The Climate Response to Emissions Reductions due to COVID-19

2021 ◽  
Author(s):  
Chris Jones ◽  
Keyword(s):  
Atmospheric Composition ◽  
Shortwave Radiation ◽  
Initial Condition ◽  
Emissions Reductions ◽  
Near Surface ◽  
Surface Climate ◽  
Climate Signals ◽  
Near Term ◽  
Regional Analyses ◽  
The Impact

<p>Many nations responded to the COVID-19 pandemic by restricting travel and other activities during 2020, resulting in temporarily reduced emissions of CO2, other greenhouse gases and ozone and aerosol precursors. We perform a coordinated Intercomparison, CovidMIP, of Earth System model simulations to assess the impact on climate of these emissions reductions. Eleven models performed multiple initial-condition ensembles to produce over 280 simulations spanning both initial condition and model structural uncertainty. We find model consensus on reduced aerosol amounts (particularly over East Asia) and associated increases in surface shortwave radiation levels. However, any impact on near-surface temperature or rainfall during 2020-2024 is extremely small and is not detectable in this initial analysis. Regional analyses on a finer scale, and closer attention to extremes (especially linked to changes in atmospheric composition and air quality) are required to test the impact of COVID-19-related emission reductions on near-term climate.</p><p>This first-look at results has focussed on surface climate, but future analysis will include attribution of drivers of climate signals; longer term implications of emissions reductions and options for economic recovery; quantifying changes in extremes; influence on atmospheric circulation and the carbon cycle.</p>

scholarly journals A bias-corrected CMIP5 dataset for Africa using the CDF-t method – a contribution to agricultural impact studies

2018 ◽  
Vol 9 (1) ◽  
pp. 313-338 ◽  
Author(s):  
Adjoua Moise Famien ◽  
Serge Janicot ◽  
Abe Delfin Ochou ◽  
Mathieu Vrac ◽  
Dimitri Defrance ◽  
...  
Keyword(s):  
West Africa ◽  
Air Temperature ◽  
Climate Model ◽  
Global Climate Model ◽  
Cumulative Distribution ◽  
Shortwave Radiation ◽  
Climate Change Scenarios ◽  
Reference Dataset ◽  
Near Surface ◽  
The Impact

Abstract. The objective of this paper is to present a new dataset of bias-corrected CMIP5 global climate model (GCM) daily data over Africa. This dataset was obtained using the cumulative distribution function transform (CDF-t) method, a method that has been applied to several regions and contexts but never to Africa. Here CDF-t has been applied over the period 1950–2099 combining Historical runs and climate change scenarios for six variables: precipitation, mean near-surface air temperature, near-surface maximum air temperature, near-surface minimum air temperature, surface downwelling shortwave radiation, and wind speed, which are critical variables for agricultural purposes. WFDEI has been used as the reference dataset to correct the GCMs. Evaluation of the results over West Africa has been carried out on a list of priority user-based metrics that were discussed and selected with stakeholders. It includes simulated yield using a crop model simulating maize growth. These bias-corrected GCM data have been compared with another available dataset of bias-corrected GCMs using WATCH Forcing Data as the reference dataset. The impact of WFD, WFDEI, and also EWEMBI reference datasets has been also examined in detail. It is shown that CDF-t is very effective at removing the biases and reducing the high inter-GCM scattering. Differences with other bias-corrected GCM data are mainly due to the differences among the reference datasets. This is particularly true for surface downwelling shortwave radiation, which has a significant impact in terms of simulated maize yields. Projections of future yields over West Africa are quite different, depending on the bias-correction method used. However all these projections show a similar relative decreasing trend over the 21st century.

scholarly journals Representation of model error in a convective-scale ensemble prediction system

2014 ◽  
Vol 21 (1) ◽  
pp. 19-39 ◽  
Author(s):  
L. H. Baker ◽  
A. C. Rudd ◽  
S. Migliorini ◽  
R. N. Bannister
Keyword(s):  
Model Error ◽  
Ensemble Prediction ◽  
Initial Condition ◽  
Prediction System ◽  
Ensemble Prediction System ◽  
Near Surface ◽  
Skill Scores ◽  
The Uk ◽  
Parameter Values ◽  
The Impact

Abstract. In this paper ensembles of forecasts (of up to six hours) are studied from a convection-permitting model with a representation of model error due to unresolved processes. The ensemble prediction system (EPS) used is an experimental convection-permitting version of the UK Met Office's 24-member Global and Regional Ensemble Prediction System (MOGREPS). The method of representing model error variability, which perturbs parameters within the model's parameterisation schemes, has been modified and we investigate the impact of applying this scheme in different ways. These are: a control ensemble where all ensemble members have the same parameter values; an ensemble where the parameters are different between members, but fixed in time; and ensembles where the parameters are updated randomly every 30 or 60 min. The choice of parameters and their ranges of variability have been determined from expert opinion and parameter sensitivity tests. A case of frontal rain over the southern UK has been chosen, which has a multi-banded rainfall structure. The consequences of including model error variability in the case studied are mixed and are summarised as follows. The multiple banding, evident in the radar, is not captured for any single member. However, the single band is positioned in some members where a secondary band is present in the radar. This is found for all ensembles studied. Adding model error variability with fixed parameters in time does increase the ensemble spread for near-surface variables like wind and temperature, but can actually decrease the spread of the rainfall. Perturbing the parameters periodically throughout the forecast does not further increase the spread and exhibits "jumpiness" in the spread at times when the parameters are perturbed. Adding model error variability gives an improvement in forecast skill after the first 2–3 h of the forecast for near-surface temperature and relative humidity. For precipitation skill scores, adding model error variability has the effect of improving the skill in the first 1–2 h of the forecast, but then of reducing the skill after that. Complementary experiments were performed where the only difference between members was the set of parameter values (i.e. no initial condition variability). The resulting spread was found to be significantly less than the spread from initial condition variability alone.

scholarly journals Near-surface climate and surface energy budget of Larsen C ice shelf, Antarctic Peninsula

2012 ◽  
Vol 6 (2) ◽  
pp. 353-363 ◽  
Author(s):  
P. Kuipers Munneke ◽  
M. R. van den Broeke ◽  
J. C. King ◽  
T. Gray ◽  
C. H. Reijmer
Keyword(s):  
Surface Energy ◽  
Antarctic Peninsula ◽  
Energy Budget ◽  
Heat Fluxes ◽  
Surface Energy Budget ◽  
Shortwave Radiation ◽  
Sensible Heat ◽  
Ice Shelf ◽  
Near Surface ◽  
The Impact

Abstract. Data collected by two automatic weather stations (AWS) on the Larsen C ice shelf, Antarctica, between 22 January 2009 and 1 February 2011 are analyzed and used as input for a model that computes the surface energy budget (SEB), which includes melt energy. The two AWSs are separated by about 70 km in the north–south direction, and both the near-surface meteorology and the SEB show similarities, although small differences in all components (most notably the melt flux) can be seen. The impact of subsurface absorption of shortwave radiation on melt and snow temperature is significant, and discussed. In winter, longwave cooling of the surface is entirely compensated by a downward turbulent transport of sensible heat. In summer, the positive net radiative flux is compensated by melt, and quite frequently by upward turbulent diffusion of heat and moisture, leading to sublimation and weak convection over the ice shelf. The month of November 2010 is highlighted, when strong westerly flow over the Antarctic Peninsula led to a dry and warm föhn wind over the ice shelf, resulting in warm and sunny conditions. Under these conditions the increase in shortwave and sensible heat fluxes is larger than the decrease of net longwave and latent heat fluxes, providing energy for significant melt.

Impact Assessment of Satellite-Derived Leaf Area Index Datasets Using a General Circulation Model

2007 ◽  
Vol 20 (6) ◽  
pp. 993-1015 ◽  
Author(s):  
Hyun-Suk Kang ◽  
Yongkang Xue ◽  
G. James Collatz
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
General Circulation ◽  
Circulation Model ◽  
West African ◽  
Radiative Energy ◽  
Area Index ◽  
Near Surface ◽  
Surface Climate ◽  
The Impact

Abstract This study assesses the impact of two different remote sensing–derived leaf area index (RSLAI) datasets retrieved from the same source (i.e., Advanced Very High Resolution Radiometer measurements) on a general circulation model’s (GCM) seasonal climate simulations as well as the mechanisms that lead to the improvement in simulations over several regions. Based on the analysis of these two RSLAI datasets for 17 yr from 1982 to 1998, their spatial distribution patterns and characteristics are discussed. Despite some disagreements in the RSLAI magnitudes and the temporal variability between these two datasets over some areas, their effects on the simulation of near-surface climate and the regions with significant impact are generally similar to each other. Major disagreements in the simulated climate appear in a few limited regions. The GCM experiment using the RSLAI and other satellite-derived land surface products showed substantial improvements in the near-surface climate in the East Asian and West African summer monsoon areas and boreal forests of North America compared to the control experiment that used LAI extrapolated from limited ground surveys. For the East Asia and northwest U.S. regions, the major role of RSLAI changes is in partitioning the net radiative energy into latent and sensible heat fluxes, which results in discernable warming and decrease of precipitation due to the smaller RSLAI values compared to the control. Meanwhile, for the West African semiarid regions, where the LAI difference between RSLAI and control experiments is negligible, the decrease in surface albedo caused by the high vegetation cover fraction in the satellite-derived dataset plays an important role in altering local circulation that produces a positive feedback in land/atmosphere interaction.

scholarly journals Near-surface climate and surface energy budget of Larsen C ice shelf, Antarctic Peninsula

2011 ◽  
Vol 5 (5) ◽  
pp. 2665-2697
Author(s):  
P. Kuipers Munneke ◽  
M. R. van den Broeke ◽  
J. C. King ◽  
T. Gray ◽  
C. H. Reijmer
Keyword(s):  
Surface Energy ◽  
Antarctic Peninsula ◽  
Energy Budget ◽  
Heat Fluxes ◽  
Surface Energy Budget ◽  
Shortwave Radiation ◽  
Sensible Heat ◽  
Ice Shelf ◽  
Near Surface ◽  
The Impact

Abstract. Data collected by two automatic weather stations (AWS) on the Larsen C ice shelf, Antarctica, between 22 January 2009 and 1 February 2011 are analyzed and used as input for a model that computes the surface energy budget (SEB), including melt energy. The two AWSs are separated by about 70 km in the north-south direction, and both the near-surface meteorology and the SEB show similarities, although small differences in all components (most notably the melt flux) can be seen. The impact of subsurface absorption of shortwave radiation on melt and snow temperature is significant, and discussed. In winter, longwave cooling of the surface is entirely compensated by a downward turbulent transport of sensible heat. In summer, the positive net radiative flux is compensated by melt, and quite frequently by upward turbulent diffusion of heat and moisture, leading to sublimation and weak convection over the ice shelf. The month of November 2010 is highlighted, when strong westerly flow over the Antarctic Peninsula led to a dry and warm föhn wind over the ice shelf, resulting in warm and sunny conditions. Under these conditions the increase in shortwave and sensible heat fluxes is larger than the reduction of net longwave and latent heat fluxes, providing energy for significant melt.

scholarly journals A bias-corrected CMIP5 dataset for Africa using CDF-t method. A contribution to agricultural impact studies

2017 ◽  
Author(s):  
Adjoua Moise Famien ◽  
Serge Janicot ◽  
Abe Delfin Ochou ◽  
Mathieu Vrac ◽  
Dimitri Defrance ◽  
...  
Keyword(s):  
West Africa ◽  
Air Temperature ◽  
Climate Models ◽  
Global Climate Models ◽  
Cumulative Distribution ◽  
Shortwave Radiation ◽  
Climate Change Scenarios ◽  
Data Set ◽  
Near Surface ◽  
The Impact

Abstract. The objective of this paper is to present a new data set of bias-corrected CMIP5 global climate models (GCMs) daily data over Africa. This dataset was obtained in using the Cumulative Distribution Function Transform (CDF-t) method, a method that has been applied on several regions and contexts but never on Africa. Here CDF-t is used over the period 1950–2099 combining historical runs and climate change scenarios on 6 variables, precipitation, mean near-surface air temperature, near-surface maximum air temperature, near-surface minimum air temperature, surface down-welling shortwave radiation, and wind speed, which are critical variables for agricultural purposes. Evaluation of the results is carried out over West Africa on a list of priority users-based metrics that was discussed and selected with stakeholders and on simulated yield using a crop model simulating maize growth. Bias-corrected GCMs data are compared with another available dataset of bias-corrected GCMs, and the impact of three different reference datasets on bias-corrections is also examined in details. CDF-t is very effective in removing the biases and in reducing the high inter-GCMs scattering. Differences with other bias-corrected GCMs data are mainly due to the differences between the reference datasets. This is particular true for surface down-welling shortwave radiation, which has impacts in terms of simulated maize yields. Projections of future yields over West Africa have quite different levels, depending on bias-correction method used, but they all show a similar relative decreasing trend over the 21st century.

scholarly journals Using Satellite Data for CBRN (Chemical, Biological, Radiological, and Nuclear) Threat Detection, Monitoring, and Modelling

2021 ◽  
Author(s):  
Gary Sutlieff ◽  
Lucy Berthoud ◽  
Mark Stinchcombe
Keyword(s):  
Satellite Data ◽  
Meteorological Data ◽  
Atmospheric Composition ◽  
Chemical Detection ◽  
List Type ◽  
Data Types ◽  
Wide Range ◽  
Future Technologies ◽  
The Impact ◽  
Near Future

Abstract CBRN (Chemical, Biological, Radiological, and Nuclear) threats are becoming more prevalent, as more entities gain access to modern weapons and industrial technologies and chemicals. This has produced a need for improvements to modelling, detection, and monitoring of these events. While there are currently no dedicated satellites for CBRN purposes, there are a wide range of possibilities for satellite data to contribute to this field, from atmospheric composition and chemical detection to cloud cover, land mapping, and surface property measurements. This study looks at currently available satellite data, including meteorological data such as wind and cloud profiles, surface properties like temperature and humidity, chemical detection, and sounding. Results of this survey revealed several gaps in the available data, particularly concerning biological and radiological detection. The results also suggest that publicly available satellite data largely does not meet the requirements of spatial resolution, coverage, and latency that CBRN detection requires, outside of providing terrain use and building height data for constructing models. Lastly, the study evaluates upcoming instruments, platforms, and satellite technologies to gauge the impact these developments will have in the near future. Improvements in spatial and temporal resolution as well as latency are already becoming possible, and new instruments will fill in the gaps in detection by imaging a wider range of chemicals and other agents and by collecting new data types. This study shows that with developments coming within the next decade, satellites should begin to provide valuable augmentations to CBRN event detection and monitoring. Article Highlights There is a wide range of existing satellite data in fields that are of interest to CBRN detection and monitoring. The data is mostly of insufficient quality (resolution or latency) for the demanding requirements of CBRN modelling for incident control. Future technologies and platforms will improve resolution and latency, making satellite data more viable in the CBRN management field

A Method for Evaluating Intensity of Water Cavitation Peening Processing

2011 ◽  
Vol 675-677 ◽  
pp. 747-750
Author(s):  
B. Han ◽  
Dong Ying Ju ◽  
Xiao Guang Yu
Keyword(s):  
Residual Stress ◽  
Process Capability ◽  
Diffraction Method ◽  
Spring Steel ◽  
Bubble Collapse ◽  
Plastic Layer ◽  
Process Conditions ◽  
X Ray Diffraction ◽  
Near Surface ◽  
The Impact

Water cavitation peening (WCP) with aeration, namely, a new ventilation nozzle with aeration is adopted to improve the process capability of WCP by increasing the impact pressure induced by the bubble collapse on the surface of components. In this study, in order to investigate the process capability of the WCP with aeration a standard N-type almen strips of spring steel SAE 1070 was treated byWCP with various process conditions, and the arc height value and the residual stress in the superficial layers were measured by means of the Almen-scale and X-ray diffraction method, respectively. The optimal fluxes of aeration and the optimal standoff distances were achieved. The maximum of arc height value reach around 150μm. The depth of plastic layer observed from the results of residual stresses is up to 150μm. The results verify the existence of macro-plastic strain in WCP processing. The distributions of residual stress in near-surface under different peening intensity can provide a reference for engineers to decide the optimal process conditions of WCP processing.

scholarly journals Assessing the regional impacts of Mexico City emissions on air quality and chemistry

2009 ◽  
Vol 9 (11) ◽  
pp. 3731-3743 ◽  
Author(s):  
M. Mena-Carrasco ◽  
G. R. Carmichael ◽  
J. E. Campbell ◽  
D. Zimmerman ◽  
Y. Tang ◽  
...  
Keyword(s):  
Air Quality ◽  
Mexico City ◽  
Ozone Production ◽  
Anthropogenic Aerosol ◽  
Near Surface ◽  
Mixing Ratios ◽  
Regional Impacts ◽  
Photolysis Rates ◽  
Regional Air Quality ◽  
The Impact

Abstract. The impact of Mexico City (MCMA) emissions is examined by studying its effects on air quality, photochemistry, and on ozone production regimes by combining model products and aircraft observations from the MILAGRO experiment during March 2006. The modeled influence of MCMA emissions to enhancements in surface level NOx, CO, and O3 concentrations (10–30% increase) are confined to distances <200 km, near surface. However, the extent of the influence is significantly larger at higher altitudes. Broader MCMA impacts (some 900 km Northeast of the city) are shown for specific outflow conditions in which enhanced ozone, NOy, and MTBE mixing ratios over the Gulf of Mexico are linked to MCMA by source tagged tracers and sensitivity runs. This study shows that the "footprint" of MCMA on average is fairly local, with exception to reactive nitrogen, which can be transported long range in the form of PAN, acting as a reservoir and source of NOx with important regional ozone formation implications. The simulated effect of MCMA emissions of anthropogenic aerosol on photochemistry showed a maximum regional decrease of 40% in J[NO2→NO+O], and resulting in the reduction of ozone production by 5–10%. Observed ozone production efficiencies are evaluated as a function of distance from MCMA, and by modeled influence from MCMA. These tend to be much lower closer to MCMA, or in those points where modeled contribution from MCMA is large. This research shows that MCMA emissions do effect on regional air quality and photochemistry, both contributing large amounts of ozone and its precursors, but with caveat that aerosol concentrations hinder formation of ozone to its potential due to its reduction in photolysis rates.

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