scholarly journals Last interglacial model–data mismatch of thermal maximum temperatures partially explained

2014 ◽  
Vol 10 (4) ◽  
pp. 1633-1644 ◽  
Author(s):  
P. Bakker ◽  
H. Renssen
Keyword(s):  
Climate Models ◽  
Temporal Variations ◽  
Model Data ◽  
Last Interglacial ◽  
Underlying Assumption ◽  
Thermal Maximum ◽  
Spatio Temporal ◽  
Maximum Temperatures ◽  
The Impact ◽  
Global Mean

Abstract. The timing of the last interglacial (LIG) thermal maximum across the globe remains to be precisely assessed. Because of difficulties in establishing a common temporal framework between records from different palaeoclimatic archives retrieved from various places around the globe, it has not yet been possible to reconstruct spatio-temporal variations in the occurrence of the maximum warmth across the globe. Instead, snapshot reconstructions of warmest LIG conditions have been presented, which have an underlying assumption that maximum warmth occurred synchronously everywhere. Although known to be an oversimplification, the impact of this assumption on temperature estimates has yet to be assessed. We use the LIG temperature evolutions simulated by nine different climate models to investigate whether the assumption of synchronicity results in a sizeable overestimation of the LIG thermal maximum. We find that for annual temperatures, the overestimation is small, strongly model-dependent (global mean 0.4 ± 0.3 °C) and cannot explain the recently published 0.67 °C difference between simulated and reconstructed annual mean temperatures during the LIG thermal maximum. However, if one takes into consideration that temperature proxies are possibly biased towards summer, the overestimation of the LIG thermal maximum based on warmest month temperatures is non-negligible with a global mean of 1.1 ± 0.4 °C.

scholarly journals Last Interglacial model-data mismatch of thermal maximum temperatures partially explained

2014 ◽  
Vol 10 (1) ◽  
pp. 739-760 ◽  
Author(s):  
P. Bakker ◽  
H. Renssen
Keyword(s):  
Climate Models ◽  
Global Model ◽  
Model Data ◽  
Last Interglacial ◽  
Thermal Maximum ◽  
Maximum Temperatures ◽  
The Impact ◽  
Global Mean

Abstract. The timing of the Last Interglacial (LIG) thermal maximum is highly uncertain. Compilations of maximum LIG temperatures are therefore based on the assumption that maximum warmth occurred synchronously across the globe. Although known to be an oversimplification, the impact of this assumption on temperature estimates has yet to be assessed. We use the LIG temperature evolutions simulated by 9 different climate models to investigate whether the assumption of synchronicity results in a sizeable overestimation of LIG thermal maximum temperatures. We find that for annual temperatures, the overestimation is small, strongly model-dependent (global mean 0.4 ± 0.3 °C) and cannot explain the recently published 0.67 °C difference between simulated and reconstructed LIG thermal maximum temperatures. However, if one takes into consideration that temperature proxies are possibly biased towards summer, the overestimation of the LIG thermal maximum based on warmest month temperatures is non-negligible (global mean 1.1 ± 0.4 °C) and can at least partly explain the 0.67 °C global model-data difference.

scholarly journals Influences of hydroxyl radicals (OH) on top-down estimates of the global and regional methane budgets

2020 ◽  
Author(s):  
Yuanhong Zhao ◽  
Marielle Saunois ◽  
Philippe Bousquet ◽  
Xin Lin ◽  
Antoine Berchet ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Climate Models ◽  
Transport Model ◽  
Atmospheric Transport ◽  
Temporal Variations ◽  
Oh Radicals ◽  
Chemical Transport Model ◽  
Top Down ◽  
Ch4 Emissions ◽  
The Impact

Abstract. The hydroxyl radical (OH), which is the dominant sink of methane (CH4), plays a key role to close the global methane budget. Previous research that assessed the impact of OH changes on the CH4 budget mostly relied on box modeling inversions with a very simplified atmospheric transport and no representation of the heterogeneous spatial distribution of OH radicals. Here using a variational Bayesian inversion framework and a 3D chemical transport model, LMDz, combined with 10 different OH fields derived from chemistry-climate models (CCMI experiment), we evaluate the influence of OH burden, spatial distribution, and temporal variations on the global CH4 budget. The global tropospheric mean CH4-reaction-weighted [OH] ([OH]GM-CH4) ranges 10.3–16.3 × 105 molec cm−3 across 10 OH fields during the early 2000s, resulting in inversion-based global CH4 emissions between 518 and 757 Tg yr−1. The uncertainties in CH4 inversions induced by the different OH fields are comparable to, or even larger than the uncertainty typically given by bottom-up and top-down estimates. Based on the LMDz inversions, we estimate that a 1 %-increase in OH burden leads to an increase of 4 Tg yr−1 in the estimate of global methane emissions, which is about 25 % smaller than what is estimated by box-models. The uncertainties in emissions induced by OH are largest over South America, corresponding to large inter-model differences of [OH] in this region. From the early to the late 2000s, the optimized CH4 emissions increased by 21.9 ± 5.7 Tg yr−1 (16.6–30.0 Tg yr−1), of which ~ 25 % (on average) is contributed by −0.5 to +1.8 % increase in OH burden. If the CCMI models represent the OH trend properly over the 2000s, our results show that a higher increasing trend of CH4 emissions is needed to match the CH4 observations compared to the CH4 emission trend derived using constant OH. This study strengthens the importance to reach a better representation of OH burden and of OH spatial and temporal distributions to reduce the uncertainties on the global CH4 budget.

scholarly journals Implications of model bias in carbon monoxide for methane lifetime

2015 ◽  
Vol 15 (14) ◽  
pp. 20305-20348 ◽  
Author(s):  
S. A. Strode ◽  
B. N. Duncan ◽  
E. A. Yegorova ◽  
J. Kouatchou ◽  
J. R. Ziemke ◽  
...  
Keyword(s):  
Carbon Monoxide ◽  
Hemispheric Asymmetry ◽  
Climate Models ◽  
Model Bias ◽  
Source Type ◽  
Methyl Chloroform ◽  
Northern Latitudes ◽  
High Bias ◽  
The Impact ◽  
Global Mean

Abstract. A low bias in carbon monoxide (CO) at high northern latitudes is a common feature of chemistry climate models (CCMs) that may indicate or contribute to a high bias in simulated OH and corresponding low bias in methane lifetime. We use simulations with CO tagged by source type to investigate the sensitivity of the CO bias to CO emissions, global mean OH, and the hemispheric asymmetry of OH. Our results show that reducing the hemispheric asymmetry of OH improves the agreement of simulated CO with observations. We use simulations with parameterized OH to quantify the impact of known model biases on simulated OH. Removing biases in ozone and water vapor as well as reducing Northern Hemisphere NOx does not remove the hemispheric asymmetry in OH, but brings the simulated methyl chloroform lifetime into agreement with observation-based estimates.

scholarly journals Greenland Ice Sheet influence on Last Interglacial climate: global sensitivity studies performed with an atmosphere–ocean general circulation model

2016 ◽  
Vol 12 (6) ◽  
pp. 1313-1338 ◽  
Author(s):  
Madlene Pfeiffer ◽  
Gerrit Lohmann
Keyword(s):  
Temperature Change ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Minor Importance ◽  
Last Interglacial ◽  
Proxy Data ◽  
Proxy Records ◽  
Thermal Maximum ◽  
Sensitivity Studies ◽  
The Impact

Abstract. During the Last Interglacial (LIG, ∼130–115 kiloyears (kyr) before present (BP)), the northern high latitudes were characterized by higher temperatures than those of the late Holocene and a lower Greenland Ice Sheet (GIS). However, the impact of a reduced GIS on the global climate has not yet been well constrained. In this study, we quantify the contribution of the GIS to LIG warmth by performing various sensitivity studies based on equilibrium simulations, employing the Community Earth System Models (COSMOS), with a focus on height and extent of the GIS. We present the first study on the effects of a reduction in the GIS on the surface temperature (TS) on a global scale and separate the contribution of astronomical forcing and changes in GIS to LIG warmth. The strong Northern Hemisphere summer warming of approximately 2 °C (with respect to pre-industrial) is mainly caused by increased summer insolation. Reducing the height by  ∼ 1300 m and the extent of the GIS does not have a strong influence during summer, leading to an additional global warming of only +0.24 °C compared to the purely insolation-driven LIG. The effect of a reduction in the GIS is, however, strongest during local winter, with up to +5 °C regional warming and with an increase in global average temperature of +0.48 °C. In order to evaluate the performance of our LIG simulations, we additionally compare the simulated TS anomalies with marine and terrestrial proxy-based LIG temperature anomalies derived from three different proxy data compilations. Our model results are in good agreement with proxy records with respect to the warming pattern but underestimate the magnitude of temperature change when compared to reconstructions, suggesting a potential misinterpretation of the proxy records or deficits in our model. However, we are able to partly reduce the mismatch between model and data by additionally taking into account the potential seasonal bias of the proxy record and/or the uncertainties in the dating of the proxy records for the LIG thermal maximum. The seasonal bias and the uncertainty of the timing are estimated from new transient model simulations covering the whole LIG. The model–data comparison improves for proxies that represent annual mean temperatures when the GIS is reduced and when we take the local thermal maximum during the LIG (130–120 kyr BP) into account. For proxy data that represent summer temperatures, changes in the GIS are of minor importance for sea surface temperatures. However, the annual mean and summer temperature change over Greenland in the reduced GIS simulations seems to be overestimated as compared to the local ice core data, which could be related to the interpretation of the recorder system and/or the assumptions of GIS reduction. Thus, the question regarding the real size of the GIS during the LIG has yet to be answered.

scholarly journals Preparing for a future COVID-19 wave: insights and limitations from a data-driven evaluation of non-pharmaceutical interventions in Germany

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Ashwin Aravindakshan ◽  
Jörn Boehnke ◽  
Ehsan Gholami ◽  
Ashutosh Nayak
Keyword(s):  
Public Space ◽  
Temporal Variations ◽  
International Travel ◽  
Disease Spread ◽  
Educational Institutions ◽  
Disease Propagation ◽  
Accurate Forecast ◽  
Spatio Temporal ◽  
The Impact ◽  
Pharmaceutical Interventions

AbstractTo contain the COVID-19 pandemic, governments introduced strict Non-Pharmaceutical Interventions (NPI) that restricted movement, public gatherings, national and international travel, and shut down large parts of the economy. Yet, the impact of the enforcement and subsequent loosening of these policies on the spread of COVID-19 is not well understood. Accordingly, we measure the impact of NPIs on mitigating disease spread by exploiting the spatio-temporal variations in policy measures across the 16 states of Germany. While this quasi-experiment does not allow for causal identification, each policy’s effect on reducing disease spread provides meaningful insights. We adapt the Susceptible–Exposed–Infected–Recovered model for disease propagation to include data on daily confirmed cases, interstate movement, and social distancing. By combining the model with measures of policy contributions on mobility reduction, we forecast scenarios for relaxing various types of NPIs. Our model finds that in Germany policies that mandated contact restrictions (e.g., movement in public space limited to two persons or people co-living), closure of educational institutions (e.g., schools), and retail outlet closures are associated with the sharpest drops in movement within and across states. Contact restrictions appear to be most effective at lowering COVID-19 cases, while border closures appear to have only minimal effects at mitigating the spread of the disease, even though cross-border travel might have played a role in seeding the disease in the population. We believe that a deeper understanding of the policy effects on mitigating the spread of COVID-19 allows a more accurate forecast of disease spread when NPIs are partially loosened and gives policymakers better data for making informed decisions.

scholarly journals Spatio-Temporal Consistency Evaluation of XCO2 Retrievals from GOSAT and OCO-2 Based on TCCON and Model Data for Joint Utilization in Carbon Cycle Research

Atmosphere ◽  
2019 ◽  
Vol 10 (7) ◽  
pp. 354 ◽  
Author(s):  
Yawen Kong ◽  
Baozhang Chen ◽  
Simon Measho
Keyword(s):  
Carbon Cycle ◽  
Mole Fraction ◽  
Transport Model ◽  
Total Carbon ◽  
Temporal Consistency ◽  
Model Data ◽  
Sources And Sinks ◽  
Spatio Temporal ◽  
The Impact

The global carbon cycle research requires precise and sufficient observations of the column-averaged dry-air mole fraction of CO 2 (XCO 2 ) in addition to conventional surface mole fraction observations. In addition, assessing the consistency of multi-satellite data are crucial for joint utilization to better infer information about CO 2 sources and sinks. In this work, we evaluate the consistency of long-term XCO 2 retrievals from the Greenhouse Gases Observing Satellite (GOSAT), Orbiting Carbon Observatory 2 (OCO-2) in comparison with Total Carbon Column Observing Network (TCCON) and the 3D model of CO 2 mole fractions data from CarbonTracker 2017 (CT2017). We create a consistent joint dataset and compare it with the long-term model data to assess their abilities to characterize the carbon cycle climate. The results show that, although slight increasing differences are found between the GOSAT and TCCON XCO 2 in the northern temperate latitudes, the GOSAT and OCO-2 XCO 2 retrievals agree well in general, with a mean bias ± standard deviation of differences of 0.21 ± 1.3 ppm. The differences are almost within ±2 ppm and are independent of time, indicating that they are well calibrated. The differences between OCO-2 and CT2017 XCO 2 are much larger than those between GOSAT and CT XCO 2 , which can be attributed to the significantly different spatial representatives of OCO-2 and the CT-transport model 5 (TM5). The time series of the combined OCO-2/GOSAT dataset and the modeled XCO 2 agree well, and both can characterize significantly increasing atmospheric CO 2 under the impact of a large El Niño during 2015 and 2016. The trend calculated from the dataset using the seasonal Kendall (S-K) method indicates that atmospheric CO 2 is increasing by 2–2.6 ppm per year.

Simulation of the mid-Pliocene Warm Period using HadGEM3-GC31-LL: Pliocene climate relative to the pre-industrial era, previous model versions, other climate models and proxy data

2021 ◽  
Author(s):  
Charles Williams ◽  
Daniel Lunt ◽  
Alistair Sellar ◽  
William Roberts ◽  
Robin Smith ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Climate Model ◽  
High Sensitivity ◽  
Warm Period ◽  
Future Climate ◽  
Future Climate Change ◽  
Last Interglacial ◽  
Proxy Data ◽  
Global Mean

<p>To better understand the processes contributing to future climate change, palaeoclimate model simulations are an important tool because they allow testing of the models’ ability to simulate very different climates than that of today.  As part of CMIP6/PMIP4, the latest version of the UK’s physical climate model, HadGEM3-GC31-LL (hereafter, for brevity, HadGEM3), was recently used to simulate the mid-Holocene (~6 ka) and Last Interglacial (~127 ka) simulations and the results were compared to the preindustrial era, previous versions of the same model and proxy data (see Williams et al. 2020, Climate of the Past).  Here, we use the same model to go further back in time, presenting the results from the mid-Pliocene Warm Period (~3.3 to 3 ma, hereafter the “Pliocene” for brevity).  This period is of particular interest when it comes to projections of future climate change under various scenarios of CO<sub>2</sub> emissions, because it is the most recent time in Earth’s history when CO<sub>2</sub> levels were roughly equivalent to today.  In response, albeit due to slower mechanisms than today’s anthropogenic fossil fuel driven-change, during the Pliocene global mean temperatures were 2-3°C higher than today, more so at the poles.</p><p> </p><p>Here, we present results from the HadGEM3 Pliocene simulation.  The model is responding to the Pliocene boundary conditions in a manner consistent with current understanding and existing literature.  When compared to the preindustrial era, global mean temperatures are currently ~5°C higher, with the majority of warming coming from high latitudes due to polar amplification from a lack of sea ice.  Relative to other models within the Pliocene Modelling Intercomparison Project (PlioMIP), this is the 2<sup>nd</sup> warmest model, with the majority of others only showing up to a 4.5°C increase and many a lot less.  This is consistent with the relatively high sensitivity of HadGEM3, relative to other CMIP6-class models.  When compared to a previous generation of the same UK model, HadCM3, similar patterns of both surface temperature and precipitation changes are shown (relative to preindustrial).  Moreover, when the simulations are compared to proxy data, the results suggest that the HadGEM3 Pliocene simulation is closer to the reconstructions than its predecessor.</p>

scholarly journals Spatio-temporal Variability and Trends of Mean and Extreme Rainfall Events in the Sudano-sahelian Region of Cameroon

2021 ◽  
Author(s):  
Ibrahim NJOUENWET ◽  
Lucie A. Djiotang Tchotchou ◽  
Brian Odhiambo Ayugi ◽  
Guy Merlin Guenang ◽  
Derbetini A. Vondou ◽  
...  
Keyword(s):  
Climate Change ◽  
Extreme Rainfall ◽  
Temporal Variations ◽  
Annual Rainfall ◽  
Drought Risk ◽  
Extreme Rainfall Events ◽  
Rainfall Events ◽  
Precipitation Concentration ◽  
Spatio Temporal ◽  
The Impact

Abstract The Sudano-Sahelian region of Cameroon is mainly drained by the Benue, Chari and Logone rivers, which are very useful for water resources, especially for irrigation, hydropower generation, and navigation. Long-term changes in mean and extreme rainfall events in the region may be of crucial importance in understanding the impact of climate change. Daily and monthly rainfall data from twenty-five synoptic stations in the study area from 1980 to 2019 and extreme indices from the Expert Team on Climate Change Detection and Indices (ETCCDI) measurements were estimated using the non-parametric Modified Mann-Kendall test and the Sen slope estimator. The precipitation concentration index (PCI), the precipitation concentration degree (PCD), and the precipitation concentration period (PCP) were used to explore the spatio-temporal variations in the characteristics of rainfall concentrations. An increase in extreme rainfall events was observed, leading to an upward trend in mean annual. Trends in consecutive dry days (CDD) are significantly increasing in most parts of the study area. This could mean that the prevalence of drought risk is higher in the study area. Overall, the increase in annual rainfall could benefit the hydro-power sector, agricultural irrigation, the availability of potable water sources, and food security.

scholarly journals Landscape Dynamics Improved Recreation Service of the Three Gorges Reservoir Area, China

2021 ◽  
Vol 18 (16) ◽  
pp. 8356
Author(s):  
Dengyue Zhao ◽  
Mingzhu Xiao ◽  
Chunbo Huang ◽  
Yuan Liang ◽  
Ziyue An
Keyword(s):  
Three Gorges Reservoir ◽  
Temporal Variations ◽  
Landscape Dynamics ◽  
Three Gorges Reservoir Area ◽  
Three Gorges ◽  
The Three Gorges ◽  
Vegetation Landscape ◽  
Recreation Service ◽  
Spatio Temporal ◽  
The Impact

Spatio-temporal variations of recreation service not only could help to understand the impact of cultural services on human well-being but also provides theoretical and technical support for regional landscape management. However, previous studies have avoided deeply quantifying and analyzing it or have simply focused on assessing recreational service at a single period in time. In this study, we used the InVEST model to evaluate the spatio-temporal variations of recreation service in the Three Gorges Reservoir Area and demonstrated the impact of recreation service on landscape dynamics. The results demonstrated that recreation service increased significantly and presented a significant spatial heterogeneity. Although afforestation and urban expansion both could significantly increase recreation service, the recreation service proxy of the non-vegetation landscape is far higher than that of the vegetation landscape. This finding indicated that human landscape is more attractive to tourists than the natural landscape, so we recommend to strengthen the infrastructure construction for enhancing the accessibility of natural landscapes. Moreover, we propose other constructive suggestions and landscape-design solutions for promoting recreation service. This study shifted the static environmental health assessment to the analysis of recreation service dynamics, bridging the regulatory mechanisms of ecosystem services involved in cultural services.

scholarly journals A Stochastic Analysis of the Impact of Small-Scale Fluctuations on the Tropospheric Temperature Response to CO2 Doubling

2010 ◽  
Vol 23 (9) ◽  
pp. 2307-2319 ◽  
Author(s):  
Rita Seiffert ◽  
Jin-Song von Storch
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Small Scale ◽  
Tropospheric Temperature ◽  
Climate Response ◽  
Restoring Force ◽  
Global Mean Temperature ◽  
Mean Temperature ◽  
The Impact ◽  
Global Mean

Abstract The climate response to increased CO2 concentration is generally studied using climate models that have finite spatial and temporal resolutions. Different parameterizations of the effect of unresolved processes can result in different representations of small-scale fluctuations in the climate model. The representation of small-scale fluctuations can, on the other hand, affect the modeled climate response. In this study the mechanisms by which enhanced small-scale fluctuations alter the climate response to CO2 doubling are investigated. Climate experiments with preindustrial and doubled CO2 concentrations obtained from a comprehensive climate model [ECHAM5/Max Planck Institute Ocean Model (MPI-OM)] are analyzed both with and without enhanced small-scale fluctuations. By applying a stochastic model to the experimental results, two different mechanisms are found. First, the small-scale fluctuations can change the statistical behavior of the global mean temperature as measured by its statistical damping. The statistical damping acts as a restoring force that determines, according to the fluctuation–dissipation theory, the amplitude of the climate response to a change in external forcing (here, CO2 doubling). Second, the small-scale fluctuations can affect processes that occur only in response to the CO2 increase, thereby altering the change of the effective forcing on the global mean temperature.

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