scholarly journals Persisting volcanic ash particles impact stratospheric SO2 lifetime and aerosol optical properties

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Yunqian Zhu ◽  
Owen B. Toon ◽  
Eric J. Jensen ◽  
Charles G. Bardeen ◽  
Michael J. Mills ◽  
...  
Keyword(s):  
Optical Properties ◽  
Volcanic Ash ◽  
Climate Model ◽  
Atmospheric Lifetime ◽  
Stratospheric Chemistry ◽  
Sulfur Chemistry ◽  
Climate Simulations ◽  
Volcanic Cloud ◽  
Climate Model Simulations ◽  
The Impact

Abstract Volcanic ash is often neglected in climate simulations because ash particles are assumed to have a short atmospheric lifetime, and to not participate in sulfur chemistry. After the Mt. Kelut eruption in 2014, stratospheric ash-rich aerosols were observed for months. Here we show that the persistence of super-micron ash is consistent with a density near 0.5 g cm−3, close to pumice. Ash-rich particles dominate the volcanic cloud optical properties for the first 60 days. We also find that the initial SO2 lifetime is determined by SO2 uptake on ash, rather than by reaction with OH as commonly assumed. About 43% more volcanic sulfur is removed from the stratosphere in 2 months with the SO2 heterogeneous chemistry on ash particles than without. This research suggests the need for re-evaluation of factors controlling SO2 lifetime in climate model simulations, and of the impact of volcanic ash on stratospheric chemistry and radiation.

Future changes in heatwaves over Africa at the convection-permitting scale

2021 ◽  
Author(s):  
Cathryn Birch ◽  
Lawrence Jackson ◽  
Declan Finney ◽  
John Marsham ◽  
Rachel Stratton ◽  
...  
Keyword(s):  
Climate Model ◽  
Daily Rainfall ◽  
Shortwave Radiation ◽  
Daily Maximum ◽  
Future Change ◽  
Driving Mechanisms ◽  
The Future ◽  
Convective Scale ◽  
Climate Model Simulations ◽  
The Impact

<p>Mean temperatures and their extremes have increased over Africa since the latter half of the 20th century and this trend is projected to continue, with very frequent, intense and often deadly heatwaves likely to occur very regularly over much of Africa by 2100. It is crucial that we understand the scale of the future increases in extremes and the driving mechanisms. We diagnose daily maximum wet bulb temperature heatwaves, which allows for both the impact of temperature and humidity, both critical for human health and survivability. During wet bulb heatwaves, humidity and cloud cover increase, which limits the surface shortwave radiation flux but increases longwave warming. It is found from observations and ERA5 reanalysis that approximately 30% of wet bulb heatwaves over Africa are associated with daily rainfall accumulations of more than 1 mm/day on the first day of the heatwave. The first ever pan-African convection-permitting climate model simulations of present-day and RCP8.5 future climate are utilised to illustrate the projected future change in heatwaves, their drivers and their sensitivity to the representation of convection. Compared to ERA5, the convection-permitting model better represents the frequency and magnitude of present-day wet bulb heatwaves than a version of the model with more traditional parameterised convection. The future change in heatwave frequency, duration and magnitude is also larger in the convective-scale simulation, suggesting CMIP-style models may underestimate the future change in wet bulb heat extremes over Africa. The main reason for the larger future change appears to be the ability of the model to produce larger anomalies relative to its climatology in precipitation, cloud and the surface energy balance.</p>

scholarly journals Influence of parallel computational uncertainty on simulations of the Coupled General Climate Model

2012 ◽  
Vol 5 (2) ◽  
pp. 313-319 ◽  
Author(s):  
Z. Song ◽  
F. Qiao ◽  
X. Lei ◽  
C. Wang
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Quality Standard ◽  
Ensemble Member ◽  
Climate System ◽  
Climate System Model ◽  
Climate Simulations ◽  
Computational Uncertainty ◽  
The Impact ◽  
General Climate

Abstract. This paper investigates the impact of the parallel computational uncertainty due to the round-off error on climate simulations using the Community Climate System Model Version 3 (CCSM3). A series of sensitivity experiments have been conducted and the analyses are focused on the Global and Nino3.4 average sea surface temperatures (SST). For the monthly time series, it is shown that the amplitude of the deviation induced by the parallel computational uncertainty is the same order as that of the climate system change. However, the ensemble mean method can reduce the influence and the ensemble member number of 15 is enough to ignore the uncertainty. For climatology, the influence can be ignored when the climatological mean is calculated by using more than 30-yr simulations. It is also found that the parallel computational uncertainty has no distinguishable effect on power spectrum analysis of climate variability such as ENSO. Finally, it is suggested that the influence of the parallel computational uncertainty on Coupled General Climate Models (CGCMs) can be a quality standard or a metric for developing CGCMs.

scholarly journals On the Choice of Ensemble Mean for Estimating the Forced Signal in the Presence of Internal Variability

2018 ◽  
Vol 31 (14) ◽  
pp. 5681-5693 ◽  
Author(s):  
Leela M. Frankcombe ◽  
Matthew H. England ◽  
Jules B. Kajtar ◽  
Michael E. Mann ◽  
Byron A. Steinman
Keyword(s):  
Regional Differences ◽  
Climate Model ◽  
Surface Air Temperature ◽  
Internal Variability ◽  
Single Model ◽  
Sea Level Pressure ◽  
Model Simulations ◽  
Ensemble Mean ◽  
Climate Model Simulations ◽  
The Impact

Abstract In this paper we examine various options for the calculation of the forced signal in climate model simulations, and the impact these choices have on the estimates of internal variability. We find that an ensemble mean of runs from a single climate model [a single model ensemble mean (SMEM)] provides a good estimate of the true forced signal even for models with very few ensemble members. In cases where only a single member is available for a given model, however, the SMEM from other models is in general out-performed by the scaled ensemble mean from all available climate model simulations [the multimodel ensemble mean (MMEM)]. The scaled MMEM may therefore be used as an estimate of the forced signal for observations. The MMEM method, however, leads to increasing errors further into the future, as the different rates of warming in the models causes their trajectories to diverge. We therefore apply the SMEM method to those models with a sufficient number of ensemble members to estimate the change in the amplitude of internal variability under a future forcing scenario. In line with previous results, we find that on average the surface air temperature variability decreases at higher latitudes, particularly over the ocean along the sea ice margins, while variability in precipitation increases on average, particularly at high latitudes. Variability in sea level pressure decreases on average in the Southern Hemisphere, while in the Northern Hemisphere there are regional differences.

scholarly journals A pragmatic approach for the downscaling and bias correction of regional climate simulations – evaluation in hydrological modeling

2011 ◽  
Vol 4 (1) ◽  
pp. 45-63 ◽  
Author(s):  
T. Marke ◽  
W. Mauser ◽  
A. Pfeiffer ◽  
G. Zängl
Keyword(s):  
Hydrological Modeling ◽  
Hydrological Model ◽  
Climate Model ◽  
Regional Climate ◽  
Model Performance ◽  
Reanalysis Data ◽  
Historical Period ◽  
Climate Simulations ◽  
Meteorological Observations ◽  
Climate Model Simulations

Abstract. The present study investigates a statistical approach for the downscaling of climate simulations focusing on those meteorological parameters most commonly required as input for climate change impact models (temperature, precipitation, air humidity and wind speed), including the option to correct biases in the climate model simulations. The approach is evaluated by the utilization of a hydrometeorological model chain consisting of (i) the regional climate model MM5 (driven by reanalysis data at the boundaries of the model domain), (ii) the downscaling and model interface SCALMET, and (iii) the hydrological model PROMET. The results of four hydrological model runs are compared to discharge recordings at the gauge of the Upper Danube Watershed (Central Europe) for the historical period of 1972–2000 on a daily time basis. The comparison reveals that the presented approaches allow for a more accurate simulation of discharge for the catchment of the Upper Danube Watershed and the considered gauge at the outlet in Achleiten. The correction for subgrid-scale variability is shown to reduce biases in simulated discharge compared to the utilization of bilinear interpolation. Further enhancements in model performance could be achieved by a correction of biases in the RCM data within the downscaling process. Although the presented downscaling approach strongly improves the performance of the hydrological model, deviations from the observed discharge conditions persist that are not found when driving the hydrological model with spatially distributed meteorological observations.

scholarly journals A multi-model ensemble method that combines imperfect models through learning

2011 ◽  
Vol 2 (1) ◽  
pp. 161-177 ◽  
Author(s):  
L. A. van den Berge ◽  
F. M. Selten ◽  
W. Wiegerinck ◽  
G. S. Duane
Keyword(s):  
Climate Model ◽  
Model Ensemble ◽  
Promising Strategy ◽  
Climate Simulations ◽  
Weather And Climate ◽  
Standard Parameter ◽  
Climate Model Simulations ◽  
Model Equations ◽  
Parameter Values ◽  
Better Than

Abstract. In the current multi-model ensemble approach climate model simulations are combined a posteriori. In the method of this study the models in the ensemble exchange information during simulations and learn from historical observations to combine their strengths into a best representation of the observed climate. The method is developed and tested in the context of small chaotic dynamical systems, like the Lorenz 63 system. Imperfect models are created by perturbing the standard parameter values. Three imperfect models are combined into one super-model, through the introduction of connections between the model equations. The connection coefficients are learned from data from the unperturbed model, that is regarded as the truth. The main result of this study is that after learning the super-model is a very good approximation to the truth, much better than each imperfect model separately. These illustrative examples suggest that the super-modeling approach is a promising strategy to improve weather and climate simulations.

scholarly journals Trends in Downward Solar Radiation at the Surface over North America from Climate Model Projections and Implications for Solar Energy

2015 ◽  
Vol 2015 ◽  
pp. 1-7 ◽  
Author(s):  
Gerardo Andres Saenz ◽  
Huei-Ping Huang
Keyword(s):  
United States ◽  
North America ◽  
Solar Radiation ◽  
Solar Energy ◽  
Climate Model ◽  
Global Climate Model ◽  
The United States ◽  
Model Simulations ◽  
Climate Model Simulations ◽  
The Impact

The projected changes in the downward solar radiation at the surface over North America for late 21st century are deduced from global climate model simulations with greenhouse-gas (GHG) forcing. A robust trend is found in winter over the United States, which exhibits a simple pattern of a decrease of sunlight over Northern USA. and an increase of sunlight over Southern USA. This structure was identified in both the seasonal mean and the mean climatology at different times of the day. It is broadly consistent with the known poleward shift of storm tracks in winter in climate model simulations with GHG forcing. The centennial trend of the downward shortwave radiation at the surface in Northern USA. is on the order of 10% of the climatological value for the January monthly mean, and slightly over 10% at the time when it is midday in the United States. This indicates a nonnegligible influence of the GHG forcing on solar energy in the long term. Nevertheless, when dividing the 10% by a century, in the near term, the impact of the GHG forcing is relatively minor such that the estimate of solar power potential using present-day climatology will remain useful in the coming decades.

scholarly journals Estimating design hydrologic extremes in a warming climate: alternatives, uncertainties and the way forward

2021 ◽  
Vol 379 (2195) ◽  
pp. 20190623 ◽  
Author(s):  
Ashish Sharma ◽  
Suresh Hettiarachchi ◽  
Conrad Wasko
Keyword(s):  
Climate Model ◽  
Flash Flood ◽  
Design Guidelines ◽  
Design Flood ◽  
The Future ◽  
Flood Magnitude ◽  
Urban Catchments ◽  
Climate Model Simulations ◽  
Hydrologic Design ◽  
The Impact

It is now well established that our warming planet is experiencing changes in extreme storms and floods, resulting in a need to better specify hydrologic design guidelines that can be projected into the future. This paper attempts to summarize the nature of changes occurring and the impact they are having on the design flood magnitude, with a focus on the urban catchments that we will increasingly reside in as time goes on. Two lines of reasoning are used to assess and model changes in design hydrology. The first of these involves using observed storms and soil moisture conditions and projecting how these may change into the future. The second involves using climate model simulations of the future and using them as inputs into hydrologic models to assess the changed design estimates. We discuss here the limitations in both and suggest that the two are, in fact, linked, as climate model projections for the future are needed in the first approach to form meaningful projections for the future. Based on the author's experience with both lines of reasoning, this invited commentary presents a theoretical narrative linking these two and identifying factors and assumptions that need to be validated before implementation in practice. This article is part of a discussion meeting issue ‘Intensification of short-duration rainfall extremes and implications for flash flood risks’.

scholarly journals Decline in Terrestrial Moisture Sources of the Mississippi River Basin in a Future Climate

2020 ◽  
Vol 21 (2) ◽  
pp. 299-316 ◽  
Author(s):  
Imme Benedict ◽  
Chiel C. van Heerwaarden ◽  
Ruud J. van der Ent ◽  
Albrecht H. Weerts ◽  
Wilco Hazeleger
Keyword(s):  
River Basin ◽  
Mississippi River ◽  
Climate Model ◽  
Low Frequency ◽  
Future Climate ◽  
Mississippi River Basin ◽  
Moisture Source ◽  
Moisture Sources ◽  
Climate Model Simulations ◽  
The Impact

AbstractAssessment of the impact of climate change on water resources over land requires knowledge on the origin of the precipitation and changes therein toward the future. We determine the origin of precipitation over the Mississippi River basin (MRB) using high-resolution (~25 km) climate model simulations for present and future climate (RCP4.5). Moisture resulting in precipitation over the MRB is tracked back in time using Eulerian offline moisture tracking, in order to find out from where this water originally evaporated (i.e., the moisture sources). We find that the most important continental moisture sources are the MRB itself and the area southwest of the basin. The two most relevant oceanic sources are the Gulf of Mexico/Caribbean and the Pacific. The distribution of sources varies per season, with more recycling of moisture within the basin during summer and more transport of moisture from the ocean toward the basin in winter. In future winters, we find an increase in moisture source from the oceans (related to higher sea surface temperatures), resulting in more precipitation over the MRB. In future summers, we find an approximately 5% decrease in moisture source from the basin itself, while the decrease in precipitation is smaller (i.e., lower recycling ratios). The results here are based on one climate model, and we do not study low-frequency climate variability. We conclude that Mississippi’s moisture sources will become less local in a future climate, with more water originating from the oceans.

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