scholarly journals Climate extremes in multi-model simulations of stratospheric aerosol and marine cloud brightening climate engineering

2014 ◽  
Vol 14 (23) ◽  
pp. 32393-32425
Author(s):  
V. N. Aswathy ◽  
O. Boucher ◽  
M. Quaas ◽  
U. Niemeier ◽  
H. Muri ◽  
...  
Keyword(s):  
The Arctic ◽  
Large Temperature ◽  
Solar Radiation Management ◽  
Change Scenario ◽  
Climate Engineering ◽  
Cold Temperatures ◽  
Dry Spell ◽  
Low Latitudes ◽  
The Mean ◽  
The Tropics

Abstract. Simulations from a multi-model ensemble for the RCP4.5 climate change scenario for the 21st century, and for two solar radiation management schemes (stratospheric sulfate injection, G3, and marine cloud brightening, G3SSCE) have been analyzed in terms of changes in the mean and extremes for surface air temperature and precipitation. The climate engineered (SRM 2060s – RCP4.5 2010s) and termination (2080s – 2060s) periods are investigated. During the climate engineering period, both schemes, as intended, offset temperature increases by about 60% globally, but are more effective in the low latitudes and exhibit some residual warming in the Arctic (especially in the case of marine cloud brightening that is only applied in the low latitudes). In both climate engineering scenarios, extreme temperatures changes are similar to the mean temperature changes over much of the globe. The exception is in Northern Hemisphere high latitudes, where high temperatures (90th percentile of the distribution) of climate engineering relative to RCP4.5 rise less than the mean and cold temperatures (10th percentile) much more than the mean. When defining temperature extremes by fixed thresholds, namely number of frost days and summer days, it is found that both climate engineering experiments are not completely alleviating the changes relative to RCP 4.5. The reduction in 2060s dry spell occurrence over land region in G3-SSCE is is more pronounced than over oceans. Experiment G3 exhibits same pattern as G3-SSCE albeit, stronger in magnitude. A strong termination effect is found for the two climate engineering schemes, with large temperature increases especially in the Arctic. Mean temperatures rise faster than the extremes, especially over oceans, with the exception of the Tropics. Conversely precipitation extremes rise much more than the mean, even more so over the ocean, and especially in the Tropics.

scholarly journals Climate extremes in multi-model simulations of stratospheric aerosol and marine cloud brightening climate engineering

2015 ◽  
Vol 15 (16) ◽  
pp. 9593-9610 ◽  
Author(s):  
V. N. Aswathy ◽  
O. Boucher ◽  
M. Quaas ◽  
U. Niemeier ◽  
H. Muri ◽  
...  
Keyword(s):  
Extreme Precipitation ◽  
Extreme Temperature ◽  
The Arctic ◽  
Large Temperature ◽  
Frequency Of Occurrence ◽  
Climate Engineering ◽  
Temperature Changes ◽  
Dry Spell ◽  
Low Latitudes ◽  
The Mean

Abstract. Simulations from a multi-model ensemble for the RCP4.5 climate change scenario for the 21st century, and for two solar radiation management (SRM) schemes (stratospheric sulfate injection (G3), SULF and marine cloud brightening by sea salt emission SALT) have been analysed in terms of changes in the mean and extremes of surface air temperature and precipitation. The climate engineering and termination periods are investigated. During the climate engineering period, both schemes, as intended, offset temperature increases by about 60 % globally, but are more effective in the low latitudes and exhibit some residual warming in the Arctic (especially in the case of SALT which is only applied in the low latitudes). In both climate engineering scenarios, extreme temperature changes are similar to the mean temperature changes over much of the globe. The exceptions are the mid- and high latitudes in the Northern Hemisphere, where high temperatures (90th percentile of the distribution) of the climate engineering period compared to RCP4.5 control period rise less than the mean, and cold temperatures (10th percentile), much more than the mean. This aspect of the SRM schemes is also reflected in simulated reduction in the frost day frequency of occurrence for both schemes. However, summer day frequency of occurrence increases less in the SALT experiment than the SULF experiment, especially over the tropics. Precipitation extremes in the two SRM scenarios act differently – the SULF experiment more effectively mitigates extreme precipitation increases over land compared to the SALT experiment. A reduction in dry spell occurrence over land is observed in the SALT experiment. The SULF experiment has a slight increase in the length of dry spells. A strong termination effect is found for the two climate engineering schemes, with large temperature increases especially in the Arctic. Globally, SULF is more effective in reducing extreme temperature increases over land than SALT. Extreme precipitation increases over land is also more reduced in SULF than the SALT experiment. However, globally SALT decreases the frequency of dry spell length and reduces the occurrence of hot days compared to SULF.

scholarly journals Fresnel scatter revisited – comparison of 50 MHz radar and radiosondes in the Arctic, the Tropics and Antarctica

2010 ◽  
Vol 28 (10) ◽  
pp. 1993-2005 ◽  
Author(s):  
S. Kirkwood ◽  
E. Belova ◽  
K. Satheesan ◽  
T. Narayana Rao ◽  
T. Rajendra Prasad ◽  
...  
Keyword(s):  
Refractive Index ◽  
The Arctic ◽  
Refractive Index Gradient ◽  
Upper Troposphere ◽  
Show Evidence ◽  
Index Gradient ◽  
The Mean ◽  
Distinct Layering ◽  
The Tropics ◽  
The Relationship

Abstract. High-resolution radiosondes and calibrated radars operating close to 50 MHz, are used to examine the relationship between the strength of radar scatter and refractive index gradient. Three radars are used, in Kiruna in Arctic Sweden, at Gadanki in southern India and at the Swedish/Finnish base Wasa/Aboa in Queen Maud Land, Antarctica. Calibration is accomplished using the daily variation of galactic noise measured at each site. Proportionality between radar scatter strength and the square of the mean gradient of potential refractive index, M2, is found in the upper troposphere and lower stratosphere at all three sites, confirming previously reported results from many VHF radars. If the radar scatter is interpreted as Fresnel scatter, the constant of proportionality between radar scatter and M2 is found to be the same, within the calibration uncertainties, for all three radars. The radiosondes show evidence of distinct layering with sharp gradients, extending over 10s of kilometers horizontally, but the scatter is found to be two orders of magnitude weaker than would be expected from true Fresnel scatter from such layers. Using radar reflectivities resolved to a few 100 ms, we show that this is due to strong temporal variability in the scattering conditions, possibly due to undulations of the scattering layers. The constancy of the radar scatter – M2 relationship between the different sites suggests an unexpected uniformity in these perturbations between very different regions of the globe.

scholarly journals Large-Scale Tropospheric Transport in the Chemistry Climate Model Initiative (CCMI) Simulations

2017 ◽  
Author(s):  
Clara Orbe ◽  
Huang Yang ◽  
Darryn W. Waugh ◽  
Guang Zeng ◽  
Olaf Morgenstern ◽  
...  
Keyword(s):  
Large Scale ◽  
Climate Model ◽  
Atmospheric Transport ◽  
Global Scale ◽  
Atmospheric Composition ◽  
The Arctic ◽  
Free Running ◽  
The Mean ◽  
The Tropics ◽  
Interhemispheric Transport

Abstract. Understanding and modeling the large-scale transport of trace gases and aerosols is important for interpreting past (and projecting future) changes in atmospheric composition. Here we show that there are large differences in the global-scale atmospheric transport properties among models participating in the IGAC SPARC Chemistry-Climate Model Initiative (CCMI). Specifically, we find up to 40 % differences in the transport timescales connecting the Northern Hemisphere (NH) midlatitude surface to the Arctic and to Southern Hemisphere high latitudes, where the mean age ranges between 1.7 years and 2.6 years. We show that these differences are related to large differences in vertical transport among the simulations and, in particular, to differences in parameterized convection over the oceans. While stronger convection over NH midlatitudes is associated with slower transport to the Arctic, stronger convection in the tropics and subtropics is associated with faster interhemispheric transport. We also show that the differences among simulations constrained with fields derived from the same reanalysis products are as large as (and, in some cases, larger than) the differences among free-running simulations, due to larger differences in parameterized convection. Our results indicate that care must be taken when using simulations constrained with analyzed winds to interpret the influence of meteorology on tropospheric composition.

scholarly journals Large-scale tropospheric transport in the Chemistry–Climate Model Initiative (CCMI) simulations

2018 ◽  
Vol 18 (10) ◽  
pp. 7217-7235 ◽  
Author(s):  
Clara Orbe ◽  
Huang Yang ◽  
Darryn W. Waugh ◽  
Guang Zeng ◽  
Olaf Morgenstern ◽  
...  
Keyword(s):  
Large Scale ◽  
Climate Model ◽  
Atmospheric Transport ◽  
Global Scale ◽  
Atmospheric Composition ◽  
The Arctic ◽  
Free Running ◽  
The Mean ◽  
The Tropics ◽  
Interhemispheric Transport

Abstract. Understanding and modeling the large-scale transport of trace gases and aerosols is important for interpreting past (and projecting future) changes in atmospheric composition. Here we show that there are large differences in the global-scale atmospheric transport properties among the models participating in the IGAC SPARC Chemistry–Climate Model Initiative (CCMI). Specifically, we find up to 40 % differences in the transport timescales connecting the Northern Hemisphere (NH) midlatitude surface to the Arctic and to Southern Hemisphere high latitudes, where the mean age ranges between 1.7 and 2.6 years. We show that these differences are related to large differences in vertical transport among the simulations, in particular to differences in parameterized convection over the oceans. While stronger convection over NH midlatitudes is associated with slower transport to the Arctic, stronger convection in the tropics and subtropics is associated with faster interhemispheric transport. We also show that the differences among simulations constrained with fields derived from the same reanalysis products are as large as (and in some cases larger than) the differences among free-running simulations, most likely due to larger differences in parameterized convection. Our results indicate that care must be taken when using simulations constrained with analyzed winds to interpret the influence of meteorology on tropospheric composition.

scholarly journals Using Saildrones to Validate Arctic Sea-Surface Salinity from the SMAP Satellite and from Ocean Models

2021 ◽  
Vol 13 (5) ◽  
pp. 831
Author(s):  
Jorge Vazquez-Cuervo ◽  
Chelle Gentemann ◽  
Wenqing Tang ◽  
Dustin Carroll ◽  
Hong Zhang ◽  
...  
Keyword(s):  
Arctic Ocean ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
The Arctic ◽  
Future Research ◽  
Surface Salinity ◽  
Cold Temperatures ◽  
Yukon River ◽  
Arctic Sea ◽  
The Arctic Ocean

The Arctic Ocean is one of the most important and challenging regions to observe—it experiences the largest changes from climate warming, and at the same time is one of the most difficult to sample because of sea ice and extreme cold temperatures. Two NASA-sponsored deployments of the Saildrone vehicle provided a unique opportunity for validating sea-surface salinity (SSS) derived from three separate products that use data from the Soil Moisture Active Passive (SMAP) satellite. To examine possible issues in resolving mesoscale-to-submesoscale variability, comparisons were also made with two versions of the Estimating the Circulation and Climate of the Ocean (ECCO) model (Carroll, D; Menmenlis, D; Zhang, H.). The results indicate that the three SMAP products resolve the runoff signal associated with the Yukon River, with high correlation between SMAP products and Saildrone SSS. Spectral slopes, overall, replicate the −2.0 slopes associated with mesoscale-submesoscale variability. Statistically significant spatial coherences exist for all products, with peaks close to 100 km. Based on these encouraging results, future research should focus on improving derivations of satellite-derived SSS in the Arctic Ocean and integrating model results to complement remote sensing observations.

scholarly journals Evaluation of cloud fraction and its radiative effect simulated by IPCC AR4 global models against ARM surface observations

2012 ◽  
Vol 12 (4) ◽  
pp. 1785-1810 ◽  
Author(s):  
Y. Qian ◽  
C. N. Long ◽  
H. Wang ◽  
J. M. Comstock ◽  
S. A. McFarlane ◽  
...  
Keyword(s):  
Seasonal Variation ◽  
Probability Distribution ◽  
Vertical Structure ◽  
Cloud Amount ◽  
Cloud Fraction ◽  
Department Of Energy ◽  
The Arctic ◽  
Radiative Fluxes ◽  
The Tropics ◽  
Ipcc Ar4

Abstract. Cloud Fraction (CF) is the dominant modulator of radiative fluxes. In this study, we evaluate CF simulated in the IPCC AR4 GCMs against ARM long-term ground-based measurements, with a focus on the vertical structure, total amount of cloud and its effect on cloud shortwave transmissivity. Comparisons are performed for three climate regimes as represented by the Department of Energy Atmospheric Radiation Measurement (ARM) sites: Southern Great Plains (SGP), Manus, Papua New Guinea and North Slope of Alaska (NSA). Our intercomparisons of three independent measurements of CF or sky-cover reveal that the relative differences are usually less than 10% (5%) for multi-year monthly (annual) mean values, while daily differences are quite significant. The total sky imager (TSI) produces smaller total cloud fraction (TCF) compared to a radar/lidar dataset for highly cloudy days (CF > 0.8), but produces a larger TCF value than the radar/lidar for less cloudy conditions (CF < 0.3). The compensating errors in lower and higher CF days result in small biases of TCF between the vertically pointing radar/lidar dataset and the hemispheric TSI measurements as multi-year data is averaged. The unique radar/lidar CF measurements enable us to evaluate seasonal variation of cloud vertical structures in the GCMs. Both inter-model deviation and model bias against observation are investigated in this study. Another unique aspect of this study is that we use simultaneous measurements of CF and surface radiative fluxes to diagnose potential discrepancies among the GCMs in representing other cloud optical properties than TCF. The results show that the model-observation and inter-model deviations have similar magnitudes for the TCF and the normalized cloud effect, and these deviations are larger than those in surface downward solar radiation and cloud transmissivity. This implies that other dimensions of cloud in addition to cloud amount, such as cloud optical thickness and/or cloud height, have a similar magnitude of disparity as TCF within the GCMs, and suggests that the better agreement among GCMs in solar radiative fluxes could be a result of compensating effects from errors in cloud vertical structure, overlap assumption, cloud optical depth and/or cloud fraction. The internal variability of CF simulated in ensemble runs with the same model is minimal. Similar deviation patterns between inter-model and model-measurement comparisons suggest that the climate models tend to generate larger biases against observations for those variables with larger inter-model deviation. The GCM performance in simulating the probability distribution, transmissivity and vertical profiles of cloud are comprehensively evaluated over the three ARM sites. The GCMs perform better at SGP than at the other two sites in simulating the seasonal variation and probability distribution of TCF. However, the models remarkably underpredict the TCF at SGP and cloud transmissivity is less susceptible to the change of TCF than observed. In the tropics, most of the GCMs tend to underpredict CF and fail to capture the seasonal variation of CF at middle and low levels. The high-level CF is much larger in the GCMs than the observations and the inter-model variability of CF also reaches a maximum at high levels in the tropics, indicating discrepancies in the representation of ice cloud associated with convection in the models. While the GCMs generally capture the maximum CF in the boundary layer and vertical variability, the inter-model deviation is largest near the surface over the Arctic.

The Identity and Distribution of Species of Phytoseius Ribaga (Acarina: Phytoseiidae) in Canada,

1965 ◽  
Vol 97 (9) ◽  
pp. 897-909 ◽  
Author(s):  
D. A. Chant
Keyword(s):  
The Arctic ◽  
Deciduous Trees ◽  
The Tropics

AbstractMites of the genus Phytoseius Ribaga largely inhabit plants and are at least partly predacious, feeding on tetranychid, eriophyid, and other mites. They probably also feed on pollen, honeydew, and plant juices, as do other phytoseiids that have been studied (Chant 1959; Dosse 1961; McMurty and Scriven 1964). They are not usually found in soil or humus but occur on many kinds of low growing plants as well as coniferous and deciduous trees. They have been collected on all continents and from the arctic to the tropics.

Potential predictability of Southwest US rainfall : role of tropical and high-latitude variability

2021 ◽  
pp. 1-45
Keyword(s):  
Time Scale ◽  
Climate Model ◽  
Southern Oscillation ◽  
Seasonal Prediction ◽  
Seasonal Rainfall ◽  
The Arctic ◽  
Sea Ice Concentration ◽  
Potential Predictability ◽  
Subseasonal Variability ◽  
The Tropics

Abstract This study explores the potential predictability of Southwest US (SWUS) precipitation for the November-March season in a set of numerical experiments performed with the Whole Atmospheric Community Climate Model. In addition to the prescription of observed sea surface temperature and sea ice concentration, observed variability from the MERRA-2 reanalysis is prescribed in the tropics and/or the Arctic through nudging of wind and temperature. These experiments reveal how a perfect prediction of tropical and/or Arctic variability in the model would impact the prediction of seasonal rainfall over the SWUS, at various time scales. Imposing tropical variability improves the representation of the observed North Pacific atmospheric circulation, and the associated SWUS seasonal precipitation. This is also the case at the subseasonal time scale due to the inclusion of the Madden-Julian Oscillation (MJO) in the model. When additional nudging is applied in the Arctic, the model skill improves even further, suggesting that improving seasonal predictions in high latitudes may also benefit prediction of SWUS precipitation. An interesting finding of our study is that subseasonal variability represents a source of noise (i.e., limited predictability) for the seasonal time scale. This is because when prescribed in the model, subseasonal variability, mostly the MJO, weakens the El Niño Southern Oscillation (ENSO) teleconnection with SWUS precipitation. Such knowledge may benefit S2S and seasonal prediction as it shows that depending on the amount of subseasonal activity in the tropics on a given year, better skill may be achieved in predicting subseasonal rather than seasonal rainfall anomalies, and conversely.

scholarly journals Inter-comparison of CO measurements from TROPOMI, ACE-FTS, and a high-Arctic ground-based FTS

2021 ◽  
Author(s):  
Tyler Wizenberg ◽  
Kimberly Strong ◽  
Kaley Walker ◽  
Erik Lutsch ◽  
Tobias Borsdorff ◽  
...  
Keyword(s):  
Satellite Data ◽  
Polar Region ◽  
High Arctic ◽  
Equatorial Region ◽  
The Arctic ◽  
Data Sets ◽  
Positive Bias ◽  
Clear Sky ◽  
Global Comparison ◽  
The Mean

Abstract. ACE/TROPOMI Abstract for AMT submission The TROPOspheric Monitoring Instrument (TROPOMI) provides a daily, spatially-resolved (initially 7 × 7 km2, upgraded to 7 × 5.6 km2 in August 2019) global data set of CO columns, however, due to the relative sparseness of reliable ground-based data sources, it can be challenging to characterize the validity and accuracy of satellite data products in remote regions such as the high Arctic. In these regions, satellite inter-comparisons can supplement model- and ground-based validation efforts and serve to verify previously observed differences. In this paper, we compare the CO products from TROPOMI, the Atmospheric Chemistry Experiment (ACE) Fourier Transform Spectrometer (FTS), and a high-Arctic ground-based FTS located at the Polar Environment Atmospheric Research Laboratory (PEARL) in Eureka, Nunavut (80.05° N, 86.42° W). A global comparison of TROPOMI reference profiles scaled by the retrieved total column with ACE-FTS CO partial columns for the period from 10 November 2017 to 31 May 2020 displays excellent agreement between the two data sets (R = 0.93), and a small relative bias of −0.68 ± 0.25 % (bias ± standard error). Additional comparisons were performed within five latitude bands; the north Polar region (60° N to 90° N), northern Mid-latitudes (20° N to 60° N), the Equatorial region (20° S to 20° N), southern Mid-latitudes (60° S to 20° S), and the south Polar region (90° S to 60° S). Latitudinal comparisons of the TROPOMI and ACE-FTS CO datasets show strong correlations ranging from R = 0.93 (southern Mid-latitudes) to R = 0.85 (Equatorial region) between the CO products, but display a dependence of the mean differences on latitude. Positive mean biases of 7.92 ± 0.58 % and 7.98 ± 0.51 % were found in the northern and southern Polar regions, respectively, while a negative bias of −9.16 ± 0.55 % was observed in the Equatorial region. To investigate whether these differences are introduced by cloud contamination which is reflected in the TROPOMI averaging kernel shape, the latitudinal comparisons were repeated for cloud-covered pixels and clear-sky pixels only, and for the unsmoothed and smoothed cases. Clear-sky pixels were found to be biased higher with poorer correlations on average than clear+cloudy scenes and cloud-covered scenes only. Furthermore, the latitudinal dependence on the biases was observed in both the smoothed and unsmoothed cases. To provide additional context to the global comparisons of TROPOMI with ACE-FTS in the Arctic, both satellite data sets were compared against measurements from the ground-based PEARL-FTS. Comparisons of TROPOMI with smoothed PEARL-FTS total columns in the period of 3 March 2018 to 27 March 2020 display a strong correlation (R = 0.88), however a positive mean bias of 14.3 ± 0.16 % was also found. A partial column comparison of ACE-FTS with the PEARL-FTS in the period from 25 February 2007 to 18 March 2020 shows good agreement (R = 0.82), and a mean positive bias of 9.83 ± 0.22 % in the ACE-FTS product relative to the ground-based FTS. The magnitude and sign of the mean relative differences are consistent across all inter-comparisons in this work, as well as with recent ground-based validation efforts, suggesting that current TROPOMI CO product exhibits a positive bias in the high-Arctic region. However, the observed bias is within the TROPOMI mission accuracy requirement of ±15 %, providing further confirmation that the data quality in these remote high-latitude regions meets this specification.

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