Quantifying the biologically possible range of steady-state soil and surface climates with climate model simulations

Biologia ◽  
2006 ◽  
Vol 61 (19) ◽  
Author(s):  
Axel Kleidon
Keyword(s):  
Surface Energy ◽  
Land Surface ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Climatic Conditions ◽  
Terrestrial Biosphere ◽  
Form And Function ◽  
Climate Model Simulations ◽  
Vegetation Form

AbstractThe terrestrial biosphere shapes the exchange fluxes of energy and mass at the land surface. The diversity of plant form and functioning can potentially result in a wide variety of possible climatic conditions at the land surface and in the soil, which in turn feed back to more or less suitable conditions for terrestrial productivity. Here, I use sensitivity simulations to vegetation form and functioning with a global climate model to quantify this possible range of steady-states (“PROSS”) of the surface energy-and mass balances. The surface energy-and water balances over land are associated with substantial sensitivity to vegetation parameters, with precipitation varying by more than a factor of 2, and evapotranspiration by a factor of 5. This range in biologically possible climatic conditions is associated with drastically different levels of vegetation productivity. Optimum conditions for maximum productivity are close to the simulated climate of present-day conditions. These results suggest the conclusions that (a) climate does not determine vegetation form and function, but merely constrains it, and (b) the emergent climatic conditions at the land surface seem to be close to optimal for the functioning of the terrestrial biosphere.

scholarly journals Ability of a land surface model to predict climate induced changes in northern Russian river runoff during the 21st century

2015 ◽  
Vol 371 ◽  
pp. 59-64 ◽  
Author(s):  
O. N. Nasonova ◽  
Y. M. Gusev ◽  
E. M. Volodin ◽  
E. E. Kovalev
Keyword(s):  
River Runoff ◽  
Land Surface ◽  
Climate Model ◽  
Greenhouse Gas Emission ◽  
Global Climate ◽  
Global Climate Model ◽  
Land Surface Model ◽  
Climatic Conditions ◽  
Surface Model ◽  
Russian River

Abstract. The objective of the present study is application of the land surface model SWAP to project climate change impact on northern Russian river runoff up to 2100 using meteorological projections from the atmosphere–ocean global climate model INMCM4.0. The study was performed for the Northern Dvina River and the Kolyma River characterized by different climatic conditions. The ability of both models to reproduce the observed river runoff was investigated. To apply SWAP for hydrological projections, the robustness of the model was evaluated. The river runoff projections up to 2100 were calculated for two greenhouse gas emission scenarios: RCP8.5 and RCP4.5 prepared for the phase five of the Coupled Model Intercomparison Project (CMIP5). For each scenario, several runoff projections were obtained using different models (INMCM4.0 and SWAP) and different post-processing techniques for correcting biases in meteorological forcing data. Differences among the runoff projections obtained for the same emission scenario and the same period illustrate uncertainties resulted from application of different models and bias-correcting techniques.

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 The PRISM4 (mid-Piacenzian) paleoenvironmental reconstruction

2016 ◽  
Vol 12 (7) ◽  
pp. 1519-1538 ◽  
Author(s):  
Harry Dowsett ◽  
Aisling Dolan ◽  
David Rowley ◽  
Robert Moucha ◽  
Alessandro M. Forte ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Land Surface ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Sea Surface ◽  
Paleoenvironmental Reconstruction ◽  
Dynamic Topography ◽  
Intercomparison Project

Abstract. The mid-Piacenzian is known as a period of relative warmth when compared to the present day. A comprehensive understanding of conditions during the Piacenzian serves as both a conceptual model and a source for boundary conditions as well as means of verification of global climate model experiments. In this paper we present the PRISM4 reconstruction, a paleoenvironmental reconstruction of the mid-Piacenzian ( ∼  3 Ma) containing data for paleogeography, land and sea ice, sea-surface temperature, vegetation, soils, and lakes. Our retrodicted paleogeography takes into account glacial isostatic adjustments and changes in dynamic topography. Soils and lakes, both significant as land surface features, are introduced to the PRISM reconstruction for the first time. Sea-surface temperature and vegetation reconstructions are unchanged but now have confidence assessments. The PRISM4 reconstruction is being used as boundary condition data for the Pliocene Model Intercomparison Project Phase 2 (PlioMIP2) experiments.

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

AN EQUATION OF STATE FOR LAND SURFACE CLIMATES

2011 ◽  
Vol 21 (12) ◽  
pp. 3577-3587 ◽  
Author(s):  
KLAUS FRAEDRICH ◽  
FRANK SIELMANN
Keyword(s):  
Equation Of State ◽  
Land Surface ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Regional Scale ◽  
State Parameter ◽  
Lake Area ◽  
Rainfall Runoff ◽  
Change Analysis

A biased coinflip Ansatz provides a stochastic regional scale surface climate model of minimum complexity, which represents physical and stochastic properties of the rainfall–runoff chain. The solution yields the Schreiber–Budyko relation as an equation of state describing land surface vegetation, river runoff and lake areas in terms of physical flux ratios, which are associated with three thresholds. Validation of consistency and predictability within a Global Climate Model (GCM) environment demonstrates the stochastic rainfall–runoff chain to be a viable surrogate model for regional climate state averages and variabilites. A terminal (closed) lake area ratio is introduced as a new climate state parameter, which quantifies lake overflow as a threshold in separating water from energy limited climate regimes. A climate change analysis based on the IPCC A1B scenario is included for completeness.

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>

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