scholarly journals Including the efficacy of land ice changes in deriving climate sensitivity from paleodata

2019 ◽  
Vol 10 (2) ◽  
pp. 333-345 ◽  
Author(s):  
Lennert B. Stap ◽  
Peter Köhler ◽  
Gerrit Lohmann
Keyword(s):  
Climate Sensitivity ◽  
Radiative Forcing ◽  
Climate Models ◽  
Co2 Concentration ◽  
Global Temperature ◽  
Maximum Temperature ◽  
Radiative Forcings ◽  
The Impact ◽  
The Last Glacial

Abstract. The equilibrium climate sensitivity (ECS) of climate models is calculated as the equilibrium global mean surface air warming resulting from a simulated doubling of the atmospheric CO2 concentration. In these simulations, long-term processes in the climate system, such as land ice changes, are not incorporated. Hence, climate sensitivity derived from paleodata has to be compensated for these processes, when comparing it to the ECS of climate models. Several recent studies found that the impact these long-term processes have on global temperature cannot be quantified directly through the global radiative forcing they induce. This renders the prevailing approach of deconvoluting paleotemperatures through a partitioning based on radiative forcings inaccurate. Here, we therefore implement an efficacy factor ε[LI] that relates the impact of land ice changes on global temperature to that of CO2 changes in our calculation of climate sensitivity from paleodata. We apply our refined approach to a proxy-inferred paleoclimate dataset, using ε[LI]=0.45-0.20+0.34 based on a multi-model assemblage of simulated relative influences of land ice changes on the Last Glacial Maximum temperature anomaly. The implemented ε[LI] is smaller than unity, meaning that per unit of radiative, forcing the impact on global temperature is less strong for land ice changes than for CO2 changes. Consequently, our obtained ECS estimate of 5.8±1.3 K, where the uncertainty reflects the implemented range in ε[LI], is ∼50 % higher than when differences in efficacy are not considered.

scholarly journals Including the efficacy of land ice changes in deriving climate sensitivity from paleodata

2018 ◽  
Author(s):  
Lennert B. Stap ◽  
Peter Köhler ◽  
Gerrit Lohmann
Keyword(s):  
Climate Sensitivity ◽  
Radiative Forcing ◽  
Climate Models ◽  
Climate Model ◽  
Temperature Anomaly ◽  
Global Temperature ◽  
Radiative Forcings ◽  
Intercomparison Project ◽  
The Impact

Abstract. The influence of long-term processes in the climate system, such as land ice changes, has to be compensated for when comparing climate sensitivity derived from paleodata with equilibrium climate sensitivity (ECS) calculated by climate models, which is only generated by a CO2 change. Several recent studies found that the impact these long-term processes have on global temperature cannot be quantified directly through the global radiative forcing they induce. This renders the approach of deconvoluting paleotemperatures through a partitioning based on radiative forcings inaccurate. Here, we therefore implement an efficacy factor ε[LI], that relates the impact of land ice changes on global temperature to that of CO2 changes, in our calculation of climate sensitivity from paleodata. We apply our new approach to a proxy-inferred paleoclimate dataset, and find an equivalent ECS of 5.6 ± 1.3 K per CO2 doubling. The substantial uncertainty herein is generated by the range in ε[LI] we use, which is based on a multi-model assemblage of simulated relative influences of land ice changes on the Last Glacial Maximum (LGM) temperature anomaly (46 ± 14 %). The low end of our ECS estimate, which concurs with estimates from other approaches, tallies with a large influence for land ice changes. To separately assess this influence, we analyse output of the PMIP3 climate model intercomparison project. From this data, we infer a functional intermodel relation between global and high-latitude temperature changes at the LGM with respect to the pre-industrial climate, and the temperature anomaly caused by a CO2 change. Applying this relation to our dataset, we find a considerable 64 % influence for land ice changes on the LGM temperature anomaly. This is even higher than the range used before, and leads to an equivalent ECS of 3.8 K per CO2 doubling. Together, our results suggest that land ice changes play a key role in the variability of Late Pleistocene temperatures.

scholarly journals Total aerosol effect: radiative forcing or radiative flux perturbation?

2009 ◽  
Vol 9 (6) ◽  
pp. 25633-25661 ◽  
Author(s):  
U. Lohmann ◽  
L. Rotstayn ◽  
T. Storelvmo ◽  
A. Jones ◽  
S. Menon ◽  
...  
Keyword(s):  
Global Warming ◽  
Radiative Forcing ◽  
Climate Models ◽  
Radiative Flux ◽  
Radiative Forcings ◽  
Microphysical Properties ◽  
Aerosol Effect ◽  
Rain Formation ◽  
Aerosol Radiative ◽  
Flux Perturbation

Abstract. Uncertainties in aerosol radiative forcings, especially those associated with clouds, contribute to a large extent to uncertainties in the total anthropogenic forcing. The interaction of aerosols with clouds and radiation introduces feedbacks which can affect the rate of rain formation. In former assessments of aerosol radiative forcings, these effects have not been quantified. Also, with global aerosol-climate models simulating interactively aerosols and cloud microphysical properties, a quantification of the aerosol forcings in the traditional way is difficult to properly define. Here we argue that fast feedbacks should be included because they act quickly compared with the time scale of global warming. We show that for different forcing agents (aerosols and greenhouse gases) the radiative forcings as traditionally defined agree rather well with estimates from a method, here referred to as radiative flux perturbations (RFP), that takes these fast feedbacks and interactions into account. Based on our results, we recommend RFP as a valid option to compare different forcing agents, and to compare the effects of particular forcing agents in different models.

scholarly journals Evaluation of Future Climate and Potential Impact on Streamflow in the Upper Nan River Basin of Northern Thailand

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Miyuru B. Gunathilake ◽  
Yasasna V. Amaratunga ◽  
Anushka Perera ◽  
Imiya M. Chathuranika ◽  
Anura S. Gunathilake ◽  
...  
Keyword(s):  
River Basin ◽  
Minimum Temperature ◽  
Climate Models ◽  
Hydrological Modeling ◽  
Winter Season ◽  
Future Climate ◽  
Maximum Temperature ◽  
Monthly Precipitation ◽  
Northern Thailand ◽  
The Impact

Water resources in Northern Thailand have been less explored with regard to the impact on hydrology that the future climate would have. For this study, three regional climate models (RCMs) from the Coordinated Regional Downscaling Experiment (CORDEX) of Coupled Model Intercomparison Project 5 (CMIP5) were used to project future climate of the upper Nan River basin. Future climate data of ACCESS_CCAM, MPI_ESM_CCAM, and CNRM_CCAM under Representation Concentration Pathways RCP4.5 and RCP8.5 were bias-corrected by the linear scaling method and subsequently drove the Hydrological Engineering Center-Hydrological Modeling System (HEC-HMS) to simulate future streamflow. This study compared baseline (1988–2005) climate and streamflow values with future time scales during 2020–2039 (2030s), 2040–2069 (2050s), and 2070–2099 (2080s). The upper Nan River basin will become warmer in future with highest increases in the maximum temperature of 3.8°C/year for MPI_ESM and minimum temperature of 3.6°C/year for ACCESS_CCAM under RCP8.5 during 2080s. The magnitude of changes and directions in mean monthly precipitation varies, with the highest increase of 109 mm for ACESSS_CCAM under RCP 4.5 in September and highest decrease of 77 mm in July for CNRM, during 2080s. Average of RCM combinations shows that decreases will be in ranges of −5.5 to −48.9% for annual flows, −31 to −47% for rainy season flows, and −47 to −67% for winter season flows. Increases in summer seasonal flows will be between 14 and 58%. Projection of future temperature levels indicates that higher increases will be during the latter part of the 20th century, and in general, the increases in the minimum temperature will be higher than those in the maximum temperature. The results of this study will be useful for river basin planners and government agencies to develop sustainable water management strategies and adaptation options to offset negative impacts of future changes in climate. In addition, the results will also be valuable for agriculturists and hydropower planners.

scholarly journals The impact of neglecting ice phase on cloud optical depth retrievals from AERONET cloud mode observations

2019 ◽  
Vol 12 (9) ◽  
pp. 5087-5099 ◽  
Author(s):  
Jonathan K. P. Shonk ◽  
Jui-Yuan Christine Chiu ◽  
Alexander Marshak ◽  
David M. Giles ◽  
Chiung-Huei Huang ◽  
...  
Keyword(s):  
Linear Equation ◽  
Optical Depth ◽  
Climate Models ◽  
Deep Convection ◽  
Surface Flux ◽  
Climate Modelling ◽  
Cloud Optical Depth ◽  
The Impact ◽  
Ice Fraction

Abstract. Clouds present many challenges to climate modelling. To develop and verify the parameterisations needed to allow climate models to represent cloud structure and processes, there is a need for high-quality observations of cloud optical depth from locations around the world. Retrievals of cloud optical depth are obtainable from radiances measured by Aerosol Robotic Network (AERONET) radiometers in “cloud mode” using a two-wavelength retrieval method. However, the method is unable to detect cloud phase, and hence assumes that all of the cloud in a profile is liquid. This assumption has the potential to introduce errors into long-term statistics of retrieved optical depth for clouds that also contain ice. Using a set of idealised cloud profiles we find that, for optical depths above 20, the fractional error in retrieved optical depth is a linear function of the fraction of the optical depth that is due to the presence of ice cloud (“ice fraction”). Clouds that are entirely ice have positive errors with magnitudes of the order of 55 % to 70 %. We derive a simple linear equation that can be used as a correction at AERONET sites where ice fraction can be independently estimated. Using this linear equation, we estimate the magnitude of the error for a set of cloud profiles from five sites of the Atmospheric Radiation Measurement programme. The dataset contains separate retrievals of ice and liquid retrievals; hence ice fraction can be estimated. The magnitude of the error at each location was related to the relative frequencies of occurrence in thick frontal cloud at the mid-latitude sites and of deep convection at the tropical sites – that is, of deep cloud containing both ice and liquid particles. The long-term mean optical depth error at the five locations spans the range 2–4, which we show to be small enough to allow calculation of top-of-atmosphere flux to within 10 % and surface flux to about 15 %.

scholarly journals Radiative forcing bias of simulated surface albedo modifications linked to forest cover changes at northern latitudes

2015 ◽  
Vol 12 (7) ◽  
pp. 2195-2205 ◽  
Author(s):  
R. M. Bright ◽  
G. Myhre ◽  
R. Astrup ◽  
C. Antón-Fernández ◽  
A. H. Strømman
Keyword(s):  
Radiative Forcing ◽  
Surface Albedo ◽  
Forest Cover ◽  
Climate Models ◽  
Open Area ◽  
Data Set ◽  
Radiative Forcings ◽  
Open Forest ◽  
Northern Latitudes ◽  
Analytical Time

Abstract. In the presence of snow, the bias in the prediction of surface albedo by many climate models remains difficult to correct due to the difficulties of separating the albedo parameterizations from those describing snow and vegetation cover and structure. This can be overcome by extracting the albedo parameterizations in isolation, by executing them with observed meteorology and information on vegetation structure, and by comparing the resulting predictions to observations. Here, we employ an empirical data set of forest structure and daily meteorology for three snow cover seasons and for three case regions in boreal Norway to compute and evaluate predicted albedo to those based on daily MODIS retrievals. Forest and adjacent open area albedos are subsequently used to estimate bias in top-of-the-atmosphere (TOA) radiative forcings (RF) from albedo changes (Δα, Open–Forest) connected to land use and land cover changes (LULCC). As expected, given the diversity of approaches by which snow masking by tall-statured vegetation is parameterized, the magnitude and sign of the albedo biases varied considerably for forests. Large biases at the open sites were also detected, which was unexpected given that these sites were snow-covered throughout most of the analytical time period, therefore eliminating potential biases linked to snow-masking parameterizations. Biases at the open sites were mostly positive, exacerbating the strength of vegetation masking effects and hence the simulated LULCC Δα RF. Despite the large biases in both forest and open area albedos by some schemes in some months and years, the mean Δα RF bias over the 3-year period (November–May) was considerably small across models (−2.1 ± 1.04 Wm−2; 21 ± 11%); four of six models had normalized mean absolute errors less than 20%. Identifying systematic sources of the albedo prediction biases proved challenging, although for some schemes clear sources were identified.

scholarly journals A simulation of the global distribution and radiative forcing of soil dust aerosols at the Last Glacial Maximum

2009 ◽  
Vol 9 (9) ◽  
pp. 3061-3073 ◽  
Author(s):  
T. Takemura ◽  
M. Egashira ◽  
K. Matsuzawa ◽  
H. Ichijo ◽  
R. O'ishi ◽  
...  
Keyword(s):  
Last Glacial Maximum ◽  
Radiative Forcing ◽  
Global Distribution ◽  
Present Climate ◽  
Soil Dust ◽  
Radiative Forcings ◽  
Dust Aerosols ◽  
Last Glacial ◽  
The Last Glacial Maximum ◽  
The Last Glacial

Abstract. In this study an integrated simulation of the global distribution and the radiative forcing of soil dust aerosols at the Last Glacial Maximum (LGM) is performed with an aerosol climate model, SPRINTARS. It is compared with another simulation for the present climate condition. The global total emission flux of soil dust aerosols at the LGM is simulated to be about 2.4 times as large as that in the present climate, and the simulated deposition flux is in general agreement with estimations from ice core and marine sediment samplings though it appears to be underestimated over the Antarctic. The calculated direct radiative forcings of soil dust aerosols at the LGM is close to zero at the tropopause and −0.4 W m−2 at the surface. These radiative forcings are about twice as large as those in the present climate. SPRINTARS also includes the microphysical parameterizations of the cloud-aerosol interaction both for liquid water and ice crystals, which affect the radiation budget. The positive radiative forcing from the indirect effect of soil dust aerosols is mainly caused by their properties to act as ice nuclei. This effect is simulated to be smaller (−0.9 W m−2) at the LGM than in the present. It is suggested that atmospheric dust might contribute to the cold climate during the glacial periods both through the direct and indirect effects, relative to the interglacial periods.

scholarly journals The Impact of Recent Forcing and Ocean Heat Uptake Data on Estimates of Climate Sensitivity

2018 ◽  
Vol 31 (15) ◽  
pp. 6051-6071 ◽  
Author(s):  
Nicholas Lewis ◽  
Judith Curry
Keyword(s):  
Climate Sensitivity ◽  
Climate Models ◽  
Temperature Data ◽  
Historical Period ◽  
Climate Feedbacks ◽  
Ocean Heat Uptake ◽  
Transient Climate Response ◽  
Surface Temperature Change ◽  
Aerosol Forcing ◽  
The Impact

Energy budget estimates of equilibrium climate sensitivity (ECS) and transient climate response (TCR) are derived based on the best estimates and uncertainty ranges for forcing provided in the IPCC Fifth Assessment Report (AR5). Recent revisions to greenhouse gas forcing and post-1990 ozone and aerosol forcing estimates are incorporated and the forcing data extended from 2011 to 2016. Reflecting recent evidence against strong aerosol forcing, its AR5 uncertainty lower bound is increased slightly. Using an 1869–82 base period and a 2007–16 final period, which are well matched for volcanic activity and influence from internal variability, medians are derived for ECS of 1.50 K (5%–95% range: 1.05–2.45 K) and for TCR of 1.20 K (5%–95% range: 0.9–1.7 K). These estimates both have much lower upper bounds than those from a predecessor study using AR5 data ending in 2011. Using infilled, globally complete temperature data give slightly higher estimates: a median of 1.66 K for ECS (5%–95% range: 1.15–2.7 K) and 1.33 K for TCR (5%–95% range: 1.0–1.9 K). These ECS estimates reflect climate feedbacks over the historical period, assumed to be time invariant. Allowing for possible time-varying climate feedbacks increases the median ECS estimate to 1.76 K (5%–95% range: 1.2–3.1 K), using infilled temperature data. Possible biases from non–unit forcing efficacy, temperature estimation issues, and variability in sea surface temperature change patterns are examined and found to be minor when using globally complete temperature data. These results imply that high ECS and TCR values derived from a majority of CMIP5 climate models are inconsistent with observed warming during the historical period.

scholarly journals A New Method of Comparing Forcing Agents in Climate Models*

2015 ◽  
Vol 28 (20) ◽  
pp. 8203-8218 ◽  
Author(s):  
Ben Kravitz ◽  
Douglas G. MacMartin ◽  
Philip J. Rasch ◽  
Andrew J. Jarvis
Keyword(s):  
Solar Irradiance ◽  
Feedback Loop ◽  
Climate Models ◽  
Climate Model ◽  
Co2 Concentration ◽  
Total Solar Irradiance ◽  
New Method ◽  
Convergence Time ◽  
Radiative Forcings ◽  
Global Mean

Abstract The authors describe a new method of comparing different climate forcing agents (e.g., CO2 concentration, CH4 concentration, and total solar irradiance) in climate models that circumvents many of the difficulties associated with explicit calculations of efficacy. This is achieved by introducing an explicit feedback loop external to a climate model that adjusts one forcing agent to balance another while keeping global-mean surface temperature constant. The convergence time of this feedback loop can be adjusted, allowing for comparisons of forcing agents to be achieved with relatively short simulations. Comparisons between forcing agents are highly linear in concordance with predicted scaling relationships; for example, the global-mean climate response to a doubling of the CO2 concentration is equivalent to that of a 2.1% change in total solar irradiance. This result is independent of the magnitude of the forcing agent (within the range of radiative forcings considered here) and is consistent across two different climate models.

scholarly journals Regional emission metrics for short-lived climate forcers from multiple models

2016 ◽  
Vol 16 (11) ◽  
pp. 7451-7468 ◽  
Author(s):  
Borgar Aamaas ◽  
Terje K. Berntsen ◽  
Jan S. Fuglestvedt ◽  
Keith P. Shine ◽  
Nicolas Bellouin
Keyword(s):  
East Asia ◽  
Radiative Forcing ◽  
Climate Models ◽  
Global Climate ◽  
Climate Impact ◽  
Ozone Precursors ◽  
Direct Forcing ◽  
Rf Values ◽  
Global Temperature Change ◽  
The Impact

Abstract. For short-lived climate forcers (SLCFs), the impact of emissions depends on where and when the emissions take place. Comprehensive new calculations of various emission metrics for SLCFs are presented based on radiative forcing (RF) values calculated in four different (chemical-transport or coupled chemistry–climate) models. We distinguish between emissions during summer (May–October) and winter (November–April) for emissions in Europe and East Asia, as well as from the global shipping sector and global emissions. The species included in this study are aerosols and aerosol precursors (BC, OC, SO2, NH3), as well as ozone precursors (NOx, CO, VOCs), which also influence aerosols to a lesser degree. Emission metrics for global climate responses of these emissions, as well as for CH4, have been calculated using global warming potential (GWP) and global temperature change potential (GTP), based on dedicated RF simulations by four global models. The emission metrics include indirect cloud effects of aerosols and the semi-direct forcing for BC. In addition to the standard emission metrics for pulse and sustained emissions, we have also calculated a new emission metric designed for an emission profile consisting of a ramping period of 15 years followed by sustained emissions, which is more appropriate for a gradual implementation of mitigation policies.For the aerosols, the emission metric values are larger in magnitude for emissions in Europe than East Asia and for summer than winter. A variation is also observed for the ozone precursors, with largest values for emissions in East Asia and winter for CO and in Europe and summer for VOCs. In general, the variations between the emission metrics derived from different models are larger than the variations between regions and seasons, but the regional and seasonal variations for the best estimate also hold for most of the models individually. Further, the estimated climate impact of an illustrative mitigation policy package is robust even when accounting for the fact that the magnitude of emission metrics for different species in a given model is correlated. For the ramping emission metrics, the values are generally larger than for pulse or sustained emissions, which holds for all SLCFs. For SLCFs mitigation policies, the dependency of metric values on the region and season of emission should be considered.

scholarly journals Evaluation of the impacts of climate variability on rainfed maize production over the Wami-Ruvu basin of Tanzania

2017 ◽  
Vol 9 (1) ◽  
pp. 207-222 ◽  
Author(s):  
Philbert Luhunga
Keyword(s):  
Climate Variability ◽  
Climate Models ◽  
Pearson Correlation ◽  
Regional Climate ◽  
Maximum Temperature ◽  
Climate Projections ◽  
Historical Climate ◽  
Climate Simulations ◽  
Maize Yields ◽  
The Impact

AbstractIn this study, the impact of inter-seasonal climate variability on rainfed maize (Zea mays) production over the Wami-Ruvu basin of Tanzania is evaluated. Daily high-resolution climate simulations from the Coordinated Regional Climate Downscaling Experiment_Regional Climate Models (CORDEX_RCMs) are used to drive the Decision Support System for Agro-technological Transfer (DSSAT) to simulate maize yields. Climate simulations for the base period of 35 years (1971–2005) are used to drive DSSAT to simulate maize yields during the historical climate. On the other hand, climate projections for the period 2010–2039 (current), 2040–2069 (mid), and 2070–2099 centuries for two Representative Concentration Pathway (RCP45 and 85) emission scenarios are used to drive DSSAT to simulate maize yields in respective centuries. Statistical approaches based on Pearson correlation coefficient and the coefficients of determination are used in the analysis. Results show that rainfall, maximum temperature, and solar radiation are the most important climate variables that determine variation in rainfed maize yields over the Wami-Ruvu basin of Tanzania. They explain the variability in maize yields in historical climate condition (1971–2005), present century under RCP 4.5, and mid and end centuries under both RCP 4.5 and RCP 8.5.

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