Internal variability of surface solar radiation and associated PV production

2020 ◽  
Author(s):  
Doris Folini
Keyword(s):  
Solar Radiation ◽  
Coupled Model ◽  
Internal Variability ◽  
Industrial Control ◽  
Surface Solar Radiation ◽  
Decadal Scale ◽  
Intercomparison Project ◽  
Analytical Relations ◽  
Average Uncertainty

<p>Results on the statistical properties of internal variability of annual mean surface solar radiation (SSR) and associated decadal scale trends are presented, following in part Folini et al. 2017 (doi:10.1002/2016JD025869). Estimates are based on 43 pre-industrial control (piControl) experiments of the Coupled Model Intercomparison Project Phase 5 (CMIP5). Trends are shown to depend strongly on geographical region and on whether they are quantified in absolute units or relative to the long term mean SSR. Providing one map for absolute and one map for relative trends is sufficient, as approximate analytical relations are shown to hold between trends of different length and likelihood and the standard deviation of the underlying SSR time series. Comparison with present-day observations and inter-model spread suggest an average uncertainty of these estimates of about 30%.  Intermodel spread suggests that regional uncertainties can be up to about three times larger or smaller. Using the model by Crook et al. 2011 (doi:10.1039/C1EE01495A) to translate SSR into PV production, associated internal variability of photo voltaic (PV) energy production is inferred. Results suggest that it is plausible for PV production to change by several per cent over a decade just because of internal variability.</p>

Long-term variations of surface solar radiation in China from routine meteorological observations

2021 ◽  
pp. 105715
Author(s):  
Xuefang Yang ◽  
Wenmin Qin ◽  
Lunche Wang ◽  
Ming Zhang ◽  
Zigeng Niu
Keyword(s):  
Solar Radiation ◽  
Surface Solar Radiation ◽  
Meteorological Observations ◽  
Long Term Variations

Estimation and Long-term Trend Analysis of Surface Solar Radiation in Antarctica: A Case Study of Zhongshan Station

2021 ◽  
Author(s):  
Zhaoliang Zeng ◽  
Zemin Wang ◽  
Minghu Ding ◽  
Xiangdong Zheng ◽  
Xiaoyu Sun ◽  
...  
Keyword(s):  
Solar Radiation ◽  
Trend Analysis ◽  
Surface Solar Radiation ◽  
Term Trend ◽  
Zhongshan Station ◽  
Long Term Trend

Anthropogenic and Natural Contributions to the Lengthening of the Summer Season in the Northern Hemisphere

2018 ◽  
Vol 31 (17) ◽  
pp. 6803-6819 ◽  
Author(s):  
Bo-Joung Park ◽  
Yeon-Hee Kim ◽  
Seung-Ki Min ◽  
Eun-Pa Lim
Keyword(s):  
Northern Hemisphere ◽  
Coupled Model ◽  
Atlantic Multidecadal Oscillation ◽  
Summer Season ◽  
Season Length ◽  
The Past ◽  
External Forcings ◽  
Regional Trends ◽  
Intercomparison Project

Observed long-term variations in summer season timing and length in the Northern Hemisphere (NH) continents and their subregions were analyzed using temperature-based indices. The climatological mean showed coastal–inland contrast; summer starts and ends earlier inland than in coastal areas because of differences in heat capacity. Observations for the past 60 years (1953–2012) show lengthening of the summer season with earlier summer onset and delayed summer withdrawal across the NH. The summer onset advance contributed more to the observed increase in summer season length in many regions than the delay of summer withdrawal. To understand anthropogenic and natural contributions to the observed change, summer season trends from phase 5 of the Coupled Model Intercomparison Project (CMIP5) multimodel simulations forced with the observed external forcings [anthropogenic plus natural forcing (ALL), natural forcing only (NAT), and greenhouse gas forcing only (GHG)] were analyzed. ALL and GHG simulations were found to reproduce the overall observed global and regional lengthening trends, but NAT had negligible trends, which implies that increased greenhouse gases were the main cause of the observed changes. However, ALL runs tend to underestimate the observed trend of summer onset and overestimate that of withdrawal, the causes of which remain to be determined. Possible contributions of multidecadal variabilities, such as Pacific decadal oscillation and Atlantic multidecadal oscillation, to the observed regional trends in summer season length were also assessed. The results suggest that multidecadal variability can explain a moderate portion (about ±10%) of the observed trends in summer season length, mainly over the high latitudes.

scholarly journals Long-term Surface Temperature (LoST) database as a complement for GCM preindustrial simulations

2019 ◽  
Vol 15 (3) ◽  
pp. 1099-1111 ◽  
Author(s):  
Francisco José Cuesta-Valero ◽  
Almudena García-García ◽  
Hugo Beltrami ◽  
Eduardo Zorita ◽  
Fernando Jaume-Santero
Keyword(s):  
Surface Temperature ◽  
General Circulation ◽  
Ground Surface ◽  
Coupled Model ◽  
Circulation Model ◽  
Research Unit ◽  
Large Spread ◽  
Intercomparison Project ◽  
Past Millennium

Abstract. Estimates of climate sensitivity from general circulation model (GCM) simulations still present a large spread despite the continued improvements in climate modeling since the 1970s. This variability is partially caused by the dependence of several long-term feedback mechanisms on the reference climate state. Indeed, state-of-the-art GCMs present a large spread of control climate states probably due to the lack of a suitable reference for constraining the climatology of preindustrial simulations. We assemble a new gridded database of long-term ground surface temperatures (LoST database) obtained from geothermal data over North America, and we explore its use as a potential reference for the evaluation of GCM preindustrial simulations. We compare the LoST database with observations from the Climate Research Unit (CRU) database, as well as with five past millennium transient climate simulations and five preindustrial control simulations from the third phase of the Paleoclimate Modelling Intercomparison Project (PMIP3) and the fifth phase of the Coupled Model Intercomparison Project (CMIP5). The database is consistent with meteorological observations as well as with both types of preindustrial simulations, which suggests that LoST temperatures can be employed as a reference to narrow down the spread of surface temperature climatologies on GCM preindustrial control and past millennium simulations.

The Double-ITCZ Bias in CMIP6 Models

2020 ◽  
Author(s):  
Baijun Tian
Keyword(s):  
Climate Models ◽  
Global Climate ◽  
Coupled Model ◽  
Global Climate Models ◽  
Cmip5 Models ◽  
Tropical Precipitation ◽  
Double Itcz ◽  
Intercomparison Project ◽  
Fully Coupled

<p>The double-Intertropical Convergence Zone (ITCZ) bias is one of the most outstanding problems in climate models. This study seeks to examine the double-ITCZ bias in the latest state-of-the-art fully coupled global climate models that participated in Coupled Model Intercomparison Project (CMIP) Phase 6 (CMIP6) in comparison to their previous generations (CMIP3 and CMIP5 models). To that end, we have analyzed the long-term annual mean tropical precipitation distributions and several precipitation bias indices that quantify the double-ITCZ biases in 75 climate models including 24 CMIP3 models, 25 CMIP3 models, and 26 CMIP6 models. We find that the double-ITCZ bias and its big inter-model spread persist in CMIP6 models but the double-ITCZ bias is slightly reduced from CMIP3 or CMIP5 models to CMIP6 models.</p>

Using Modified Sandia Method in Developing Typical Solar Radiation Year for Photovoltaic Electricity Generation Projection

2011 ◽  
Vol 71-78 ◽  
pp. 4374-4381 ◽  
Author(s):  
Kuo Tsang Huang ◽  
Wen Sheng Ou
Keyword(s):  
Solar Radiation ◽  
Electricity Generation ◽  
Meteorological Data ◽  
Global Solar Radiation ◽  
Climate Variations ◽  
Surface Solar Radiation ◽  
Estimation Process ◽  
Pv Panel ◽  
Southern Taiwan

The energy generation efficiency of Building Intergraded Photovoltaic Systems (BIPV) system relies much on the panel’s surface solar radiation received. In the projection of annual power generation of photovoltaic panels, local global solar radiation plays a pivotal role for reliable estimation process. The purpose of this paper is to develop an hourly typical solar radiation year (TSRY) as fundamental meteorological database for utilizing the estimation process. The TSRY should be interpretable to local long-term climate variations, thus, ten years' hourly meteorological data were gathered to formulate a typical year by means of modified Sandia method herein. A total of four cities' hourly typical years from northern to southern Taiwan were established in this paper. Orientation and inclination effect of the PV panel were also discussed in terms of daily averaged global solar radiation that cumulate from TSRY.

Observational and Model Estimates of Cloud Amount Feedback over the Indian and Pacific Oceans

2014 ◽  
Vol 27 (2) ◽  
pp. 925-940 ◽  
Author(s):  
Katinka Bellomo ◽  
Amy C. Clement ◽  
Joel R. Norris ◽  
Brian J. Soden
Keyword(s):  
Coupled Model ◽  
Cloud Amount ◽  
Western Indian Ocean ◽  
Model Intercomparison ◽  
Central Pacific ◽  
Radiative Impact ◽  
Southern Central ◽  
Intercomparison Project ◽  
Very High

AbstractConstraining intermodel spread in cloud feedback with observations is problematic because available cloud datasets are affected by spurious behavior in long-term variability. This problem is addressed by examining cloud amount in three independent ship-based [Extended Edited Cloud Reports Archive (EECRA)] and satellite-based [International Satellite Cloud Climatology Project (ISCCP) and Advanced Very High Resolution Radiometer Pathfinder Atmosphere–Extended (PATMOS-X)] observational datasets, and models from phase 5 of the Coupled Model Intercomparison Project (CMIP5). The three observational datasets show consistent cloud variability in the overlapping years of coverage (1984–2007). The long-term cloud amount change from 1954 to 2005 in ship-based observations shares many of the same features with the multimodel mean cloud amount change of 42 CMIP5 historical simulations, although the magnitude of the multimodel mean is smaller. The radiative impact of cloud changes is estimated by computing an observationally derived estimate of cloud amount feedback. The observational estimates of cloud amount feedback are statistically significant over four regions: the northeast Pacific subtropical stratocumulus region and equatorial western Pacific, where cloud amount feedback is found to be positive, and the southern central Pacific and western Indian Ocean, where cloud amount feedback is found to be negative. Multimodel mean cloud amount feedback is consistent in sign but smaller in magnitude than in observations over these four regions because models simulate weaker cloud changes. Individual models, however, can simulate cloud amount feedback of the same magnitude if not larger than observed. Focusing on the regions where models and observations agree can lead to improved understanding of the mechanisms of cloud amount changes and associated radiative impact.

scholarly journals Reduced complexity model intercomparison project phase 1: Protocol, results and initial observations

2020 ◽  
Author(s):  
Zebedee R. J. Nicholls ◽  
Malte Meinshausen ◽  
Jared Lewis ◽  
Robert Gieseke ◽  
Dietmar Dommenget ◽  
...  
Keyword(s):  
Radiative Forcing ◽  
Climate Models ◽  
Phase 1 ◽  
Coupled Model ◽  
Surface Air Temperature ◽  
Internal Variability ◽  
Second Phase ◽  
Model Intercomparison ◽  
Intercomparison Project ◽  
Reduced Complexity

Abstract. Here we present results from the first phase of the Reduced Complexity Model Intercomparison Project (RCMIP). RCMIP is a systematic examination of reduced complexity climate models (RCMs), which are used to complement and extend the insights from more complex Earth System Models (ESMs), in particular those participating in the Sixth Coupled Model Intercomparison Project (CMIP6). In Phase 1 of RCMIP, with 14 participating models namely ACC2, AR5IR (2 and 3 box versions), CICERO-SCM, ESCIMO, FaIR, GIR, GREB, Hector, Held et al. two layer model, MAGICC, MCE, OSCAR and WASP, we highlight the structural differences across various RCMs and show that RCMs are capable of reproducing global-mean surface air temperature (GSAT) changes of ESMs and historical observations. We find that some RCMs are capable of emulating the GSAT response of CMIP6 models to within a root-mean square error of 0.2 °C (of the same order of magnitude as ESM internal variability) over a range of scenarios. Running the same model configurations for both RCP and SSP scenarios, we see that the SSPs exhibit higher effective radiative forcing throughout the second half of the 21st Century. Comparing our results to the difference between CMIP5 and CMIP6 output, we find that the change in scenario explains approximately 46 % of the increase in higher end projected warming between CMIP5 and CMIP6. This suggests that changes in ESMs from CMIP5 to CMIP6 explain the rest of the increase, hence the higher climate sensitivities of available CMIP6 models may not be having as large an impact on GSAT projections as first anticipated. A second phase of RCMIP will complement RCMIP Phase 1 by exploring probabilistic results and emulation in more depth to provide results available for the IPCC's Sixth Assessment Report author teams.

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