scholarly journals Cosmic rays linked to rapid mid-latitude cloud changes

2010 ◽  
Vol 10 (22) ◽  
pp. 10941-10948 ◽  
Author(s):  
B. A. Laken ◽  
D. R. Kniveton ◽  
M. R. Frogley
Keyword(s):  
Causal Relationship ◽  
General Circulation ◽  
Cloud Cover ◽  
Circulation Model ◽  
Cosmic Ray ◽  
Reanalysis Data ◽  
Short Term ◽  
Earth’S Climate ◽  
Relationship Of ◽  
Galactic Cosmic Ray

Abstract. The effect of the Galactic Cosmic Ray (GCR) flux on Earth's climate is highly uncertain. Using a novel sampling approach based around observing periods of significant cloud changes, a statistically robust relationship is identified between short-term GCR flux changes and the most rapid mid-latitude (60°–30° N/S) cloud decreases operating over daily timescales; this signal is verified in surface level air temperature (SLAT) reanalysis data. A General Circulation Model (GCM) experiment is used to test the causal relationship of the observed cloud changes to the detected SLAT anomalies. Results indicate that the anomalous cloud changes were responsible for producing the observed SLAT changes, implying that if there is a causal relationship between significant decreases in the rate of GCR flux (~0.79 GU, where GU denotes a change of 1% of the 11-year solar cycle amplitude in four days) and decreases in cloud cover (~1.9 CU, where CU denotes a change of 1% cloud cover in four days), an increase in SLAT (~0.05 KU, where KU denotes a temperature change of 1 K in four days) can be expected. The influence of GCRs is clearly distinguishable from changes in solar irradiance and the interplanetary magnetic field. However, the results of the GCM experiment are found to be somewhat limited by the ability of the model to successfully reproduce observed cloud cover. These results provide perhaps the most compelling evidence presented thus far of a GCR-climate relationship. From this analysis we conclude that a GCR-climate relationship is governed by both short-term GCR changes and internal atmospheric precursor conditions.

scholarly journals Cosmic rays linked to rapid mid-latitude cloud changes

2010 ◽  
Vol 10 (8) ◽  
pp. 18235-18253 ◽  
Author(s):  
B. A. Laken ◽  
D. R. Kniveton ◽  
M. R. Frogley
Keyword(s):  
Model Experiment ◽  
General Circulation ◽  
Cloud Cover ◽  
Circulation Model ◽  
Cosmic Ray ◽  
Reanalysis Data ◽  
Surface Level ◽  
Earth’S Climate ◽  
Relationship Of ◽  
Galactic Cosmic Ray

Abstract. The effect of the Galactic Cosmic Ray (GCR) flux on Earth's climate is highly uncertain. Using a novel sampling approach based around observing periods of significant cloud changes, a statistically robust relationship is identified between the rate of GCR flux and the most rapid mid-latitude (60°–30° N/S) cloud decreases operating over daily timescales; this signal is verified in surface level air temperature (SLAT) reanalysis data. A General Circulation Model experiment is used to test the causal relationship of the observed cloud changes to the detected SLAT anomalies. Results indicate that the cloud anomalies were responsible for producing the observed SLAT changes, implying a link between significant decreases in the rate of GCR flux (~0.79%/day (relative to the peak-to-peak amplitude of 11-yr solar cycle)), decreases in cloud cover (~1.9%/day) and increases in SLAT (~0.05 K/day). The influence of GCRs is clearly distinguishable from changes in solar irradiance and the interplanetary magnetic field. These results provide the most compelling evidence presented thus far of a GCR-climate relationship. From this analysis we conclude: (i) a GCR-climate relationship is governed by both the rate of GCR flux and internal precursor conditions; and (ii) it is likely that this natural forcing has not contributed significantly to recent anthropogenic temperature rises.

A comparison of catalogues of Forbush decreases identified from individual and a network of neutron monitors: a critical perspective

2021 ◽  
Vol 503 (4) ◽  
pp. 5675-5691
Author(s):  
O Okike ◽  
J A Alhassan ◽  
E U Iyida ◽  
A E Chukwude
Keyword(s):  
Cosmic Ray ◽  
Radiowave Propagation ◽  
Current Work ◽  
Survey Method ◽  
Critical Perspective ◽  
Short Term ◽  
Forbush Decreases ◽  
Academy Of Sciences ◽  
Galactic Cosmic Ray ◽  
Monitor Data

ABSTRACT Short-term rapid depressions in Galactic cosmic ray (GCR) flux, historically referred to as Forbush decreases (FDs), have long been recognized as important events in the observation of cosmic ray (CR) activity. Although theories and empirical results on the causes, characteristics, and varieties of FDs have been well established, detection of FDs, from either isolated detectors' or arrays of neutron monitor data, remains a subject of interest. Efforts to create large catalogues of FDs began in the 1990s and have continued to the present. In an attempt to test some of the proposed CR theories, several analyses have been conducted based on the available lists. Nevertheless, the results obtained depend on the FD catalogues used. This suggests a need for an examination of consistency between FD catalogues. This is the aim of the present study. Some existing lists of FDs, as well as FD catalogues developed in the current work, were compared, with an emphasis on the FD catalogues selected by the global survey method (GSM). The Forbush effects and interplanetary disturbances database (FEID), created by the Pushkov Institute of Terrestrial Magnetism, Ionosphere and Radiowave Propagation Russian Academy of Sciences (IZMIRAN), is the only available comprehensive and up to date FD catalogue. While there are significant disparities between the IZMIRAN FD and other event lists, there is a beautiful agreement between FDs identified in the current work and those in the FEID. This may be a pointer to the efficiency of the GSM and the automated approach to FD event detection presented here.

scholarly journals Utility of daily vs. monthly large-scale climate data: an intercomparison of two statistical downscaling methods

2007 ◽  
Vol 4 (5) ◽  
pp. 3413-3440 ◽  
Author(s):  
E. P. Maurer ◽  
H. G. Hidalgo
Keyword(s):  
Statistical Downscaling ◽  
General Circulation ◽  
Large Scale ◽  
Impact Analysis ◽  
Climate Model ◽  
Daily Precipitation ◽  
Circulation Model ◽  
Reanalysis Data ◽  
Temperature Extremes ◽  
Daily Data

Abstract. Downscaling of climate model data is essential to most impact analysis. We compare two methods of statistical downscaling to produce continuous, gridded time series of precipitation and surface air temperature at a 1/8-degree (approximately 140 km² per grid cell) resolution over the western U.S. We use NCEP/NCAR Reanalysis data from 1950–1999 as a surrogate General Circulation Model (GCM). The two methods included are constructed analogues (CA) and a bias correction and spatial downscaling (BCSD), both of which have been shown to be skillful in different settings, and BCSD has been used extensively in hydrologic impact analysis. Both methods use the coarse scale Reanalysis fields of precipitation and temperature as predictors of the corresponding fine scale fields. CA downscales daily large-scale data directly and BCSD downscales monthly data, with a random resampling technique to generate daily values. The methods produce comparable skill in producing downscaled, gridded fields of precipitation and temperatures at a monthly and seasonal level. For daily precipitation, both methods exhibit some skill in reproducing both observed wet and dry extremes and the difference between the methods is not significant, reflecting the general low skill in daily precipitation variability in the reanalysis data. For low temperature extremes, the CA method produces greater downscaling skill than BCSD for fall and winter seasons. For high temperature extremes, CA demonstrates higher skill than BCSD in summer. We find that the choice of most appropriate downscaling technique depends on the variables, seasons, and regions of interest, on the availability of daily data, and whether the day to day correspondence of weather from the GCM needs to be reproduced for some applications. The ability to produce skillful downscaled daily data depends primarily on the ability of the climate model to show daily skill.

scholarly journals Evaluation of Southern Ocean cloud in the HadGEM3 general circulation model and MERRA-2 reanalysis using ship-based observations

2020 ◽  
Vol 20 (11) ◽  
pp. 6607-6630 ◽  
Author(s):  
Peter Kuma ◽  
Adrian J. McDonald ◽  
Olaf Morgenstern ◽  
Simon P. Alexander ◽  
John J. Cassano ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Southern Ocean ◽  
General Circulation ◽  
Cloud Cover ◽  
Atmospheric Stability ◽  
Austral Summer ◽  
Circulation Model ◽  
Radiation Budget ◽  
Cloud Albedo ◽  
Low Cloud

Abstract. Southern Ocean (SO) shortwave (SW) radiation biases are a common problem in contemporary general circulation models (GCMs), with most models exhibiting a tendency to absorb too much incoming SW radiation. These biases have been attributed to deficiencies in the representation of clouds during the austral summer months, either due to cloud cover or cloud albedo being too low. The problem has been the focus of many studies, most of which utilised satellite datasets for model evaluation. We use multi-year ship-based observations and the CERES spaceborne radiation budget measurements to contrast cloud representation and SW radiation in the atmospheric component Global Atmosphere (GA) version 7.1 of the HadGEM3 GCM and the MERRA-2 reanalysis. We find that the prevailing bias is negative in GA7.1 and positive in MERRA-2. GA7.1 performs better than MERRA-2 in terms of absolute SW bias. Significant errors of up to 21 W m−2 (GA7.1) and 39 W m−2 (MERRA-2) are present in both models in the austral summer. Using ship-based ceilometer observations, we find low cloud below 2 km to be predominant in the Ross Sea and the Indian Ocean sectors of the SO. Utilising a novel surface lidar simulator developed for this study, derived from an existing Cloud Feedback Model Intercomparison Project (CFMIP) Observation Simulator Package (COSP) – active remote sensing simulator (ACTSIM) spaceborne lidar simulator, we find that GA7.1 and MERRA-2 both underestimate low cloud and fog occurrence relative to the ship observations on average by 4 %–9 % (GA7.1) and 18 % (MERRA-2). Based on radiosonde observations, we also find the low cloud to be strongly linked to boundary layer atmospheric stability and the sea surface temperature. GA7.1 and MERRA-2 do not represent the observed relationship between boundary layer stability and clouds well. We find that MERRA-2 has a much greater proportion of cloud liquid water in the SO in austral summer than GA7.1, a likely key contributor to the difference in the SW radiation bias. Our results suggest that subgrid-scale processes (cloud and boundary layer parameterisations) are responsible for the bias and that in GA7.1 a major part of the SW radiation bias can be explained by cloud cover underestimation, relative to underestimation of cloud albedo.

scholarly journals An efficient method to generate a perturbed parameter ensemble of a fully coupled AOGCM without flux-adjustment

2013 ◽  
Vol 6 (5) ◽  
pp. 1447-1462 ◽  
Author(s):  
P. J. Irvine ◽  
L. J. Gregoire ◽  
D. J. Lunt ◽  
P. J. Valdes
Keyword(s):  
General Circulation ◽  
Circulation Model ◽  
Parametric Uncertainty ◽  
Ocean General Circulation Model ◽  
Reanalysis Data ◽  
Entrainment Rate ◽  
Industrial Control ◽  
Simple Method ◽  
Fully Coupled ◽  
Flux Adjustment

Abstract. We present a simple method to generate a perturbed parameter ensemble (PPE) of a fully-coupled atmosphere-ocean general circulation model (AOGCM), HadCM3, without requiring flux-adjustment. The aim was to produce an ensemble that samples parametric uncertainty in some key variables and gives a plausible representation of the climate. Six atmospheric parameters, a sea-ice parameter and an ocean parameter were jointly perturbed within a reasonable range to generate an initial group of 200 members. To screen out implausible ensemble members, 20 yr pre-industrial control simulations were run and members whose temperature responses to the parameter perturbations were projected to be outside the range of 13.6 ± 2 °C, i.e. near to the observed pre-industrial global mean, were discarded. Twenty-one members, including the standard unperturbed model, were accepted, covering almost the entire span of the eight parameters, challenging the argument that without flux-adjustment parameter ranges would be unduly restricted. This ensemble was used in 2 experiments; an 800 yr pre-industrial and a 150 yr quadrupled CO2 simulation. The behaviour of the PPE for the pre-industrial control compared well to ERA-40 reanalysis data and the CMIP3 ensemble for a number of surface and atmospheric column variables with the exception of a few members in the Tropics. However, we find that members of the PPE with low values of the entrainment rate coefficient show very large increases in upper tropospheric and stratospheric water vapour concentrations in response to elevated CO2 and one member showed an implausible nonlinear climate response, and as such will be excluded from future experiments with this ensemble. The outcome of this study is a PPE of a fully-coupled AOGCM which samples parametric uncertainty and a simple methodology which would be applicable to other GCMs.

Statistical downscaling of general circulation model outputs to precipitation, evaporation and temperature using a key station approach

2016 ◽  
Vol 7 (4) ◽  
pp. 683-707
Author(s):  
D. A. Sachindra ◽  
F. Huang ◽  
A. Barton ◽  
B. J. C. Perera
Keyword(s):  
General Circulation Model ◽  
Statistical Downscaling ◽  
General Circulation ◽  
Emission Scenario ◽  
Circulation Model ◽  
Reanalysis Data ◽  
Maximum Temperature ◽  
Monthly Precipitation ◽  
Regression Equations ◽  
Highly Correlated

Using a key station approach, statistical downscaling of monthly general circulation model outputs to monthly precipitation, evaporation, minimum temperature and maximum temperature at 17 observation stations located in Victoria, Australia was performed. Using the observations of each predictand, over the period 1950–2010, correlations among all stations were computed. For each predictand, the station which showed the highest number of correlations above 0.80 with other stations was selected as the first key station. The stations that were highly correlated with that key station were considered as the member stations of the first cluster. By employing this same procedure on the remaining stations, the next key station was found. This procedure was performed until all stations were segregated into clusters. Thereafter, using the observations of each predictand, regression equations (inter-station regression relationships) were developed between the key stations and the member stations for each calendar month. The downscaling models at the key stations were developed using reanalysis data as inputs to them. The outputs of HadCM3 pertaining to A2 emission scenario were introduced to these downscaling models to produce projections of the predictands over the period 2000–2099. Then the outputs of these downscaling models were introduced to the inter-station regression relationships to produce projections of predictands at all member stations.

scholarly journals Changes in the Global Sulfate Burden due to Perturbations in Global CO2 Concentrations

2009 ◽  
Vol 22 (20) ◽  
pp. 5421-5432 ◽  
Author(s):  
Duncan Ackerley ◽  
Eleanor J. Highwood ◽  
David J. Frame ◽  
Ben B. B. Booth
Keyword(s):  
General Circulation ◽  
Cloud Cover ◽  
Circulation Model ◽  
Ocean Model ◽  
Sulfur Cycle ◽  
Sulfate Aerosol ◽  
Climate Response ◽  
Carbon Dioxide Co2 ◽  
Sulfur Emissions ◽  
Global Mean

Abstract A large ensemble of general circulation model (GCM) integrations coupled to a fully interactive sulfur cycle scheme were run on the climateprediction.net platform to investigate the uncertainty in the climate response to sulfate aerosol and carbon dioxide (CO2) forcing. The sulfate burden within the model (and the atmosphere) depends on the balance between formation processes and deposition (wet and dry). The wet removal processes for sulfate aerosol are much faster than dry removal and so any changes in atmospheric circulation, cloud cover, and precipitation will feed back on the sulfate burden. When CO2 is doubled in the Hadley Centre Slab Ocean Model (HadSM3), global mean precipitation increased by 5%; however, the global mean sulfate burden increased by 10%. Despite the global mean increase in precipitation, there were large areas of the model showing decreases in precipitation (and cloud cover) in the Northern Hemisphere during June–August, which reduced wet deposition and allowed the sulfate burden to increase. Further experiments were also undertaken with and without doubling CO2 while including a future anthropogenic sulfur emissions scenario. Doubling CO2 further enhanced the increases in sulfate burden associated with increased anthropogenic sulfur emissions as observed in the doubled CO2-only experiment. The implications are that the climate response to doubling CO2 can influence the amount of sulfate within the atmosphere and, despite increases in global mean precipitation, may act to increase it.

scholarly journals Effect of retreating sea ice on Arctic cloud cover in simulated recent global warming

2016 ◽  
Author(s):  
Manabu Abe ◽  
Toru Nozawa ◽  
Tomoo Ogura ◽  
Kumiko Takata
Keyword(s):  
Global Warming ◽  
Sea Ice ◽  
General Circulation ◽  
Cloud Cover ◽  
Lower Troposphere ◽  
Circulation Model ◽  
Arctic Sea Ice ◽  
Thin Layers ◽  
Downward Longwave Radiation ◽  
Sea Ice Reduction

Abstract. This study investigates the effect of sea ice reduction on Arctic cloud cover in historical simulations with the coupled Atmosphere-Ocean general circulation model MIROC5. Arctic sea ice has been shown to exhibit substantial reductions under simulated global warming conditions since the 1970s, particularly in September. This simulated reduction is consistent with satellite observation results. However, Arctic cloud cover increases significantly during October, leading to extensive reductions in sea ice because of the enhanced heat and moisture fluxes from the underlying ocean. Sensitivity experiments with the atmospheric model MIROC5 clearly show that sea ice reduction causes increased cloud cover. Increased cloud cover occurs primarily in the lower troposphere; however, clouds in the thin surface layers directly above the ocean decrease despite the increased moisture flux because the surface air temperature rises in these thin layers, causing the relative humidity to decrease. As cloud cover increases, the cloud radiative effect cause an increase in the surface downward longwave radiation (DLR) by approximately 40–60 % compared with changes in clear-sky surface DLR in fall. These results suggest that an increase in Arctic cloud cover as a result of reduced sea ice coverage may further melt the sea ice and enhance the feedback processes of Arctic warming.

Present-Day Atmospheric Simulations Using GISS ModelE: Comparison to In Situ, Satellite, and Reanalysis Data

2006 ◽  
Vol 19 (2) ◽  
pp. 153-192 ◽  
Author(s):  
Gavin A. Schmidt ◽  
Reto Ruedy ◽  
James E. Hansen ◽  
Igor Aleinov ◽  
Nadine Bell ◽  
...  
Keyword(s):  
General Circulation ◽  
Circulation Model ◽  
Reanalysis Data ◽  
Full Description ◽  
Marine Stratocumulus ◽  
Sea Level Pressure ◽  
In Situ Data ◽  
Basic Physics ◽  
Goddard Institute

Abstract A full description of the ModelE version of the Goddard Institute for Space Studies (GISS) atmospheric general circulation model (GCM) and results are presented for present-day climate simulations (ca. 1979). This version is a complete rewrite of previous models incorporating numerous improvements in basic physics, the stratospheric circulation, and forcing fields. Notable changes include the following: the model top is now above the stratopause, the number of vertical layers has increased, a new cloud microphysical scheme is used, vegetation biophysics now incorporates a sensitivity to humidity, atmospheric turbulence is calculated over the whole column, and new land snow and lake schemes are introduced. The performance of the model using three configurations with different horizontal and vertical resolutions is compared to quality-controlled in situ data, remotely sensed and reanalysis products. Overall, significant improvements over previous models are seen, particularly in upper-atmosphere temperatures and winds, cloud heights, precipitation, and sea level pressure. Data–model comparisons continue, however, to highlight persistent problems in the marine stratocumulus regions.

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