated rainfall during February and March. When analyzed by sowing date and for successive 20-year period from 2020 to 2100, there was a significant increase in seedbed temperatures by 2°C after 2060 while no change in cumulative rainfall was found before and after sowings, compared with the past. Emergence rate was generally higher for 2081-2100, while time to reach the maximum emergence rate decreased by about one week, compared with other periods, due to higher average seedbed temperatures. The rate of non-germinated seeds decreased, especially for the earlier sowing dates, but the frequency of non-emergence due to water stress increased after 2060 for all sowing dates, including the mid-February sowing. Bolting remains a risk for sowings before mid-March although this risk will be markedly decreased after 2060. The changes in seedbed conditions will be significant after 2060 in terms of temperatures. However, the possibility of field access will be a main limiting factor for earlier sowings, as no significant changes in cumulative rainfall, compared with the past, will occur under future climate change. When field access is not a constraint, an anticipation of the sowing date, compared to the currently practiced sowing (i.e. mid-March), will lead to decreased risks for the sugar beet crop establishment and bolting. The use of future climate scenarios coupled with a crop model allows a precise insight into the future sowing conditions, and provide helpful information to better project future farming systems.

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