scholarly journals Estimating Changes in Global Temperature since the Preindustrial Period

2017 ◽  
Vol 98 (9) ◽  
pp. 1841-1856 ◽  
Author(s):  
Ed Hawkins ◽  
Pablo Ortega ◽  
Emma Suckling ◽  
Andrew Schurer ◽  
Gabi Hegerl ◽  
...  
Keyword(s):  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Global Temperature ◽  
Radiative Forcings ◽  
Global Average ◽  
Average Temperature ◽  
Climate Model Simulations ◽  
Temperature Levels ◽  
Definition Of

Abstract The United Nations Framework Convention on Climate Change (UNFCCC) process agreed in Paris to limit global surface temperature rise to “well below 2°C above pre-industrial levels.” But what period is preindustrial? Somewhat remarkably, this is not defined within the UNFCCC’s many agreements and protocols. Nor is it defined in the IPCC’s Fifth Assessment Report (AR5) in the evaluation of when particular temperature levels might be reached because no robust definition of the period exists. Here we discuss the important factors to consider when defining a preindustrial period, based on estimates of historical radiative forcings and the availability of climate observations. There is no perfect period, but we suggest that 1720–1800 is the most suitable choice when discussing global temperature limits. We then estimate the change in global average temperature since preindustrial using a range of approaches based on observations, radiative forcings, global climate model simulations, and proxy evidence. Our assessment is that this preindustrial period was likely 0.55°–0.80°C cooler than 1986–2005 and that 2015 was likely the first year in which global average temperature was more than 1°C above preindustrial levels. We provide some recommendations for how this assessment might be improved in the future and suggest that reframing temperature limits with a modern baseline would be inherently less uncertain and more policy relevant.

scholarly journals Sea-Breeze Dynamics and Convection Initiation: The Influence of Convective Parameterization in Weather and Climate Model Biases

2015 ◽  
Vol 28 (20) ◽  
pp. 8093-8108 ◽  
Author(s):  
Cathryn E. Birch ◽  
Malcolm J. Roberts ◽  
Luis Garcia-Carreras ◽  
Duncan Ackerley ◽  
Michael J. Reeder ◽  
...  
Keyword(s):  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Sea Breeze ◽  
Early Morning ◽  
Sea Temperature ◽  
Convective Parameterization ◽  
Study Approach ◽  
Climate Model Simulations ◽  
Convection Initiation

Abstract There are some long-established biases in atmospheric models that originate from the representation of tropical convection. Previously, it has been difficult to separate cause and effect because errors are often the result of a number of interacting biases. Recently, researchers have gained the ability to run multiyear global climate model simulations with grid spacings small enough to switch the convective parameterization off, which permits the convection to develop explicitly. There are clear improvements to the initiation of convective storms and the diurnal cycle of rainfall in the convection-permitting simulations, which enables a new process-study approach to model bias identification. In this study, multiyear global atmosphere-only climate simulations with and without convective parameterization are undertaken with the Met Office Unified Model and are analyzed over the Maritime Continent region, where convergence from sea-breeze circulations is key for convection initiation. The analysis shows that, although the simulation with parameterized convection is able to reproduce the key rain-forming sea-breeze circulation, the parameterization is not able to respond realistically to the circulation. A feedback of errors also occurs: the convective parameterization causes rain to fall in the early morning, which cools and wets the boundary layer, reducing the land–sea temperature contrast and weakening the sea breeze. This is, however, an effect of the convective bias, rather than a cause of it. Improvements to how and when convection schemes trigger convection will improve both the timing and location of tropical rainfall and representation of sea-breeze circulations.

scholarly journals Global warming precipitation accumulation increases above the current-climate cutoff scale

2017 ◽  
Vol 114 (6) ◽  
pp. 1258-1263 ◽  
Author(s):  
J. David Neelin ◽  
Sandeep Sahany ◽  
Samuel N. Stechmann ◽  
Diana N. Bernstein
Keyword(s):  
Global Warming ◽  
Probability Density ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Storm Event ◽  
Current Climate ◽  
Order Of Magnitude ◽  
Climate Model Simulations ◽  
Precipitation Loss

Precipitation accumulations, integrated over rainfall events, can be affected by both intensity and duration of the storm event. Thus, although precipitation intensity is widely projected to increase under global warming, a clear framework for predicting accumulation changes has been lacking, despite the importance of accumulations for societal impacts. Theory for changes in the probability density function (pdf) of precipitation accumulations is presented with an evaluation of these changes in global climate model simulations. We show that a simple set of conditions implies roughly exponential increases in the frequency of the very largest accumulations above a physical cutoff scale, increasing with event size. The pdf exhibits an approximately power-law range where probability density drops slowly with each order of magnitude size increase, up to a cutoff at large accumulations that limits the largest events experienced in current climate. The theory predicts that the cutoff scale, controlled by the interplay of moisture convergence variance and precipitation loss, tends to increase under global warming. Thus, precisely the large accumulations above the cutoff that are currently rare will exhibit increases in the warmer climate as this cutoff is extended. This indeed occurs in the full climate model, with a 3 °C end-of-century global-average warming yielding regional increases of hundreds of percent to >1,000% in the probability density of the largest accumulations that have historical precedents. The probabilities of unprecedented accumulations are also consistent with the extension of the cutoff.

Global Instrumental Meteorological Database Before 1890 – a useful overview

2021 ◽  
Author(s):  
Elin Lundstad ◽  
Yuri Brugnera ◽  
Stefan Brönnimann
Keyword(s):  
Meteorological Parameters ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Meteorological Station ◽  
Climate Data ◽  
Data Set ◽  
Instrumental Data ◽  
The World ◽  
Climate Model Simulations

<p>This work describes the compilation of global instrumental climate data with a focus on the 18th and early 19th centuries. This database provides early instrumental data recovered for thousands of locations around the world. Instrumental meteorological measurements from periods prior to the start of national weather services are designated “early instrumental data”. Much of the data is taken from repositories we know (GHCN, ISTI, CRUTEM, Berkeley Earth, HISTALP). In addition, many of these stations have not been digitized before. Therefore,  we provide a new global collection of monthly averages of multivariable meteorological parameters before 1890 based on land-based meteorological station data. The product will be form as the most comprehensive global monthly climate data set, encompassing temperature, pressure, and precipitation as ever done. These data will be quality controlled and analyzed with respect to climate variability and they be assimilated into global climate model simulations to provide monthly global reconstructions. The collection has resulted in a completely new database that is uniform, where no interpolations are included. Therefore, we are left with climate reconstruction that becomes very authentic. This compilation will describe the procedure and various challenges we have encountered by creating a unified database that can later be used for e.g. models. It will also describe the strategy for quality control that has been adopted is a sequence of tests.</p>

scholarly journals Remote sensing of aerosols in the Arctic for an evaluation of global climate model simulations

2014 ◽  
Vol 119 (13) ◽  
pp. 8169-8188 ◽  
Author(s):  
Paul Glantz ◽  
Adam Bourassa ◽  
Andreas Herber ◽  
Trond Iversen ◽  
Johannes Karlsson ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
The Arctic ◽  
Model Simulations ◽  
Climate Model Simulations

scholarly journals Elevation-dependent warming in global climate model simulations at high spatial resolution

2018 ◽  
Vol 52 (5-6) ◽  
pp. 2685-2702 ◽  
Author(s):  
Elisa Palazzi ◽  
Luca Mortarini ◽  
Silvia Terzago ◽  
Jost von Hardenberg
Keyword(s):  
Spatial Resolution ◽  
Climate Model ◽  
High Spatial Resolution ◽  
Global Climate ◽  
Global Climate Model ◽  
Model Simulations ◽  
Climate Model Simulations

scholarly journals Strong future increases in Arctic precipitation variability linked to poleward moisture transport

2020 ◽  
Author(s):  
Richard Bintanja ◽  
Karin van der Wiel ◽  
Eveline van der Linden ◽  
Jesse Reusen ◽  
Linda Bogerd ◽  
...  
Keyword(s):  
Interannual Variability ◽  
Moisture Transport ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Arctic Region ◽  
The Arctic ◽  
Climate Model Simulations ◽  
Mean Climate ◽  
Increasing Precipitation

<p>The Arctic region is projected to experience amplified warming as well as strongly increasing precipitation rates. Equally important to trends in the mean climate are changes in interannual variability, but changes in precipitation fluctuations are highly uncertain and the associated processes unknown. Here we use various state-of-the-art global climate model simulations to show that interannual variability of Arctic precipitation will likely increase markedly (up to 40% over the 21<sup>st</sup> century), especially in summer. This can be attributed to increased poleward atmospheric moisture transport variability associated with enhanced moisture content, possibly modulated by atmospheric dynamics. Because both the means and variability of Arctic precipitation will increase, years/seasons with excessive precipitation will occur more often, as will the associated impacts.</p>

scholarly journals Simulation of black carbon in snow and its climate impact in the Canadian Global Climate Model

2015 ◽  
Vol 15 (13) ◽  
pp. 18839-18882 ◽  
Author(s):  
M. Namazi ◽  
K. von Salzen ◽  
J. N. S. Cole
Keyword(s):  
Black Carbon ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Surface Air Temperature ◽  
Climate Impact ◽  
Radiative Forcings ◽  
Mixing Ratios ◽  
Emission Changes ◽  
The Impact

Abstract. A new physically-based parameterization of black carbon (BC) in snow was developed and implemented in the Canadian Atmospheric Global Climate Model (CanAM4.2). Simulated BC snow mixing ratios and BC snow radiative forcings are in good agreement with measurements and results from other models. Simulations with the improved model yield considerable trends in regional BC concentrations in snow and BC snow radiative forcings during the time period from 1950–1959 to 2000–2009. Increases in radiative forcings for Asia and decreases for Europe and North America are found to be associated with changes in BC emissions. Additional sensitivity simulations were performed in order to study the impact of BC emission changes between 1950–1959 and 2000–2009 on surface albedo, snow cover fraction, and surface air temperature. Results from these simulations indicate that impacts of BC emission changes on snow albedos between these two decades are small and not significant. Overall, changes in BC concentrations in snow have much smaller impacts on the cryosphere than the net warming surface air temperatures during the second half of the 20th century.

scholarly journals Flexible parameter-sparse global temperature time profiles that stabilise at 1.5 and 2.0  °C

2017 ◽  
Vol 8 (3) ◽  
pp. 617-626 ◽  
Author(s):  
Chris Huntingford ◽  
Hui Yang ◽  
Anna Harper ◽  
Peter M. Cox ◽  
Nicola Gedney ◽  
...  
Keyword(s):  
Climate Model ◽  
Algebraic Curves ◽  
Climate Impacts ◽  
Global Temperature ◽  
Temperature Profiles ◽  
Average Temperature ◽  
Time Profiles ◽  
Generational Changes ◽  
Climate Model Simulations ◽  
Two Parameters

Abstract. The meeting of the United Nations Framework Convention on Climate Change (UNFCCC) in December 2015 committed parties at the convention to hold the rise in global average temperature to well below 2.0 °C above pre-industrial levels. It also committed the parties to pursue efforts to limit warming to 1.5 °C. This leads to two key questions. First, what extent of emissions reduction will achieve either target? Second, what is the benefit of the reduced climate impacts from keeping warming at or below 1.5 °C? To provide answers, climate model simulations need to follow trajectories consistent with these global temperature limits. It is useful to operate models in an inverse mode to make model-specific estimates of greenhouse gas (GHG) concentration pathways consistent with the prescribed temperature profiles. Further inversion derives related emissions pathways for these concentrations. For this to happen, and to enable climate research centres to compare GHG concentrations and emissions estimates, common temperature trajectory scenarios are required. Here we define algebraic curves that asymptote to a stabilised limit, while also matching the magnitude and gradient of recent warming levels. The curves are deliberately parameter-sparse, needing the prescription of just two parameters plus the final temperature. Yet despite this simplicity, they can allow for temperature overshoot and for generational changes, for which more effort to decelerate warming change needs to be made by future generations. The curves capture temperature profiles from the existing Representative Concentration Pathway (RCP2.6) scenario projections by a range of different Earth system models (ESMs), which have warming amounts towards the lower levels of those that society is discussing.

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