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application/pdf, International Journal of Biometeorology. 2022, 66 (5), P.883-893

A speleothem record from the north-eastern Yucatán peninsula (Mexico) provides new insights into the tropical hydro-climate of the Americas between 11,040 and 9520 a BP on up to sub-decadal scale. Despite the complex atmospheric reorganization during the end of the last deglaciation, the dominant internal leading modes of precipitation variability during the late Holocene were also active during the time of record. While multi-decadal variations were not persistent, Mesoamerican precipitation was dominated by changes on the decadal- and centennial scale, which may be attributed to ENSO activity driven by solar forcing. Freshwater fluxes from the remnant Laurentide ice sheet into the Gulf of Mexico and the North Atlantic have additionally modulated the regional evaporation/precipitation balance. In particular, this study underlines the importance of solar activity on tropical and subtropical climate variability through forcing of the tropical Pacific, providing a plausible scenario for observed recurrent droughts on the decadal scale throughout the Holocene.

The Indian Ocean Dipole (IOD) is a major mode of interannual climate variability, but its response to external climate forcings (i.e. solar forcing, volcanic radiative forcing (VRF) and greenhouse gas (GHG) radiative forcing) remains elusive. To improve our understanding of the variability of the IOD, it is necessary to investigate the IOD’s response to external forcings through multi-model simulations. Here a Granger causality test is used to examine the impact of external forcings on the IOD from past 1000 years simulations (850–1850 Common Era) derived from Coupled Model Intercomparison Project Phase 5 (CMIP5) models. The results show significant causal effects of VRF on the IOD in preindustrial times of the past 1000 years from the MPI-ESM-P, MRI-CGCM3, GISS-E2-R and CCSM4 models and uncertainties in the IOD’s responses to volcanic eruptions from other six models. Additionally, the phase responses (i.e. positive or negative) of the IOD to large volcanic eruptions remain unclear even from models showing significant causal impacts of VRF on the IOD. This result shows that the IOD exhibits a more complex response to volcanic forcing than the El Niño-Southern Oscillation. The causal impact of solar forcing on the IOD is more likely to be weak in most models. The IOD’s response to GHG variations is not significant across all the models due to minor fluctuations in GHGs occurring during preindustrial times of the past 1000 years. Further analyses based on new, improved and higher resolution models might further our understanding of the IOD’s responses to external forcing.

Bipolar magnetic regions (BMRs) are the corner-stone of solar variability. They are tracers of the large-scale magnetic processes that give rise to the solar cycle, shapers of the solar corona, building blocks of the large-scale solar magnetic field, and significant contributors to the free-energetic budget that gives rise to flares and coronal mass ejections. Surprisingly, no homogeneous catalog of BMRs exists today, in spite of the existence of systematic measurements of the magnetic field since the early 1970's. The purpose of this work is to address this deficiency by creating a homogenous catalog of BMRs from the 1970's until the present. For this purpose, in this paper we discuss the strengths and weaknesses of the automatic and manual detection of BMRs and how both methods can be combined to form the basis of our Bipolar Active Region Detection (BARD) code and its supporting human supervision module. At present, the BARD catalog contains more than 10,000 unique BMRs tracked and characterized during every day of their observation. Here we also discuss our future plans for the creation of an extended multi-scale magnetic catalog combining the SWAMIS and BARD catalogs.

Muons and neutrons are representative secondary particles that are generated by interactions between primary cosmic ray particles (mostly protons) and the nuclei of atmospheric gas compounds. Previous studies reported that muons experience seasonal variations because of the meteorological effects of temperature. The intensity of neutrons has a typical modulation with various periods and reasons, such as diurnal and solar variation or transient events. This paper reports that cosmic ray particles, which were observed by neutron monitors, have seasonal variations using the daily data at the Oulu neutron monitor. To eliminate the effects of solar activity across time, the daily data were normalized by two different transformations: transformations with respect to the grand mean and yearly mean. The data after transformation with respect to the yearly mean showed more statistical stability and clear seasonal variations. On the other hand, it is difficult to determine if the seasonal variation results from terrestrial effects, such as meteorological factors, or extraterrestrial effects, such as the position of the Earth in its orbit of revolution.

Satellite measurements over the last three decades show a gradual decrease in solar output, which can be indicative as a precursor to a modern grand solar minimum (GSM). Using a chemistry–climate model, this study investigates the potential of two GSM scenarios with different magnitude to counteract the climate change by projected anthropogenic greenhouse gas (GHG) emissions through the twenty-first century. To identify regions showing enhanced vulnerability to climate change (hot spots) and to estimate their response to a possible modern GSM, a multidimensional metric is applied that accounts for—in addition to changes in mean quantities—seasonal changes in the variability and occurrence of extreme events. We find that a future GSM in the middle of the twenty-first century would temporarily mitigate the global mean impact of anthropogenic climate change by 10%–23% depending on the GSM scenario. A future GSM would, however, not be able to stop anthropogenic global warming. For the GHG-only scenario, our hot-spot analysis suggests that the midlatitudes show a response to rising GHGs below global average, while in the tropics, climate change hot spots with more frequent extreme hot seasons will develop during the twenty-first century. A GSM would reduce the climate change warming in all regions. The GHG-induced warming in Arctic winter would be dampened in a GSM due to the impact of reduced solar irradiance on Arctic sea ice. However, even an extreme GSM could only mitigate a fraction of the tropical hot-spot pattern (up to 24%) in the long term.

In present work we analysed eight geomagnetic storm events in 2015/2016 and studied the possible influence of these events on Ethiopian power grids. The results showed that the majority of the forced power outages occurred in the period of the main phase of events and the recovery period of the geomagnetic storms. The geomagnetic storms are characterised by different indices and parameters such as the disturbance storm time (Dst) values, coronal mass ejection (CME) speed, solar wind speed (V sw) and interplanetary magnetic field (IMF-Bz) on the selected dates. In most cases the observed geomagnetic storms were produced by the CME-driven storms as they show a storm sudden commencement (SSCs) before the main storms, and also have the short recovery periods. The sudden jumps of the solar wind velocities and IMF-Bz are also consistent with occurrence of the CMEs. Moreover, this effect can be traced in changes of Earth magnetic field during geomagnetic storm and quiet days. The observed CME-driven storms can produce highly variable magnetic fields on the transformers and provide forced outages, however the studied outages have not been recognised as those one driven by a geomagnetic storm.

The stability and longevity of the Ozone Monitoring Instrument (OMI), flying on board the (active) Aura Earth‐observing satellite since July 2004, facilitates creation of accurate, long‐term record of relative (normalized to a solar minimum) solar spectral irradiances (SSIs). Here we discuss technical details of the most recent version (V3) of the SSI product that provides approximately daily measurements for the period July 2006 to April 2018 in the 265‐ to 500‐nm domain with average 0.5‐nm resolution. We compare OMI SSIs with concurrent independent observations and model estimates. The short‐term (solar rotational cycle) observations and model predictions mostly agree to ∼0.1–0.2% in the ultraviolet domain, with an excellent, down to ∼0.01% agreement in the visible range. The long‐term (solar cycle) comparisons pose more challenges in the ultraviolet domain, where the differences between observations and models frequently exceed the rather conservative ∼0.1% (both point‐to‐point and long‐term) OMI uncertainties. In the visible range, these differences gradually diminish to

Whole atmosphere chemistry‐climate model (CCM) transient studies require a solar spectral irradiance (SSI) time series with very broad wavelength coverage with an uninterrupted daily cadence over a full solar cycle time period. Herein is described the construction of a SSI record valid over Solar Cycles 23 and 24 (SC23 and SC24) specifically designed to provide: (1) a daily solar spectrum from SORCE (Solar Radiation and Climate Experiment) observations from 208–2400 nm over the 2003 to 2015 time frame, (2) a wavelength extension of this spectrum out to 10000 nm from daily spectral synthesis from the Solar Radiation Physical Model (SRPM), (3) SRPM gap‐filled spectra during the extended SORCE safe‐hold time period (Aug 2013–March 2014) and back to Solar Cycle 23 maximum conditions in 2001 and 2002, (4) analysis of solar images generated by the Precision Solar Photometric Telescope (PSPT) network from the Mauna Loa Solar Observatory (MLSO) and Rome Observatory (OAR) (These images act both as input to the SRPM model and as a stand‐alone proxy of solar variability.), (5) documentation of uncertainties and biases in the time series as a function of wavelength, and (6) comparative analysis of the SORCE time series with SRPM over the full wavelength range of the data set.

Theory and model evidence indicate a higher global hydrological sensitivity for the same amount of surface warming to solar as to greenhouse gas (GHG) forcing, but regional patterns are highly uncertain due to their dependence on circulation and dynamics. We analyse a multi-model ensemble of idealized experiments and a set of simulations of the last millennium and we demonstrate similar global signatures and patterns of forced response in the tropical Pacific, of higher sensitivity for the solar forcing. In the idealized simulations, both solar and GHG forcing warm the equatorial Pacific, enhance precipitation in the central Pacific, and weaken and shift the Walker circulation eastward. Centennial variations in the solar forcing over the last millennium cause similar patterns of enhanced equatorial precipitation and slowdown of the Walker circulation in response to periods with stronger solar forcing. Similar forced patterns albeit of considerably weaker magnitude are identified for variations in GHG concentrations over the 20th century, with the lower sensitivity explained by fast atmospheric adjustments. These findings differ from previous studies that have typically suggested divergent responses in tropical precipitation and circulation between the solar and GHG forcings. We conclude that tropical Walker circulation and precipitation might be more susceptible to solar variability rather than GHG variations during the last-millennium, assuming comparable global mean surface temperature changes.

Previous studies have reported that human influences are required to explain the observed global warming using a linear model (LM) ΔT=λLMΔF that relates change in solar forcing ΔF to change in global mean temperature (GMT) ΔT. This model has the shortcoming of assuming a given ΔF causes the same ΔT irrespective of the value of the initial global warming rate (dT/dy)i. Analysis of the GMT data showed that this warming rate has been increasing linearly since steady state ((dT/dy)o=0 for year yo=1864.5) as given by dT/dy=(dT/dy)i+aT(y−yi), where aT=7.1954×10−5 °C/year2 is the secular GMT acceleration and y−yi is the number of years of the change. The secular solar forcing due to 18% of the 11 yr solar cycle forcing of 0.19 W/m2 (0.08% of Total Solar Irradiance) was expressed as ΔF=0.18×0.19(y−yi)/11. Defining the climate sensitivity as λ=Δ(dT/dy)/ΔF=aT/(0.18×0.19/11)=0.023143 °C/year per W/m2 removed the shortcoming of the LM and integration of the model for dT/dy above and then simplifying gave a secular GMT‐solar forcing model given by ΔT=(dT/dy)i(y−yi)+(λ2/(2aT))(ΔF)2 that explained all of the observed global warming and increase in atmospheric CO2, sea level and ocean heat content. Therefore, for this nonlinear empirical model, invoking human influences to explain climate change was not required. The annual GMT model predicts a pause in global warming until 2040.

The final version (V.19) of the total solar irradiance data from the SOlar Radiation and Climate Experiment (SORCE) Total Irradiance Monitor has been released. This version includes all calibrations updated to the end of the mission and provides irradiance data from 25 February 2003 through 25 February 2020. These final calibrations are presented along with the resulting final data products. An overview of the on-orbit operations timeline is provided as well as the associated changes in the time-dependent uncertainties. Scientific highlights from the instrument are also presented. These include the establishment of a new, lower TSI value; accuracy improvements to other TSI instruments via a new calibration facility; the lowest on-orbit noise (for high sensitivity to solar variability) of any TSI instrument; the best inherent stability of any on-orbit TSI instrument; a lengthy (17-year) measurement record benefitting from these stable, low-noise measurements; the first reported detection of a solar flare in TSI; and observations of two Venus transits and four Mercury transits.

In this study, we investigate the associations between the solar variability and teleconnection indices, which influence atmospheric circulation and subsequently, the spatial distribution of the global pressure system. A study of the link between the Sun and a large-scale mode of climate variability, which may indirectly affect the Earth’s climate and weather, is crucial because the feedbacks of solar variability to an autogenic or internal process should be considered with due care. We have calculated the normalized cross-correlations of the total sunspot area, the total sunspot number, and the solar North–South asymmetry with teleconnection indices. We have found that the Southern Oscillation Index (SOI) index is anti-correlated with both solar activity and the solar North–South asymmetry, with a ∼3-year lag. This finding not only agrees with the fact that El Niño episodes are likely to occur around the solar maximum, but also explains why tropical cyclones occurring in the solar maximum periods and in El Niño periods appear similar. Conversely, other teleconnection indices, such as the Arctic Oscillation (AO) index, the Antarctic Oscillation (AAO) index, and the Pacific-North American (PNA) index, are weakly or only slightly correlated with solar activity, which emphasizes that response of terrestrial climate and weather to solar variability are local in space. It is also found that correlations between teleconnection indices and solar activity are as good as correlations resulting from the teleconnection indices themselves.

This work presents a flowsheet superstructure and integration possibilities for simultaneous optimization of the maximum share of attainable direct and indirect solar utilization through heat storage in industrial operations. Multi-period Mixed Integer Non-Linear Programming (MINLP) models were developed for this purpose and account for the dynamics in the profile of heat supply and demand using discrete time intervals/periods. The resulting models are applied to an industrial case study of a dairy plant for the two distinct integration alternatives of targeting one and multiple (two) cold stream utility requirements. The design and optimization of the integrated system is implemented and solved in GAMS. The results show good prospect for solar thermal utilization in industries with low temperature applications. Sensitivity analysis shows linear increase in the average attainable heat load up to certain collector area (on case-by-case basis), after which a break point is obtained where it is observed that additional increase in collector area does not result to much increase in the obtained heat load. For the selected case study of a dairy plant, average solar output of about 75 W/m2 of collector is obtained.

Ocean circulation responses to interhemispheric radiative imbalance can damp north–south migrations of the intertropical convergence zone (ITCZ) by reducing the burden on atmospheric energy transport. The role of the Atlantic meridional overturning circulation (AMOC) in such dynamics has not received much attention. Here, we present coupled climate modeling results that suggest AMOC responses are of first-order importance to muting ITCZ shift magnitudes as a pair of hemispherically asymmetric solar forcing bands is moved from equatorial to polar latitudes. The cross-equatorial energy transport response to the same amount of interhemispheric forcing becomes systematically more ocean-centric when higher latitudes are perturbed in association with strengthening AMOC responses. In contrast, the responses of the Pacific subtropical cell are not monotonic and cannot predict this variance in the ITCZ’s equilibrium position. Overall, these results highlight the importance of the meridional distribution of interhemispheric radiative imbalance and the rich buffering of internal feedbacks that occurs in dynamic versus thermodynamic (slab) ocean modeling experiments. Mostly, the results imply that the problem of developing a theory of ITCZ migration is entangled with that of understanding the AMOC’s response to hemispherically asymmetric radiative forcing—a difficult topic deserving of focused analysis across more climate models.

The power output of solar photovoltaics (PV) may have sharp fluctuations and its impact has to be carefully evaluated before integrating significant PV facilities into the power grid. Variability of solar resources is best measured by ground-based measurements. However, distributed ground-measured solar data is not available everywhere, and it would take considerable cost and time to obtain such data. Therefore, it is important and beneficial to model and estimate the variability of distributed PV generation even with insufficient solar data at each location. This study proposes a new methodology to generate spatially-distributed synthetic PV data based on detailed ground measurements collected at a few sites. The synthetic PV data is examined with specific criteria and the feasibility for simulating spatially-distributed PV generation is verified. A case study for Hong Kong is conducted using both the real and synthetic solar data. It is demonstrated that individual PV facilities can have significant fluctuations on a minute-by-minute basis, but the fluctuations can be significantly reduced if PV facilities are more spatially-distributed. The improvement to the estimation of solar variability with the proposed method is illustrated and the significance of its applications is discussed.

We discuss the issues of primary importance to understand the nature of climate changes in the 20th century and main physical processes responsible for these changes and present a physical model for the solar activity (SA) effect on climate characteristics. A key concept of this model is the heliogeophysical disturbance effect on the Earth climate system parameters driving the long-wave radiation flux moving away from the Earth out into space in high-latitude regions. We address the solar activity effect on the changes in the temperature of the atmosphere and of the World Ocean. The aa–index of the geomagnetic activity (GA) was used as an SA proxy index. We discuss the results of analyzing the regularities and peculiarities of the tropospheric and sea surface temperature (SST) responses to both separate heliogeophysical disturbances and long-term changes in solar and geomagnetic activity. The structure of the tropospheric and SST temperature responses was shown to feature a spatial time irregularity. We revealed the regions, where long-term SST changes are determined mainly by SA variations.

We investigate the effects of solar forcing on the North Atlantic (NA) summer climate, in climate simulations with Earth System Models (ESMs), over the preindustrial past millennium (AD 850–1849). We use one simulation and a four-member ensemble performed with the MPI-ESM-P and CESM-LME models, respectively, forced only by low-scaling variations in Total Solar Irradiance (TSI). We apply linear methods (correlation and regression) and composite analysis to estimate the NA surface and tropospheric climatic responses to decadal solar variability. Linear methods in the CESM ensemble indicate a weak summer response in sea-level pressure (SLP) and 500-hPa geopotential height to TSI, with decreased values over Greenland and increased values over the NA subtropics. Composite analysis indicates that, during high-TSI periods, SLP decreases over eastern Canada and the geopotential height at 500-hPa increases over the subtropical NA. The possible summer response of SSTs is overlapped by model internal variability. Therefore, for low-scaling TSI changes, state-of-the-art ESMs disagree on the NA surface climatic effect of solar forcing indicated by proxy-based studies during the preindustrial millennium. The analysis of control simulations indicates that, in all climatic variables studied, spurious patterns of apparent solar response may arise from the analysis of single model simulations., Atmosphere, 12 (5), ISSN:2073-4433

Megadroughts are notable manifestations of the American Southwest, but not so much of the European climate. By using long-term hydrological and meteorological observations, as well as paleoclimate reconstructions, here we show that central Europe has experienced much longer and severe droughts during the Spörer Minimum (~AD 1400–1480) and Dalton Minimum (~AD 1770–1840), than the ones observed during the 21st century. These two megadroughts appear to be linked with a cold state of the North Atlantic Ocean and enhanced winter atmospheric blocking activity over the British Isles and western part of Europe, concurrent with reduced solar forcing and explosive volcanism. Moreover, we show that the recent drought events (e.g., 2003, 2015, and 2018), are within the range of natural variability and they are not unprecedented over the last millennium., Central Europe experienced long-lasting droughts during the Spörer and Dalton solar minima around AD 1450 and 1800 that were more severe and extensive than those observed in the 21st century, according to palaeoclimate reconstructions.

The effects of solar irradiance forcing on weather and climate extremes have received relatively less attention compared to the solar-induced changes in the mean climate. In this respect, here we investigate the possible impact of solar irradiance forcing on the Northern Hemisphere extreme weather and climate variability during summer, from a potential vorticity (PV) perspective. The generation of severe weather events in the extra-tropical regions is often related to intrusions of high PV originating from the polar lower stratosphere. Various two-dimensional PV indices, similar to those characterizing surface temperature and precipitation extremes, are defined to measure the frequency of upper level PV intrusion events. Based on long-term reanalysis data, we show that upper level high PV intrusions over Asia (Europe) are more (less) frequent during high relatively to low solar irradiance summers. Consistent with this PV pattern more (less) frequent surface extreme precipitation events are recorded during high relative to low solar irradiance summers in Asia (Europe). Patterns in the frequency of extreme temperatures are largely opposite to the corresponding extreme precipitation. Furthermore, extreme climate anomaly patterns associated with high solar irradiance forcing are similar to the corresponding patterns associated with strong monsoon circulation over Asia during summer. A preliminary analysis reveals the dominant role of upper level solar related PV anomalies in generation of extreme precipitation in the Asian monsoon region during high solar irradiance summers. A persistent blocking like circulation in the Caspian Sea region during low solar irradiance summers is associated more frequent high PV intrusions and extreme precipitation over Europe. The stability of the solar related extreme precipitation and temperature patterns in the last millennium perspective is also discussed based on proxy data as well as model simulations.

Natural climate variability is partially attributed to the solar radiative forcing. The scope of this work is to increase the scientific understanding of the relative role of solar variations on the terrestrial climate. The applied methodology examines initially the variation of multiple climatic parameters (temperature, zonal wind, relative and specific humidity, sensible and latent surface heat flux, cloud cover, precipitation) in response to the 11-year solar cycle. An additional goal is to estimate the response of the climate system’s parameters to the solar forcing in multiple forecasting horizons and to evaluate the behavior of the climate system in shorter time scales. The adopted methodology includes the development of linear regression models which calculate the dependency of the climatic parameters to solar variations for each grid point of the global dataset on a monthly time scale. The solar indicator used in this study is the 10.7-cm solar radio flux (F10.7) provided by NOAA, while the climate data are extracted from the NCEP/NCAR Reanalysis 1 project with a spatial resolution of 2.5o X 2.5o for 67 years. Regarding the climate system’s response forecasting, an Artificial Neural Network has been trained for modeling and forecasting the solar indicator time series for a few time steps in advance and the effect on climatic parameters is estimated using the established regression equations. The results exhibit that the variation of the climatic parameters can be partially attributed to the 11-year solar cycle. Statistically significant areas with relatively high solar cycle signal were found in multiple pressure levels and geographical regions. Furthermore, the results indicate that the identification of a clear solar signal in the climatic data is a difficult task due to the climate system’s complexity; advanced non-linear methods could be applied in order to obtain a more accurate understanding of this research field.

The solar impact on Earth’s climate is both a rich and open-ended topic with intense debates. In this study, we use the reconstructed data available to investigate periodicities of solar variability (i.e., variations of sunspot numbers) and temperature changes (10 sites spread all over the Earth) as well as the statistical inter-relations between them on the millennial scale during the past 8640 years (BC 6755–AD 1885) before the modern industrial era. We find that the variations of the Earth’s temperatures show evidence for the Eddy cycle component, i.e., the 1000-year cyclicity, which was discovered in variations of sunspot numbers and believed to be an intrinsic periodicity of solar variability. Further wavelet time-frequency analysis demonstrates that the co-variation between the millennium cycle components of solar variability and the temperature change held stable and statistically strong for five out of these 10 sites during our study interval. In addition, the Earth’s climatic response to solar forcing could be different region-by-region, and the temperatures in the southern hemisphere seemed to have an opposite changing trend compared to those in the northern hemisphere on this millennial scale. These findings reveal not only a pronounced but also a complex relationship between solar variability and climatic change on Earth on the millennial timescale. More data are needed to further verify these preliminary results in the future.

Continuous observations play an important role in the studies of solar variability. While such observations can be achieved from space with almost 100% duty cycle, it is difficult to accomplish very high duty cycle from the ground. In this context, we assess the duty cycle that has been achieved from the ground by analyzing the observations of a six station network of identical instruments, Global Oscillation Network Group (GONG). We provide a detailed analysis of the duty cycle using GONG observations spanning over 18 years. We also discuss duty cycle of individual sites and point out various factors that may impact individual site or network duty cycle. The mean duty cycle of the network is 93%, however it reduces by about 5% after all images pass through the stringent quality-control checks. The standard deviations in monthly and yearly duty cycle values are found to be 1.9% and 2.2%, respectively. These results provide a baseline that can be used in the planning of future ground-based networks., Comment: Preprint contains 30 pages, 24 figures and 8 tables. It is published on an open access basis under a Creative Commons Attribution (CC BY) licence

With increasing concerns of climate change, renewable resources such as photovoltaic (PV) have gained popularity as a means of energy generation. The smooth integration of such resources in power system operations is enabled by accurate forecasting mechanisms that address their inherent intermittency and variability. This paper proposes a novel probabilistic framework to predict short-term PV output taking into account the variability of weather data over different seasons. To this end, we go beyond existing prediction methods, building a pipeline of processes, i.e., feature selection, clustering and Gaussian Process Regression (GPR). We make use of datasets that comprise of power output and meteorological data such as irradiance, temperature, zenith, and azimuth. First, a correlation study is performed to select the weather features which affect solar output to a greater extent. Next, we categorise the data into four groups based on solar output and time by using k-means clustering. Finally, we determine a function that relates the aforementioned selected features with solar output by using GPR and Matern 5/2 as a kernel function. We validate our method with five solar generation plants in different locations and compare the results with existing methodologies. More specifically, in order to test the proposed model, two different methods are used: (i) a 5-fold cross validation; and (ii) holding out 30 random days as test data. To confirm the model accuracy, we apply our framework 30 independent times on each of the four clusters. The average error follows a normal distribution, and with 95% confidence level, it takes values between −1.6% and 1.4%. The proposed framework decreases the normalised root mean square error and mean absolute error by 54.6% and 55.5%, respectively, when compared with other relevant works.

The relationship between River Ammer flood frequency variability, extreme summer climate over Europe, and solar forcing is investigated. First, we used observational data to evaluate extreme weather and climate anomaly patterns associated with flood and solar forcing as well as the possible dynamical mechanisms behind them. Then, the annual resolution flood layer record from the Lake Ammer sediments is analysed to evaluate millennial‐scale variability of floods and possible related extreme climate patterns back to 5,500 years BP. A composite analysis reveals that observed River Ammer flood frequency variability at interannual to multidecadal time scales is connected to large‐scale extreme precipitation and temperature patterns. From a synoptic‐scale perspective, the extreme precipitation pattern associated with floods is related to an increase in the frequency of high upper‐level potential vorticity (PV) events over western Europe and a decrease over eastern Europe and western Russia. Increased (decreased) frequency of upper‐level high PV events is related to more (less) surface extreme precipitation occurrence. Furthermore, we show that increased frequency of upper‐level high PV events over western Europe is associated with enhanced blocking activity over eastern Europe. Therefore, the out of phase interannual to millennial‐scale variations of River Ammer flood frequency and solar irradiance, as presented in previous studies, can be explained by a solar modulation of eastern European‐western Russia summer blocking and associated upstream upper‐level wave breaking activity. In addition, we identify two distinct quasi‐periodic signals in both frequency of Lake Ammer flood layer and solar irradiance records with periods of ~900 years and ~2,300 years. We argue that similar cycles should dominate millennial‐scale variations of blocking activity in eastern Europe‐western Russia as well as extreme precipitation and flood frequency variability over central and western Europe during the last ~5,500 years.

The Flare Irradiance Spectral Model (FISM) is an important tool for estimating solar variability for a myriad of space weather research studies and applications, and FISM Version 2 (FISM2) has rece...

An understanding of solar variability over a broad spectral range and broad range of timescales is needed by scientists studying Earth’s climate. The Total and Spectral Solar Irradiance Sensor (TSIS) Spectral Irradiance Monitor (SIM), is designed to measure solar spectral irradiance (SSI) with unprecedented accuracy from 200 nm to 2400 nm. SIM started daily observations in March 2018. To maintain its accuracy over the course of its anticipated 5-year mission and beyond, TSIS SIM needs to be corrected for optical degradation, common for solar viewing instruments. The differing long-term trends of various independent solar-irradiance records attest to the challenge at hand. The correction of TSIS SIM for optical degradation is based on piecewise linear fits that bring the three instrument channels into agreement. It is fundamentally different to the correction applied to the TSIS SIM predecessor on SORCE. The correction facilitates reproducibility, uncertainty estimation and is measurement-based. Corrected, integrated TSIS SIM SSI agrees with independent observations of total solar irradiance to within 45 ppm as well as various solar-irradiance models. TSIS SIM SSI is available at: http://lasp.colorado.edu/lisird/ .

Establishing clear evidence of solar-induced lower atmosphere effects is hampered by the small 11-year solar cycle responses, typically swamped by meteorological variability. Strong 27-day cyclic changes are exploited here instead. During the 2007/8 minimum in solar activity, regular 27-day lighthouse-like sweeps of energetic particles crossed the heliosphere and Earth, followed by a burst of solar ultraviolet radiation. Averaging the atmospheric responses at UK sites reveals immediate cooling in the troposphere after the peak energetic particle flux, followed by warming in the stratosphere. Regionally, this is accompanied by zonal wind changes, and temperature changes beneath cloud at the same time. Of two possible rapid distinct routes of solar influence—photochemical (through ozone) and atmospheric electrical (through low level clouds)—the ozone route does not provide a phase-locked response but the electrical route is supported by observed phase-locked thickening of low level clouds. These findings have potential value to weather forecasting.

Herein, Anatolian aurorae are reviewed based on the existing catalogs to establish a relationship between the aurora observations and past solar activity during the Medieval period. For this purpose, historical aurora catalogs for Constantinople and Anatolia are compiled based on the existing catalogs and compared with those in the Middle East region. The available catalogs in the literature are mostly related to the records observed in Europe, Japan, China, Russia, and the Middle East. There is no study dealing only with the historical aurora observations recorded in Anatolia and Constantinople. The data of the catalog show that there is a considerable relationship between the aurora activity and past strong solar activity. High auroral activity around the extreme solar particle storm in 774/7 75 and the Medieval grand maximum in the 1100s in Anatolia and the Middle East is quite consistent with the past solar variability reported in other scientific literature. WOS:000557405400001 2-s2.0-85089389194

International audience; An amendment to this paper has been published and can be accessed via a link at the top of the paper.

The authors and co-signers of the Terrestrial Planets Comparative Climatology (TPCC) mission concept white paper advocate that planetary science in the next decade would greatly benefit from comparatively studying the fundamental behavior of the atmospheres of Venus and Mars, contemporaneously and with the same instrumentation, to capture atmospheric response to the same solar forcing, and with a minimum of instrument-related variability. Thus, this white paper was created for the 2023-2032 Planetary Science Decadal Survey process. It describes the science rationale for such a mission, and a mission concept that could achieve such a mission., 8 pages including cover page with one figure on cover page

High-frequency measurements of solar resource from the National Institute of Standards and Technology (NIST) PV test-bed in Gaithersburg, MD were down-sampled from 1-minute to 1-hour and used to predict energy yield and clipping losses. Three virtual systems based on the NIST ground array with increasing DC/AC ratio were compared. With hourly input, clipping losses were smaller and energy yield was larger than predictions with high-frequency input. Systems with higher DC/AC ratio were more sensitive to time-resolution. The average difference between hourly and 1-minute predicted energy yield was 2% during the month of July for a DC/AC ratio of 1.3. These results demonstrate the importance of high-frequency solar resource in climates with solar variability to avoid over-predictions of energy yield for inverter blocks with a DC/AC ratio greater than one. The results of this study were implemented to develop a sub-hourly clipping adjustment factor for a pre-construction project site codenamed, “Orion,” near Northbridge, Massachusetts.

We compare solar spectral irradiance (SSI) measurements obtained from the Spectral Irradiance Monitor (SIM) on board the Solar Radiation and Climate Experiment (SORCE), corrected for instrument degradation using three different methods; SIM Version 25, Multiple Same‐Irradiance‐Level and SIM constrained Version 2 (SIMc V2), to quantify their differences and gain understanding about the relative performance of each method. Furthermore, we compare the three data sets to independent SSI observations that include the SORCE SIM successor Total and Spectral Solar Irradiance Sensor SIM and solar irradiance models. While we find agreement between the SSI for the three correction methods for wavelengths in the visible, differences persist for shorter and longer wavelengths, on time scales on the order of the 11‐year solar cycle. The comparisons to independent SSI observations reveal remaining instrument trends in some of the corrected SORCE SIM data.

The number and strength of weather and climate extremes, such as severe floods and droughts, have increased significantly during recent decades. Part of such increase is attributed to human-induced climate change. To better assess the role of natural and anthropogenic forcing we should put the recent climate extreme variability into a long-term perspective. We analyze the variability of extreme precipitation and temperature over Europe in connection with observed daily discharge data of the River Ammer (southern Germany) and the 5500-year flood layer record from varved sediments of the downstream Ammersee. We show that daily River Ammer floods are related to upper level Rossby waves breaking over Europe. This process, which is related to European scale extreme precipitation and temperature anomalies, is consistent with extreme precipitation and temperature patterns associated with River Ammer floods. From a synoptic scale perspective, the observed out-of-phase relationship between solar irradiance forcing and river Ammer floods, as presented in previous studies, is related to enhanced blocking activity over Eastern Europe-western Russia during low solar forcing which favors upper level positive potential vorticity anomalies over western Europe, a more unstable atmosphere and more floods. A singular spectrum analysis of a flood layer record from lake Ammer and a total solar irradiance reconstruction, going back in time to the mid-Holocene, reveals coherent variability at ~900 years and ~2300 years. We argue that similar cycles should dominate the millennial scale variations of blocking activity in the Eastern Europe-western Russia as well as the frequency of extreme temperatures, precipitation and floods over Europe.

Grain was the most important food source for a majority of the population in early modern Europe (c. 1500–1800). The price level and volatility had huge societal effects: high prices tended to increase mortality, decrease fertility as well as affect overall consumption patterns. To what extent climate variability influenced the long-term grain price evolution in early modern Europe has for a long time been a matter of debate. Recent advances in high-resolution palaeoclimatology and historical climatology have made it possible to reassess the grain price–climate relationship in time and space with unprecedented detail (Esper et al. 2017). We analyse the climate signal in 56 multi-centennial long series of annual prices of barley, oat, rye, and wheat across Europe. The grain price–climate relationship in regional clusters of grain price data is analysed using both tree-ring based temperature reconstructions, documentary-based temperature reconstructions, tree-ring based drought reconstructions, and early temperature and precipitation instrumental data, considering possible different climate responses in each grain type and different seasonal targets. In addition, we systematically investigate whether, and to what extent, the imprints of variations in solar forcing, including possible lag effects, can be detected in the grain prices.We find a highly significant and persistent negative temperature–price relationship (i.e., cold = high prices and vice versa) across all of Europe and for all four grain types using both temperature reconstructions and instrumental temperature data. Excluding the Thirty Years’ War (1618–1648) and the period following the French Revolution (1789), this relationship is as strong as r = –0.41 between the annual average of all the 56 included European grain price series and the reconstructed June–August temperature for the previous year. The correlations to drought and precipitation are, on the other hand, mainly insignificant and inconsistent in time and space. The evidence for the existence of the effect of solar forcing variations on early modern European grain prices is not strong, although we can detect statistically significant grain price–solar forcing relationships for certain regions. In conclusion, we find much stronger evidence than hitherto reported for long-term temperature imprints on historical grain prices in Europe, implying that temperature variability and change have been a more important factor in European economic history, even in southern Europe, than commonly acknowledged. Reference:Esper J., et al., 2017. Environmental drivers of historical grain price variations in Europe. Clim. Res. 72: 39–52.

Solar irradiance is a crucial input to climate models, but its measurements are only available since 1978. The variability of solar irradiance on climate-relevant time-scales is caused by the competition between bright and dark features formed by the magnetic fields emerging on the solar surface. Thus, models have been developed that reconstruct past irradiance variability from proxies of the solar magnetic activity. The longest direct proxy is the sunspot number. The common problem of such reconstructions is, however, that while sunspots adequately describe the evolution of the active regions (ARs) (large bipolar regions hosting sunspots), the evolution of their smaller counterparts, the ephemeral regions (ERs), is not directly featured by sunspots. At the same time, these small regions are much more numerous and are believed to be the main source of the long-term irradiance changes, which are of special interest to climate models. We develop an improved description of the ephemeral region emergence taking different solar observational constraints into account. The model builds on the SATIRE-T model, in which the emergence of ARs is described by the sunspot number and the emergence of the ERs is linearly linked to that of ARs. The latter, however, implies that whenever the sunspot number drops to zero, no magnetic field emerges in the model. In the new model, the emergence of the ERs is no longer linked to sunspots linearly. Instead, ARs and ERs are considered to be parts of a single power-law size distribution of the emerging magnetic regions. This ensures that even in the absence of ARs (e.g., during the grand minima of solar activity), the emergence rate of ERs remains non-zero. In particular, the solar open magnetic flux reconstructed using this approach does not drop to zero during the Maunder minimum, in agreement with independent reconstructions from the cosmogenic isotope data. Such an improved description of the ERs will allow a better constraint on the maximum solar irradiance drop during grand minima events. This, in turn, will allow a better constraint on the potential solar forcing in the future.

Recently published, precise stellar photometry of 72 Sun-like stars obtained at the Fairborn Observatory between 1993 and 2017 is used to set limits on the solar forcing of Earth's atmosphere of $\pm$ 4.5 W m$^{-2}$ since 1750. This compares with the +2.2 $\pm$ 1.1 W m$^{-2}$ IPCC estimate for anthropogenic forcing. Three critical assumptions are made. In decreasing order of importance they are: (a) most of the brightness variations occur within the average time-series length of $\approx$17 years; (b) the Sun seen from the ecliptic behaves as an ensemble of middle-aged solar-like stars; and (c) narrow-band photometry in the Str\"omgren $b$ and $y$ bands are linearly proportional to the total solar irradiance. Assumption (a) can best be relaxed and tested by obtaining more photometric data of Sun-like stars, especially those already observed. Eight stars with near-solar parameters have been observed from 1999, and two since 1993. Our work reveals the importance of continuing and expanding ground-based photometry, to complement expensive solar irradiance measurements from space., Comment: 6 pages, 6 figures, accepted to The Astrophysical Journal Letters

We compare projections of the observed hemispherical mean surface temperature (HadCRUT4.6.0.0) and the ensemble mean of CMIP5 climate models' simulations on a set of standard regression model forcing variables. We find that the volcanic aerosol regression coefficients of the CMIP5 simulations are consistently significantly larger (by 40–49%) than the volcanic aerosol coefficients of the observed temperature. The probability that the observed differences are caused just by chance is much less than 0.01. The overestimate is due to the climate models' response to volcanic aerosol radiative forcing. The largest overestimate occurs in the winter season of each hemisphere. We hypothesize that the models' parameterization of aerosol‐cloud interactions within ice and mixed phase clouds is a likely source of this discrepancy. Furthermore, the models significantly underestimate the effect of solar variability on temperature for both hemispheres.

The stochastic nature of renewable energy sources, especially solar PV output, has created uncertainties for the power sector. It threatens the stability of the power system and results in an inability to match power consumption and production. This paper presents a Convolutional Neural Network (CNN) approach consisting of different architectures, such as the regular CNN, multi-headed CNN, and CNN-LSTM (CNN-Long Short-Term Memory), which utilizes a sliding window data-level approach and other data pre-processing techniques to make accurate forecasts. The output of the solar panels is linked to input parameters such as irradiation, module temperature, ambient temperature, and windspeed. The benchmarking and accuracy metrics are calculated for 1 h, 1 day, and 1 week for the CNN based methods which are then compared with the results from the autoregressive moving average and multiple linear regression models in order to demonstrate its efficacy in making short-term and medium-term forecasts.