scholarly journals The impact of differences in large-scale circulation output from climate models on the regional modeling of ozone and PM

2012 ◽  
Vol 12 (5) ◽  
pp. 12245-12285 ◽  
Author(s):  
A. M. M. Manders ◽  
E. van Meijgaard ◽  
A. C. Mues ◽  
R. Kranenburg ◽  
L. H. van Ulft ◽  
...  
Keyword(s):  
Air Quality ◽  
Climate Models ◽  
Climate Model ◽  
Transport Model ◽  
Global Climate Model ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Climate Simulations ◽  
The Impact

Abstract. Climate change may have an impact on air quality (ozone, particulate matter) due to the strong dependency of air quality on meteorology. The effect is often studied using a global climate model (GCM) to produce meteorological fields that are subsequently used by chemical transport models. However, climate models themselves are subject to large uncertainties and fail to adequately reproduce the present-day climate. The present study illustrates the impact of this uncertainty on air quality. To this end, output from the SRES-A1B constraint transient runs with two GCMs, i.e. ECHAM5 and MIROC-hires, has been dynamically downscaled with the regional climate model RACMO2 and used to force a constant emission run with the chemistry transport model LOTOS-EUROS in a one-way coupled run covering the period 1970–2060. Results from the two climate simulations have been compared with a RACMO2-LOTOS-EUROS (RLE) simulation forced by the ERA-Interim reanalysis for the period 1989–2009. Both RLE_ECHAM and RLE_MIROC showed considerable deviations from RLE_ERA in daily maximum temperature, precipitation and wind speed. Moreover, sign and magnitude of these deviations depended on the region. Differences in average concentrations for the present-day simulations were found of equal to (RLE_MIROC) or even larger than (RLE_ECHAM) the differences in concentration between present-day and future climate (2041–2060). The climate simulations agreed on a future increase in average summer ozone daily maximum concentrations (5–10 μg m−3) in parts of Southern Europe and a smaller increase in Western and Central Europe. Annual average PM10 concentrations increased (0.5–1.0 μg m−3) in North-West Europe and the Po Valley, but these numbers are rather uncertain. Overall, changes for PM10 were small, both positive and negative changes were found, and for many locations the two runs did not agree on the sign of the change. The approach taken here illustrates that results from individual climate runs can at best indicate tendencies and should therefore be interpreted with great care.

scholarly journals The impact of differences in large-scale circulation output from climate models on the regional modeling of ozone and PM

2012 ◽  
Vol 12 (20) ◽  
pp. 9441-9458 ◽  
Author(s):  
A. M. M. Manders ◽  
E. van Meijgaard ◽  
A. C. Mues ◽  
R. Kranenburg ◽  
L. H. van Ulft ◽  
...  
Keyword(s):  
Air Quality ◽  
Climate Models ◽  
Climate Model ◽  
Transport Model ◽  
Global Climate Model ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Climate Simulations ◽  
The Impact

Abstract. Climate change may have an impact on air quality (ozone, particulate matter) due to the strong dependency of air quality on meteorology. The effect is often studied using a global climate model (GCM) to produce meteorological fields that are subsequently used by chemical transport models. However, climate models themselves are subject to large uncertainties and fail to reproduce the present-day climate adequately. The present study illustrates the impact of these uncertainties on air quality. To this end, output from the SRES-A1B constraint transient runs with two GCMs, i.e. ECHAM5 and MIROC-hires, has been dynamically downscaled with the regional climate model RACMO2 and used to force a constant emission run with the chemistry transport model LOTOS-EUROS in a one-way coupled run covering the period 1970–2060. Results from the two climate simulations have been compared with a RACMO2-LOTOS-EUROS (RLE) simulation forced by the ERA-Interim reanalysis for the period 1989–2009. Both RLE_ECHAM and RLE_MIROC showed considerable deviations from RLE_ERA for daily maximum temperature, precipitation and wind speed. Moreover, sign and magnitude of these deviations depended on the region. The differences in average present-day concentrations between the simulations were equal to (RLE_MIROC) or even larger than (RLE_ECHAM) the differences in concentrations between present-day and future climate (2041–2060). The climate simulations agreed on a future increase in average summer ozone daily maximum concentrations of 5–10 μg m−3 in parts of Southern Europe and a smaller increase in Western and Central Europe. Annual average PM10 concentrations increased 0.5–1.0 μg m−3 in North-West Europe and the Po Valley, but these numbers are rather uncertain: overall, changes for PM10 were small, both positive and negative changes were found, and for many locations the two climate runs did not agree on the sign of the change. This illustrates that results from individual climate runs can at best indicate tendencies and should therefore be interpreted with great care.

scholarly journals Improved Bias Correction Techniques for Hydrological Simulations of Climate Change*

2015 ◽  
Vol 16 (6) ◽  
pp. 2421-2442 ◽  
Author(s):  
David W. Pierce ◽  
Daniel R. Cayan ◽  
Edwin P. Maurer ◽  
John T. Abatzoglou ◽  
Katherine C. Hegewisch
Keyword(s):  
Climate Change ◽  
Bias Correction ◽  
Climate Model ◽  
Global Climate Model ◽  
Cumulative Distribution ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Climate Change Signal ◽  
Daily Maximum ◽  
Temperature And Precipitation

Abstract Global climate model (GCM) output typically needs to be bias corrected before it can be used for climate change impact studies. Three existing bias correction methods, and a new one developed here, are applied to daily maximum temperature and precipitation from 21 GCMs to investigate how different methods alter the climate change signal of the GCM. The quantile mapping (QM) and cumulative distribution function transform (CDF-t) bias correction methods can significantly alter the GCM’s mean climate change signal, with differences of up to 2°C and 30% points for monthly mean temperature and precipitation, respectively. Equidistant quantile matching (EDCDFm) bias correction preserves GCM changes in mean daily maximum temperature but not precipitation. An extension to EDCDFm termed PresRat is introduced, which generally preserves the GCM changes in mean precipitation. Another problem is that GCMs can have difficulty simulating variance as a function of frequency. To address this, a frequency-dependent bias correction method is introduced that is twice as effective as standard bias correction in reducing errors in the models’ simulation of variance as a function of frequency, and it does so without making any locations worse, unlike standard bias correction. Last, a preconditioning technique is introduced that improves the simulation of the annual cycle while still allowing the bias correction to take account of an entire season’s values at once.

scholarly journals On the temperature dependence of organic reactivity, nitrogen oxides, ozone production, and the impact of emission controls in San Joaquin Valley California

2013 ◽  
Vol 13 (11) ◽  
pp. 28511-28560 ◽  
Author(s):  
S. E. Pusede ◽  
D. R. Gentner ◽  
P. J. Wooldridge ◽  
E. C. Browne ◽  
A. W. Rollins ◽  
...  
Keyword(s):  
Air Quality ◽  
Nitrogen Oxides ◽  
San Joaquin Valley ◽  
Ozone Production ◽  
Effective Control ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
The Impact ◽  
Organic Reactivity

Abstract. The San Joaquin Valley (SJV) experiences some of the worst ozone air quality in the US, frequently exceeding the California 8 h standard of 70.4 ppb. To improve our understanding of trends in the number of ozone violations in the SJV, we analyze observed relationships between organic reactivity, nitrogen oxides (NOx), and daily maximum temperature in the southern SJV using measurements made as part of California at the Nexus of Air Quality and Climate Change in 2010 (CalNex-SJV). We find the daytime speciated organic reactivity with respect to OH during CalNex-SJV has a temperature-independent portion with molecules typically associated with motor vehicles being the major component. At high temperatures, characteristic of days with high ozone, the largest portion of the total organic reactivity increases exponentially with temperature and is dominated by small, oxygenated organics and molecules that are unidentified. We use this simple temperature classification to consider changes in organic emissions over the last and next decade. With the CalNex-SJV observations as constraints, we examine the sensitivity of ozone production (PO3) to future NOx and organic reactivity controls. We find that PO3 is NOx-limited at all temperatures on weekends and on weekdays when daily maximum temperatures are greater than 29 °C. As a~consequence, NOx reductions are the most effective control option for reducing the frequency of future ozone violations in the southern SJV.

scholarly journals On the temperature dependence of organic reactivity, nitrogen oxides, ozone production, and the impact of emission controls in San Joaquin Valley, California

2014 ◽  
Vol 14 (7) ◽  
pp. 3373-3395 ◽  
Author(s):  
S. E. Pusede ◽  
D. R. Gentner ◽  
P. J. Wooldridge ◽  
E. C. Browne ◽  
A. W. Rollins ◽  
...  
Keyword(s):  
Air Quality ◽  
Nitrogen Oxides ◽  
San Joaquin Valley ◽  
Ozone Production ◽  
Effective Control ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
The Impact ◽  
Organic Reactivity

Abstract. The San Joaquin Valley (SJV) experiences some of the worst ozone air quality in the US, frequently exceeding the California 8 h standard of 70.4 ppb. To improve our understanding of trends in the number of ozone violations in the SJV, we analyze observed relationships between organic reactivity, nitrogen oxides (NOx), and daily maximum temperature in the southern SJV using measurements made as part of California at the Nexus of Air Quality and Climate Change in 2010 (CalNex-SJV). We find the daytime speciated organic reactivity with respect to OH during CalNex-SJV has a temperature-independent portion with molecules typically associated with motor vehicles being the major component. At high temperatures, characteristic of days with high ozone, the largest portion of the total organic reactivity increases exponentially with temperature and is dominated by small, oxygenated organics and molecules that are unidentified. We use this simple temperature classification to consider changes in organic emissions over the last and next decade. With the CalNex-SJV observations as constraints, we examine the sensitivity of ozone production (PO3) to future NOx and organic reactivity controls. We find that PO3 is NOx-limited at all temperatures on weekends and on weekdays when daily maximum temperatures are greater than 29 °C. As a consequence, NOx reductions are the most effective control option for reducing the frequency of future ozone violations in the southern SJV.

scholarly journals Social media reveal ecoregional variation in how weather influences visitor behavior in U.S. National Park Service units

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Emily J. Wilkins ◽  
Peter D. Howe ◽  
Jordan W. Smith
Keyword(s):  
National Park ◽  
National Park Service ◽  
Spatial Behavior ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Daily Weather ◽  
Visitor Behavior ◽  
Park Service ◽  
The Impact

AbstractDaily weather affects total visitation to parks and protected areas, as well as visitors’ experiences. However, it is unknown if and how visitors change their spatial behavior within a park due to daily weather conditions. We investigated the impact of daily maximum temperature and precipitation on summer visitation patterns within 110 U.S. National Park Service units. We connected 489,061 geotagged Flickr photos to daily weather, as well as visitors’ elevation and distance to amenities (i.e., roads, waterbodies, parking areas, and buildings). We compared visitor behavior on cold, average, and hot days, and on days with precipitation compared to days without precipitation, across fourteen ecoregions within the continental U.S. Our results suggest daily weather impacts where visitors go within parks, and the effect of weather differs substantially by ecoregion. In most ecoregions, visitors stayed closer to infrastructure on rainy days. Temperature also affects visitors’ spatial behavior within parks, but there was not a consistent trend across ecoregions. Importantly, parks in some ecoregions contain more microclimates than others, which may allow visitors to adapt to unfavorable conditions. These findings suggest visitors’ spatial behavior in parks may change in the future due to the increasing frequency of hot summer days.

scholarly journals Joint Occurrence of Daily Temperature and Precipitation Extreme Events over Canada

2014 ◽  
Vol 53 (9) ◽  
pp. 2148-2162 ◽  
Author(s):  
Bárbara Tencer ◽  
Andrew Weaver ◽  
Francis Zwiers
Keyword(s):  
Climate Models ◽  
Regional Climate ◽  
Heavy Precipitation ◽  
Maximum Temperature ◽  
Daily Minimum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Negative Consequences ◽  
Temperature And Precipitation ◽  
Joint Occurrence

AbstractThe occurrence of individual extremes such as temperature and precipitation extremes can have a great impact on the environment. Agriculture, energy demands, and human health, among other activities, can be affected by extremely high or low temperatures and by extremely dry or wet conditions. The simultaneous or proximate occurrence of both types of extremes could lead to even more profound consequences, however. For example, a dry period can have more negative consequences on agriculture if it is concomitant with or followed by a period of extremely high temperatures. This study analyzes the joint occurrence of very wet conditions and high/low temperature events at stations in Canada. More than one-half of the stations showed a significant positive relationship at the daily time scale between warm nights (daily minimum temperature greater than the 90th percentile) or warm days (daily maximum temperature above the 90th percentile) and heavy-precipitation events (daily precipitation exceeding the 75th percentile), with the greater frequencies found for the east and southwest coasts during autumn and winter. Cold days (daily maximum temperature below the 10th percentile) occur together with intense precipitation more frequently during spring and summer. Simulations by regional climate models show good agreement with observations in the seasonal and spatial variability of the joint distribution, especially when an ensemble of simulations was used.

Assessing the contribution of multiple forcings to changes in temperature extremes 1981–2020 using CMIP6 climate models

2021 ◽  
Author(s):  
Mastawesha Misganaw Engdaw ◽  
Andrew Ballinger ◽  
Gabriele Hegerl ◽  
Andrea Steiner
Keyword(s):  
Climate Change ◽  
Greenhouse Gases ◽  
Climate Models ◽  
Temporal Trends ◽  
Maximum Temperature ◽  
Daily Minimum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Temperature Extremes ◽  
Cold Temperatures

<p>In this study, we aim at quantifying the contribution of different forcings to changes in temperature extremes over 1981–2020 using CMIP6 climate model simulations. We first assess the changes in extreme hot and cold temperatures defined as days below 10% and above 90% of daily minimum temperature (TN10 and TN90) and daily maximum temperature (TX10 and TX90). We compute the change in percentage of extreme days per season for October-March (ONDJFM) and April-September (AMJJAS). Spatial and temporal trends are quantified using multi-model mean of all-forcings simulations. The same indices will be computed from aerosols-, greenhouse gases- and natural-only forcing simulations. The trends estimated from all-forcings simulations are then attributed to different forcings (aerosols-, greenhouse gases-, and natural-only) by considering uncertainties not only in amplitude but also in response patterns of climate models. The new statistical approach to climate change detection and attribution method by Ribes et al. (2017) is used to quantify the contribution of human-induced climate change. Preliminary results of the attribution analysis show that anthropogenic climate change has the largest contribution to the changes in temperature extremes in different regions of the world.</p><p><strong>Keywords:</strong> climate change, temperature, extreme events, attribution, CMIP6</p><p> </p><p><strong>Acknowledgement:</strong> This work was funded by the Austrian Science Fund (FWF) under Research Grant W1256 (Doctoral Programme Climate Change: Uncertainties, Thresholds and Coping Strategies)</p>

scholarly journals Assessing the impact of global warming on worldwide open field tomato cultivation through CSIRO-Mk3·0 global climate model

2016 ◽  
Vol 155 (3) ◽  
pp. 407-420 ◽  
Author(s):  
R. S. SILVA ◽  
L. KUMAR ◽  
F. SHABANI ◽  
M. C. PICANÇO
Keyword(s):  
Climate Change ◽  
Global Warming ◽  
Open Field ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Current Model ◽  
Global Climate Models ◽  
The Impact

SUMMARYTomato (Solanum lycopersicum L.) is one of the most important vegetable crops globally and an important agricultural sector for generating employment. Open field cultivation of tomatoes exposes the crop to climatic conditions, whereas greenhouse production is protected. Hence, global warming will have a greater impact on open field cultivation of tomatoes rather than the controlled greenhouse environment. Although the scale of potential impacts is uncertain, there are techniques that can be implemented to predict these impacts. Global climate models (GCMs) are useful tools for the analysis of possible impacts on a species. The current study aims to determine the impacts of climate change and the major factors of abiotic stress that limit the open field cultivation of tomatoes in both the present and future, based on predicted global climate change using CLIMatic indEX and the A2 emissions scenario, together with the GCM Commonwealth Scientific and Industrial Research Organisation (CSIRO)-Mk3·0 (CS), for the years 2050 and 2100. The results indicate that large areas that currently have an optimum climate will become climatically marginal or unsuitable for open field cultivation of tomatoes due to progressively increasing heat and dry stress in the future. Conversely, large areas now marginal and unsuitable for open field cultivation of tomatoes will become suitable or optimal due to a decrease in cold stress. The current model may be useful for plant geneticists and horticulturalists who could develop new regional stress-resilient tomato cultivars based on needs related to these modelling projections.

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.

Dust Aerosol Important for Snowball Earth Deglaciation

2010 ◽  
Vol 23 (15) ◽  
pp. 4121-4132 ◽  
Author(s):  
Dorian S. Abbot ◽  
Itay Halevy
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Atmospheric Model ◽  
Dust Aerosol ◽  
Snowball Earth ◽  
Dust Aerosols ◽  
Co2 Levels ◽  
The Impact

Abstract Most previous global climate model simulations could only produce the termination of Snowball Earth episodes at CO2 partial pressures of several tenths of a bar, which is roughly an order of magnitude higher than recent estimates of CO2 levels during and shortly after Snowball events. These simulations have neglected the impact of dust aerosols on radiative transfer, which is an assumption of potentially grave importance. In this paper it is argued, using the Dust Entrainment and Deposition (DEAD) box model driven by GCM results, that atmospheric dust aerosol concentrations may have been one to two orders of magnitude higher during a Snowball Earth event than today. It is furthermore asserted on the basis of calculations using NCAR’s Single Column Atmospheric Model (SCAM)—a radiative–convective model with sophisticated aerosol, cloud, and radiative parameterizations—that when the surface albedo is high, such increases in dust aerosol loading can produce several times more surface warming than an increase in the partial pressure of CO2 from 10−4 to 10−1 bar. Therefore the conclusion is reached that including dust aerosols in simulations may reconcile the CO2 levels required for Snowball termination in climate models with observations.

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