scholarly journals Hydrological Excitations of Polar Motion Derived from Different Variables of Fgoals − g2 Climate Model

2016 ◽  
Vol 51 (4) ◽  
pp. 107-122
Author(s):  
M. Winska
Keyword(s):  
Polar Motion ◽  
Climate Models ◽  
Climate Model ◽  
Grid Point ◽  
Global Ocean ◽  
Data Set ◽  
Excitation Functions ◽  
Geophysical Excitation ◽  
Grace Data ◽  
Hydrological Angular Momentum

Abstract The hydrological contribution to decadal, inter-annual and multi-annual suppress polar motion derived from climate model as well as from GRACE (Gravity Recovery and Climate Experiment) data is discussed here for the period 2002.3-2016.0. The data set used here are Earth Orientation Parameters Combined 04 (EOP C04), Flexible Global Ocean-Atmosphere-Land System Model: Grid-point Version 2 (FGOAL-g2) and Global Land Data Assimilation System (GLDAS) climate models and GRACE CSR RL05 data for polar motion, hydrological and gravimetric excitation, respectively. Several Hydrological Angular Momentum (HAM) functions are calculated here from the selected variables: precipitation, evaporation, runoff, soil moisture, accumulated snow of the FGOALS and GLDAS climate models as well as from the global mass change fields from GRACE data provided by the International Earth Rotation and Reference System Service (IERS) Global Geophysical Fluids Center (GGFC). The contribution of different HAM excitation functions to achieve the full agreement between geodetic observations and geophysical excitation functions of polar motion is studied here.

Comparison between polar motion excitation functions estimated from recent geophysical models and observations

2021 ◽  
Author(s):  
Małgorzata Wińska ◽  
Justyna Śliwińska ◽  
Jolanta Nastula
Keyword(s):  
Angular Momentum ◽  
Polar Motion ◽  
Climate Models ◽  
Discrete Wavelet ◽  
Excitation Functions ◽  
Geophysical Excitation ◽  
Terrestrial Water ◽  
Hydrological Angular Momentum ◽  
Complex Morlet Wavelet ◽  
Project Data

<p>Continental hydrological loading by land water, snow, and ice is a process that influences the Earth’s inertia tensor and is very important for full understanding of the excitation of polar motion. In this study, the hydrological contribution to decadal, inter-annual and multi-annual suppress polar motion derived from different GRACE (Gravity Recovery and Climate Experiment) solutions as well as from SLR (Satellite Laser Ranging) and some climate models from CMIP6 project data is discussed here.</p><p>The main aim of this study is to show the influence of different representations of hydrological angular momentum (HAM) coming from different GRACE (mas concentration solutions - mascons, Terrestrial Water Storage changes, and Stokes Coefficients), SLR, and climate models solutions on agreement between Geodetic Angular Momentum (GAM) and geophysical excitations of polar motion been a sum of Atmospheric, Oceanic and Hydrological Angular Momentum (AAM+OAM+HAM) in different spectral bands.</p><p>To do that, the geodetic and geophysical excitation functions are transformed into time-scale domain using the discrete wavelet transform based on the Complex Morlet wavelet functions. Next, the time series (GAM vs. geophysical ones) are compared in terms of semblance filtering, on the basis of their phase, as a function of frequency, and amplitude information of their cross-wavelet power.</p><p>Here, we would like to present the consistency between full polar motion excitations and geophysical fluids,  that are the sum of AAM  (pressure + wind), OAM  (bottom pressure +  currents), and HAM contributions. This analysis could let us indicate, which hydrological representation of different HAM solutions cause the biggest errors in the geodetic budget.</p>

scholarly journals Fidelity of the Observational/Reanalysis Datasets and Global Climate Models in Representation of Extreme Precipitation in East China

2018 ◽  
Vol 32 (1) ◽  
pp. 195-212 ◽  
Author(s):  
Sicheng He ◽  
Jing Yang ◽  
Qing Bao ◽  
Lei Wang ◽  
Bin Wang
Keyword(s):  
Extreme Precipitation ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Yangtze River Basin ◽  
Global Climate Model ◽  
Global Climate Models ◽  
Global Ocean ◽  
East China ◽  
Cmip5 Models

AbstractRealistic reproduction of historical extreme precipitation has been challenging for both reanalysis and global climate model (GCM) simulations. This work assessed the fidelities of the combined gridded observational datasets, reanalysis datasets, and GCMs [CMIP5 and the Chinese Academy of Sciences Flexible Global Ocean–Atmospheric Land System Model–Finite-Volume Atmospheric Model, version 2 (FGOALS-f2)] in representing extreme precipitation over East China. The assessment used 552 stations’ rain gauge data as ground truth and focused on the probability distribution function of daily precipitation and spatial structure of extreme precipitation days. The TRMM observation displays similar rainfall intensity–frequency distributions as the stations. However, three combined gridded observational datasets, four reanalysis datasets, and most of the CMIP5 models cannot capture extreme precipitation exceeding 150 mm day−1, and all underestimate extreme precipitation frequency. The observed spatial distribution of extreme precipitation exhibits two maximum centers, located over the lower-middle reach of Yangtze River basin and the deep South China region, respectively. Combined gridded observations and JRA-55 capture these two centers, but ERA-Interim, MERRA, and CFSR and almost all CMIP5 models fail to capture them. The percentage of extreme rainfall in the total rainfall amount is generally underestimated by 25%–75% in all CMIP5 models. Higher-resolution models tend to have better performance, and physical parameterization may be crucial for simulating correct extreme precipitation. The performances are significantly improved in the newly released FGOALS-f2 as a result of increased resolution and a more realistic simulation of moisture and heating profiles. This work pinpoints the common biases in the combined gridded observational datasets and reanalysis datasets and helps to improve models’ simulation of extreme precipitation, which is critically important for reliable projection of future changes in extreme precipitation.

scholarly journals Atmospheric removal times of the aerosol-bound radionuclides <sup>137</sup>Cs and <sup>131</sup>I measured after the Fukushima Dai-ichi nuclear accident – a constraint for air quality and climate models

2012 ◽  
Vol 12 (22) ◽  
pp. 10759-10769 ◽  
Author(s):  
N. I. Kristiansen ◽  
A. Stohl ◽  
G. Wotawa
Keyword(s):  
Air Quality ◽  
Dry Deposition ◽  
Nuclear Power ◽  
Climate Models ◽  
Climate Model ◽  
Noble Gas ◽  
Measurement Data ◽  
Radioactive Decay ◽  
Data Set ◽  
Removal Time

Abstract. Caesium-137 (137Cs) and iodine-131 (131I) are radionuclides of particular concern during nuclear accidents, because they are emitted in large amounts and are of significant health impact. 137Cs and 131I attach to the ambient accumulation-mode (AM) aerosols and share their fate as the aerosols are removed from the atmosphere by scavenging within clouds, precipitation and dry deposition. Here, we estimate their removal times from the atmosphere using a unique high-precision global measurement data set collected over several months after the accident at the Fukushima Dai-ichi nuclear power plant in March 2011. The noble gas xenon-133 (133Xe), also released during the accident, served as a passive tracer of air mass transport for determining the removal times of 137Cs and 131I via the decrease in the measured ratios 137Cs/133Xe and 131I/133Xe over time. After correction for radioactive decay, the 137Cs/133Xe ratios reflect the removal of aerosols by wet and dry deposition, whereas the 131I/133Xe ratios are also influenced by aerosol production from gaseous 131I. We find removal times for 137Cs of 10.0–13.9 days and for 131I of 17.1–24.2 days during April and May 2011. The removal time of 131I is longer due to the aerosol production from gaseous 131I, thus the removal time for 137Cs serves as a better estimate for aerosol lifetime. The removal time of 131I is of interest for semi-volatile species. We discuss possible caveats (e.g. late emissions, resuspension) that can affect the results, and compare the 137Cs removal times with observation-based and modeled aerosol lifetimes. Our 137Cs removal time of 10.0–13.9 days should be representative of a "background" AM aerosol well mixed in the extratropical Northern Hemisphere troposphere. It is expected that the lifetime of this vertically mixed background aerosol is longer than the lifetime of fresh AM aerosols directly emitted from surface sources. However, the substantial difference to the mean lifetimes of AM aerosols obtained from aerosol models, typically in the range of 3–7 days, warrants further research on the cause of this discrepancy. Too short modeled AM aerosol lifetimes would have serious implications for air quality and climate model predictions.

scholarly journals Sources of Uncertainty in Future Projections of the Carbon Cycle

2016 ◽  
Vol 29 (20) ◽  
pp. 7203-7213 ◽  
Author(s):  
Alan J. Hewitt ◽  
Ben B. B. Booth ◽  
Chris D. Jones ◽  
Eddy S. Robertson ◽  
Andy J. Wiltshire ◽  
...  
Keyword(s):  
Carbon Cycle ◽  
Climate Models ◽  
Climate Model ◽  
Initial Conditions ◽  
Carbon Fluxes ◽  
Global Ocean ◽  
Lead Times ◽  
Carbon Uptake ◽  
The North ◽  
Ocean Carbon

Abstract The inclusion of carbon cycle processes within CMIP5 Earth system models provides the opportunity to explore the relative importance of differences in scenario and climate model representation to future land and ocean carbon fluxes. A two-way analysis of variance (ANOVA) approach was used to quantify the variability owing to differences between scenarios and between climate models at different lead times. For global ocean carbon fluxes, the variance attributed to differences between representative concentration pathway scenarios exceeds the variance attributed to differences between climate models by around 2025, completely dominating by 2100. This contrasts with global land carbon fluxes, where the variance attributed to differences between climate models continues to dominate beyond 2100. This suggests that modeled processes that determine ocean fluxes are currently better constrained than those of land fluxes; thus, one can be more confident in linking different future socioeconomic pathways to consequences of ocean carbon uptake than for land carbon uptake. The contribution of internal variance is negligible for ocean fluxes and small for land fluxes, indicating that there is little dependence on the initial conditions. The apparent agreement in atmosphere–ocean carbon fluxes, globally, masks strong climate model differences at a regional level. The North Atlantic and Southern Ocean are key regions, where differences in modeled processes represent an important source of variability in projected regional fluxes.

scholarly journals Climate Modelling in Low Precision: Effects of Both Deterministic & Stochastic Rounding.

2021 ◽  
pp. 1-43
Author(s):  
E. Adam Paxton ◽  
Matthew Chantry ◽  
Milan Klöwer ◽  
Leo Saffin ◽  
Tim Palmer
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Weather Forecasting ◽  
Stress Test ◽  
Grid Point ◽  
Atmospheric Model ◽  
Extreme Weather Events ◽  
Climate Modelling ◽  
Double Precision ◽  
Rounding Error

AbstractMotivated by recent advances in operational weather forecasting, we study the efficacy of low-precision arithmetic for climate simulations. We develop a framework to measure rounding error in a climate model which provides a stress-test for a low-precision version of the model, and we apply our method to a variety of models including the Lorenz system; a shallow water approximation for ow over a ridge; and a coarse resolution spectral global atmospheric model with simplified parameterisations (SPEEDY). Although double precision (52 significant bits) is standard across operational climate models, in our experiments we find that single precision (23 sbits) is more than enough and that as low as half precision (10 sbits) is often sufficient. For example, SPEEDY can be run with 12 sbits across the code with negligible rounding error, and with 10 sbits if minor errors are accepted, amounting to less than 0.1 mm/6hr for average grid-point precipitation, for example. Our test is based on the Wasserstein metric and this provides stringent non-parametric bounds on rounding error accounting for annual means as well as extreme weather events. In addition, by testing models using both round-to-nearest (RN) and stochastic rounding (SR) we find that SR can mitigate rounding error across a range of applications, and thus our results also provide some evidence that SR could be relevant to next-generation climate models. Further research is needed to test if our results can be generalised to higher resolutions and alternative numerical schemes. However, the results open a promising avenue towards the use of low-precision hardware for improved climate modelling.

Evaluation of land water storage prediction skill in CMIP5 decadal hindcasts by means of a GRACE-based data set

2020 ◽  
Author(s):  
Laura Jensen ◽  
Annette Eicker ◽  
Tobias Stacke ◽  
Henryk Dobslaw
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Water Storage ◽  
Cmip5 Models ◽  
Climate Projections ◽  
Terrestrial Water Storage ◽  
Data Set ◽  
Model Experiments ◽  
Terrestrial Water ◽  
Decadal Predictions

&lt;p&gt;Reliable predictions of terrestrial water storage (TWS) changes for the next couple of years would be extremely valuable for, e.g., agriculture and water management. In contrast to long-term projections of future climate conditions, so-called decadal predictions do not depend on prescribed CO&lt;sub&gt;2 &lt;/sub&gt;scenarios but provide unconditional forecasts similar to numerical weather models. Therefore, opposed to climate projections, decadal predictions (or hindcasts, if run for the past) can directly be compared to observations. Here, we evaluate decadal hindcasts of TWS related variables from an ensemble of 5 coupled CMIP5 climate models against a TWS data set based on GRACE satellite observations.&lt;/p&gt; &lt;p&gt;Since data from the CMIP5 models and GRACE is jointly available in only 9 years, we access a GRACE-like reconstruction of TWS derived from precipitation and temperature data sets (Humphrey and Gudmundsson, 2019), which expands the analysis time-frame to 41 years. The skill of the decadal hindcasts is assessed by means of anomaly correlations and root-mean-square deviations (RMSD) for the yearly global average and aggregated over different climate zones. Furthermore, we compute global maps of correlation and RMSD.&lt;/p&gt; &lt;p&gt;We find that at least for the first two prediction years the decadal model experiments clearly outperform the classical climate projections, regionally even for the third year. We can thereby demonstrate that the observation type &amp;#8220;terrestrial water storage&amp;#8221; as available from the GRACE and GRACE-FO missions is suitable as additional data set in the validation and/or calibration of climate model experiments.&lt;/p&gt;

scholarly journals Mid-to-late Holocene temperature evolution and atmospheric dynamics over Europe in regional model simulations

2016 ◽  
Vol 12 (8) ◽  
pp. 1645-1662 ◽  
Author(s):  
Emmanuele Russo ◽  
Ulrich Cubasch
Keyword(s):  
Climate Change ◽  
High Resolution ◽  
Late Holocene ◽  
Climate Models ◽  
Climate Model ◽  
Set Covering ◽  
Data Set ◽  
Near Surface ◽  
Past Climate ◽  
Past Climate Change

Abstract. The improvement in resolution of climate models has always been mentioned as one of the most important factors when investigating past climatic conditions, especially in order to evaluate and compare the results against proxy data. Despite this, only a few studies have tried to directly estimate the possible advantages of highly resolved simulations for the study of past climate change. Motivated by such considerations, in this paper we present a set of high-resolution simulations for different time slices of the mid-to-late Holocene performed over Europe using the state-of-the-art regional climate model COSMO-CLM. After proposing and testing a model configuration suitable for paleoclimate applications, the aforementioned mid-to-late Holocene simulations are compared against a new pollen-based climate reconstruction data set, covering almost all of Europe, with two main objectives: testing the advantages of high-resolution simulations for paleoclimatic applications, and investigating the response of temperature to variations in the seasonal cycle of insolation during the mid-to-late Holocene. With the aim of giving physically plausible interpretations of the mismatches between model and reconstructions, possible uncertainties of the pollen-based reconstructions are taken into consideration. Focusing our analysis on near-surface temperature, we can demonstrate that concrete advantages arise in the use of highly resolved data for the comparison against proxy-reconstructions and the investigation of past climate change. Additionally, our results reinforce previous findings showing that summertime temperatures during the mid-to-late Holocene were driven mainly by changes in insolation and that the model is too sensitive to such changes over Southern Europe, resulting in drier and warmer conditions. However, in winter, the model does not correctly reproduce the same amplitude of changes evident in the reconstructions, even if it captures the main pattern of the pollen data set over most of the domain for the time periods under investigation. Through the analysis of variations in atmospheric circulation we suggest that, even though the wintertime discrepancies between the two data sets in some areas are most likely due to high pollen uncertainties, in general the model seems to underestimate the changes in the amplitude of the North Atlantic Oscillation, overestimating the contribution of secondary modes of variability.

scholarly journals High-end climate change impact on European runoff and low flows – exploring the effects of forcing biases

2016 ◽  
Vol 20 (5) ◽  
pp. 1785-1808 ◽  
Author(s):  
Lamprini V. Papadimitriou ◽  
Aristeidis G. Koutroulis ◽  
Manolis G. Grillakis ◽  
Ioannis K. Tsanis
Keyword(s):  
Global Warming ◽  
Bias Correction ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Data Set ◽  
Low Flows ◽  
The Impact ◽  
Selection Of

Abstract. Climate models project a much more substantial warming than the 2 °C target under the more probable emission scenarios, making higher-end scenarios increasingly plausible. Freshwater availability under such conditions is a key issue of concern. In this study, an ensemble of Euro-CORDEX projections under RCP8.5 is used to assess the mean and low hydrological states under +4 °C of global warming for the European region. Five major European catchments were analysed in terms of future drought climatology and the impact of +2 °C versus +4 °C global warming was investigated. The effect of bias correction of the climate model outputs and the observations used for this adjustment was also quantified. Projections indicate an intensification of the water cycle at higher levels of warming. Even for areas where the average state may not considerably be affected, low flows are expected to reduce, leading to changes in the number of dry days and thus drought climatology. The identified increasing or decreasing runoff trends are substantially intensified when moving from the +2 to the +4° of global warming. Bias correction resulted in an improved representation of the historical hydrology. It is also found that the selection of the observational data set for the application of the bias correction has an impact on the projected signal that could be of the same order of magnitude to the selection of the Global Climate Model (GCM).

scholarly journals Tropospheric ozone in CCMI models and Gaussian process emulation to understand biases in the SOCOLv3 chemistry–climate model

2018 ◽  
Vol 18 (21) ◽  
pp. 16155-16172 ◽  
Author(s):  
Laura E. Revell ◽  
Andrea Stenke ◽  
Fiona Tummon ◽  
Aryeh Feinberg ◽  
Eugene Rozanov ◽  
...  
Keyword(s):  
Gaussian Process ◽  
Atmospheric Chemistry ◽  
Tropospheric Ozone ◽  
Climate Models ◽  
Climate Model ◽  
Coupled Model ◽  
Ozone Monitoring Instrument ◽  
Data Set ◽  
Gaussian Process Emulation ◽  
Column Ozone

Abstract. Previous multi-model intercomparisons have shown that chemistry–climate models exhibit significant biases in tropospheric ozone compared with observations. We investigate annual-mean tropospheric column ozone in 15 models participating in the SPARC–IGAC (Stratosphere–troposphere Processes And their Role in Climate–International Global Atmospheric Chemistry) Chemistry-Climate Model Initiative (CCMI). These models exhibit a positive bias, on average, of up to 40 %–50 % in the Northern Hemisphere compared with observations derived from the Ozone Monitoring Instrument and Microwave Limb Sounder (OMI/MLS), and a negative bias of up to ∼30 % in the Southern Hemisphere. SOCOLv3.0 (version 3 of the Solar-Climate Ozone Links CCM), which participated in CCMI, simulates global-mean tropospheric ozone columns of 40.2 DU – approximately 33 % larger than the CCMI multi-model mean. Here we introduce an updated version of SOCOLv3.0, “SOCOLv3.1”, which includes an improved treatment of ozone sink processes, and results in a reduction in the tropospheric column ozone bias of up to 8 DU, mostly due to the inclusion of N2O5 hydrolysis on tropospheric aerosols. As a result of these developments, tropospheric column ozone amounts simulated by SOCOLv3.1 are comparable with several other CCMI models. We apply Gaussian process emulation and sensitivity analysis to understand the remaining ozone bias in SOCOLv3.1. This shows that ozone precursors (nitrogen oxides (NOx), carbon monoxide, methane and other volatile organic compounds, VOCs) are responsible for more than 90 % of the variance in tropospheric ozone. However, it may not be the emissions inventories themselves that result in the bias, but how the emissions are handled in SOCOLv3.1, and we discuss this in the wider context of the other CCMI models. Given that the emissions data set to be used for phase 6 of the Coupled Model Intercomparison Project includes approximately 20 % more NOx than the data set used for CCMI, further work is urgently needed to address the challenges of simulating sub-grid processes of importance to tropospheric ozone in the current generation of chemistry–climate models.

scholarly journals Atmospheric removal times of the aerosol-bound radionuclides <sup>137</sup>Cs and <sup>131</sup>I during the months after the Fukushima Dai-ichi nuclear power plant accident – a constraint for air quality and climate models

2012 ◽  
Vol 12 (5) ◽  
pp. 12331-12356
Author(s):  
N. I. Kristiansen ◽  
A. Stohl ◽  
G. Wotawa
Keyword(s):  
Air Quality ◽  
Power Plant ◽  
Nuclear Power Plant ◽  
Dry Deposition ◽  
Nuclear Power ◽  
Climate Models ◽  
Climate Model ◽  
Measurement Data ◽  
Radioactive Decay ◽  
Data Set

Abstract. Caesium-137 (137Cs) and iodine-131 (131I) are radionuclides of particular concern during nuclear accidents, because they are emitted in large amounts and are of significant health impact. 137Cs and 131I attach to the ambient accumulation-mode (AM) aerosols and share their fate as the aerosols are removed from the atmosphere by scavenging within clouds, precipitation and dry deposition. Here, we estimate their removal times from the atmosphere using a unique high-precision global measurement data set collected over several months after the accident at the Fukushima Dai-ichi nuclear power plant in March 2011. The noble gas xenon-133 (133Xe), also released during the accident, served as a passive tracer of air mass transport for determining the removal times of 137Cs and 131I via the decrease in the measured ratios 137Cs/133Xe and 131I/133Xe over time. After correction for radioactive decay, the 137Cs/133Xe ratios reflect the removal of aerosols by wet and dry deposition, whereas the 131I/133Xe ratios are also influenced by aerosol production from gaseous 131I. We find removal times for 137Cs of 10.0–13.9 days and for 131I of 17.1–24.2 days during April and May 2011. We discuss possible caveats (e.g. late emissions, resuspension) that can affect the results, and compare the 137Cs removal times with observation-based and modeled aerosol lifetimes. Our 137Cs removal time of 10.0–13.9 days should be representative of a "background" AM aerosol well mixed in the extratropical Northern Hemisphere troposphere. It is expected that the lifetime of this vertically mixed background aerosol is longer than the lifetime of AM aerosols originating from surface sources. However, the substantial difference to the mean lifetimes of AM aerosols obtained from aerosol models, typically in the range of 3–7 days, warrants further research on the cause of this discrepancy. Too short modeled AM aerosol lifetimes would have serious implications for air quality and climate model predictions.

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