scholarly journals Weights for general circulation models from CMIP3/CMIP5 in a statistical downscaling framework and the impact on future Mediterranean precipitation

2019 ◽  
Vol 39 (8) ◽  
pp. 3639-3654 ◽  
Author(s):  
Irena Kaspar‐Ott ◽  
Elke Hertig ◽  
Severin Kaspar ◽  
Felix Pollinger ◽  
Christoph Ring ◽  
...  
Keyword(s):  
Statistical Downscaling ◽  
General Circulation ◽  
General Circulation Models ◽  
The Impact

Sensitivity of simulated oxygen isotopes in ice cores and speleothems to Last Glacial Maximum surface conditions

2021 ◽  
Author(s):  
André Paul ◽  
Alexandre Cauquoin ◽  
Stefan Mulitza ◽  
Thejna Tharammal ◽  
Martin Werner
Keyword(s):  
Last Glacial Maximum ◽  
General Circulation ◽  
Ice Cores ◽  
General Circulation Models ◽  
Glacial Maximum ◽  
Sea Surface ◽  
Surface Conditions ◽  
Last Glacial ◽  
The Impact ◽  
Mean Square Errors

<p>In simulations of the climate during the Last Glacial Maximum (LGM), we employ two different isotope-enabled atmospheric general circulation models (NCAR iCAM3 and MPI ECHAM6-wiso) and use simulated (by coupled climate models) as well as reconstructed (from a new global climatology of the ocean surface duing the LGM, GLOMAP) surface conditions.</p><p>The resulting atmospheric fields reflect the more pronounced structure and gradients in the reconstructions, for example, the precipitation is more depleted in oxygen-18 in the high latitudes and more enriched in low latitudes, especially in the tropical convective regions over the maritime continent in the equatorial Pacific and Indian Oceans and over the equatorial Atlantic Ocean. Furthermore, at the sites of ice cores and speleothems, the model-data fit improves in terms of the coefficients of determination and root-mean square errors.</p><p>In additional sensitivity experiments, we also use the climatologies by Annan and Hargreaves (2013) and Tierney et al. (2020) and consider the impact of changes in reconstructed sea-ice extent and the global-mean sea-surface temperature.</p><p>Our findings imply that the correct simulation or reconstruction of patterns and gradients in sea-surface conditions are crucial for a successful comparison to oxygen-isotope data from ice cores and speleothems.</p>

scholarly journals A Simplistic Approach for Assessing Hydroclimatic Vulnerability of Lakes and Reservoirs with Regulated Superficial Outflow

Hydrology ◽  
2019 ◽  
Vol 6 (3) ◽  
pp. 61 ◽  
Author(s):  
Kleoniki Demertzi ◽  
Dimitris Papadimos ◽  
Vassilis Aschonitis ◽  
Dimitris Papamichail
Keyword(s):  
Climate Change ◽  
General Circulation ◽  
Drainage Basin ◽  
Management Strategies ◽  
General Circulation Models ◽  
Climatic Conditions ◽  
Modified Model ◽  
Natural Lakes ◽  
The Future ◽  
The Impact

This study proposes a simplistic model for assessing the hydroclimatic vulnerability of lakes/reservoirs (LRs) that preserve their steady-state conditions based on regulated superficial discharge (Qd) out of the LR drainage basin. The model is a modification of the Bracht-Flyr et al. method that was initially proposed for natural lakes in closed basins with no superficial discharge outside the basin (Qd = 0) and under water-limited environmental conditions {mean annual ratio of potential/reference evapotranspiration (ETo) versus rainfall (P) greater than 1}. In the proposed modified approach, an additional Qd function is included. The modified model is applied using as a case study the Oreastiada Lake, which is located inside the Kastoria basin in Greece. Six years of observed data of P, ETo, Qd, and lake topography were used to calibrate the modified model based on the current conditions. The calibrated model was also used to assess the future lake conditions based on the future climatic projections (mean conditions of 2061-2080) derived by 19 general circulation models (GCMs) for three cases of climate change (three cases of Representative Concentration Pathways: RCP2.6, RCP4.5 and RCP8.5). The modified method can be used as a diagnostic tool in water-limited environments for analyzing the superficial discharge changes of LRs under different climatic conditions and to support the design of new management strategies for mitigating the impact of climate change on (a) flooding conditions, (b) hydroelectric production, (c) irrigation/industrial/domestic use and (d) minimum ecological flows to downstream rivers.

Hydrologic response to climate change: a case study for the Be River Catchment, Vietnam

2012 ◽  
Vol 3 (3) ◽  
pp. 207-224 ◽  
Author(s):  
Dao Nguyen Khoi ◽  
Tadashi Suetsugi
Keyword(s):  
Climate Change ◽  
General Circulation ◽  
Assessment Tool ◽  
Swat Model ◽  
General Circulation Models ◽  
Climate Change Scenarios ◽  
River Catchment ◽  
Calibration And Validation ◽  
Daily Streamflow ◽  
The Impact

The Be River Catchment was studied to quantify the potential impact of climate change on the streamflow using a multi-model ensemble approach. Climate change scenarios (A1B and B1) were developed from an ensemble of four GCMs (general circulation models) (CGCM3.1 (T63), CM2.0, CM2.1 and HadCM3) that showed good performance for the Be River Catchment through statistical evaluations between 15 GCM control simulations and the corresponding time series of observations at annual and monthly levels. The Soil and Water Assessment Tool (SWAT) was used to investigate the impact on streamflow under climate change scenarios. The model was calibrated and validated using daily streamflow records. The calibration and validation results indicated that the SWAT model was able to simulate the streamflow well, with Nash–Sutcliffe efficiency exceeding 0.78 for the Phuoc Long station and 0.65 for the Phuoc Hoa station, for both calibration and validation at daily and monthly steps. Their differences in simulating the streamflow under future climate scenarios were also investigated. The results indicate a 1.0–2.9 °C increase in annual temperature and a −4.0 to 0.7% change in annual precipitation corresponding to a change in streamflow of −6.0 to −0.4%. Large decreases in precipitation and runoff are observed in the dry season.

scholarly journals Weak Land–Atmosphere Coupling Strength in HadAM3: The Role of Soil Moisture Variability

2005 ◽  
Vol 6 (5) ◽  
pp. 670-680 ◽  
Author(s):  
David M. Lawrence ◽  
Julia M. Slingo
Keyword(s):  
Boundary Layer ◽  
Soil Moisture ◽  
Coupling Strength ◽  
General Circulation ◽  
General Circulation Models ◽  
Soil Conditions ◽  
Wide Range ◽  
The Impact ◽  
Soil Moisture Variability ◽  
Moisture Variability

Abstract A recent model intercomparison, the Global Land–Atmosphere Coupling Experiment (GLACE), showed that there is a wide range of land–atmosphere coupling strengths, or the degree that soil moisture affects the generation of precipitation, amongst current atmospheric general circulation models (AGCMs). Coupling strength in the Hadley Centre atmosphere model (HadAM3) is among the weakest of all AGCMs considered in GLACE. Reasons for the weak HadAM3 coupling strength are sought here. In particular, the impact of pervasive saturated soil conditions and low soil moisture variability on coupling strength is assessed. It is found that when the soil model is modified to reduce the occurrence of soil moisture saturation and to encourage soil moisture variability, the soil moisture–precipitation feedback remains weak, even though the relationship between soil moisture and evaporation is strengthened. Composites of the diurnal cycle, constructed relative to soil moisture, indicate that the model can simulate key differences in boundary layer development over wet versus dry soils. In particular, the influence of wet or dry soil on the diurnal cycles of Bowen ratio, boundary layer height, and total heat flux are largely consistent with the observed influence of soil moisture on these properties. However, despite what appears to be successful simulation of these key aspects of the indirect soil moisture–precipitation feedback, the model does not capture observed differences for wet and dry soils in the daily accumulation of boundary layer moist static energy, a crucial feature of the feedback mechanism.

Subtropical clouds stabilize near-Snowball Earth states

2020 ◽  
Author(s):  
Christoph Braun ◽  
Aiko Voigt ◽  
Johannes Hörner ◽  
Joaquim G. Pinto
Keyword(s):  
Sea Ice ◽  
General Circulation ◽  
General Circulation Models ◽  
Snowball Earth ◽  
Radiative Effects ◽  
Albedo Feedback ◽  
The Earth ◽  
Cloud Radiative Effects ◽  
Planetary Albedo ◽  
The Impact

<p>Atmospheric general circulation models developed for the Earth system include comprehensive parameterizations of clouds. Applying them to exoplanet atmospheres provides an opportunity to advance understanding of clouds, atmosphere dynamics, and their coupling in the context of planetary climate dynamics and habitability.</p><p>Here, we study a deep-time extreme climate of Earth as an example of the cold limit of the habitable zone. Geological evidence indicates near-global ice cover during the Neoproterozoic (1000 – 541 Million years ago) associated with considerable hysteresis of atmospheric CO<sub>2</sub>. The Snowball Earth hypothesis provides a straightforward interpretation of Neoproterozoic proxies based on a runaway of the sea-ice albedo feedback. However, the Snowball Earth hypothesis relies on the existence of local habitats to explain the survival of photosynthetic marine species on an entirely ice-covered planet. The Jormungand hypothesis may resolve this issue by considering a weakening of the sea-ice albedo feedback by exposure of dark bare sea ice when sea ice enters the subtropics. This potentially allows the Earth system to stabilize in a climate state - the Jormungand state - with near-global ice cover. Around the equator, a narrow strip of ocean remains ice-free, where life would have easily survived during the pan-glaciations.</p><p>The weakening of the sea-ice albedo feedback is based on the change of the meridional structure of planetary albedo with a moving sea-ice edge. While previous work focused on the contribution of surface albedo to planetary albedo, we here focus on the impact of subtropical and tropical cloudiness on planetary albedo. Enhanced cloudiness generally weakens the sea-ice albedo feedback and thus decreases the climate sensitivity of the Jormungand state, i.e. it stabilizes the Jormungand state. We analyze the impact of cloudiness on the stability of the Jormungand state in the general circulation models CAM3 and ICON-AES with idealized aquaplanet setups. While CAM3 shows significant CO<sub>2</sub>-hysteresis of the Jormungand state, ICON-AES exhibits no stable Jormungand state. Consistently, CAM3 exhibits stronger cloudiness than ICON-AES, especially in the subtropics. An analysis with a one-dimensional energy balance model shows that the Jormungand hysteresis strongly depends on the sensitivity of the planetary albedo to an advance of sea ice into the subtropics. Accordingly, we demonstrate that the absence of cloud-radiative effects within vertical columns in the subtropics drastically decreases the Jormungand hysteresis in CAM3.</p><p>Overall, the magnitude of the Jormungand hysteresis is tightly linked to the representation of cloud-radiative effects in general circulation models. Our results highlight the important role of uncertainties associated with cloud-radiative effects for climate feedbacks on planet Earth in the context of extreme climates, such as they have occurred in Earth’s deep past or might be found on Earth-like planets. In consequence, this also stresses the need and challenges of accounting for adequate cloud modeling for planetary climates.</p>

scholarly journals Comparison of Statistical Downscaling Methods for Monthly Total Precipitation: Case Study for the Paute River Basin in Southern Ecuador

2016 ◽  
Vol 2016 ◽  
pp. 1-13 ◽  
Author(s):  
L. Campozano ◽  
D. Tenelanda ◽  
E. Sanchez ◽  
E. Samaniego ◽  
J. Feyen
Keyword(s):  
River Basin ◽  
Statistical Downscaling ◽  
General Circulation ◽  
General Circulation Models ◽  
Support Vector ◽  
Monthly Precipitation ◽  
Local Conditions ◽  
Southern Ecuador ◽  
Monthly Total Precipitation ◽  
Precipitation Estimates

Downscaling improves considerably the results of General Circulation Models (GCMs). However, little information is available on the performance of downscaling methods in the Andean mountain region. The paper presents the downscaling of monthly precipitation estimates of the NCEP/NCAR reanalysis 1 applying the statistical downscaling model (SDSM), artificial neural networks (ANNs), and the least squares support vector machines (LS-SVM) approach. Downscaled monthly precipitation estimates after bias and variance correction were compared to the median and variance of the 30-year observations of 5 climate stations in the Paute River basin in southern Ecuador, one of Ecuador’s main river basins. A preliminary comparison revealed that both artificial intelligence methods, ANN and LS-SVM, performed equally. Results disclosed that ANN and LS-SVM methods depict, in general, better skills in comparison to SDSM. However, in some months, SDSM estimates matched the median and variance of the observed monthly precipitation depths better. Since synoptic variables do not always present local conditions, particularly in the period going from September to December, it is recommended for future studies to refine estimates of downscaling, for example, by combining dynamic and statistical methods, or to select sets of synoptic predictors for specific months or seasons.

scholarly journals Downscaling of GCM-Simulated Precipitation Using Model Output Statistics

2014 ◽  
Vol 27 (1) ◽  
pp. 312-324 ◽  
Author(s):  
Jonathan M. Eden ◽  
Martin Widmann
Keyword(s):  
Statistical Downscaling ◽  
Temporal Variability ◽  
General Circulation ◽  
Large Scale ◽  
Principal Component ◽  
General Circulation Models ◽  
Model Output ◽  
Local Scaling ◽  
Simulated Precipitation ◽  
Model Output Statistics

Abstract Producing reliable estimates of changes in precipitation at local and regional scales remains an important challenge in climate science. Statistical downscaling methods are often utilized to bridge the gap between the coarse resolution of general circulation models (GCMs) and the higher resolutions at which information is required by end users. As the skill of GCM precipitation, particularly in simulating temporal variability, is not fully understood, statistical downscaling typically adopts a perfect prognosis (PP) approach in which high-resolution precipitation projections are based on real-world statistical relationships between large-scale atmospheric predictors and local-scale precipitation. Using a nudged simulation of the ECHAM5 GCM, in which the large-scale weather states are forced toward observations of large-scale circulation and temperature for the period 1958–2001, previous work has shown ECHAM5 skill in simulating temporal variability of precipitation to be high in many parts of the world. Here, the same nudged simulation is used in an alternative downscaling approach, based on model output statistics (MOS), in which statistical corrections are derived for simulated precipitation. Cross-validated MOS corrections based on maximum covariance analysis (MCA) and principal component regression (PCR), in addition to a simple local scaling, are shown to perform strongly throughout much of the extratropics. Correlation between downscaled and observed monthly-mean precipitation is as high as 0.8–0.9 in many parts of Europe, North America, and Australia. For these regions, MOS clearly outperforms PP methods that use temperature and circulation as predictors. The strong performance of MOS makes such an approach to downscaling attractive and potentially applicable to climate change simulations.

scholarly journals Modifying emissions scenario projections to account for the effects of COVID-19: protocol for CovidMIP

2021 ◽  
Vol 14 (6) ◽  
pp. 3683-3695
Author(s):  
Robin D. Lamboll ◽  
Chris D. Jones ◽  
Ragnhild B. Skeie ◽  
Stephanie Fiedler ◽  
Bjørn H. Samset ◽  
...  
Keyword(s):  
Greenhouse Gases ◽  
General Circulation ◽  
General Circulation Models ◽  
Activity Levels ◽  
Model Intercomparison ◽  
Country Level ◽  
Detection And Attribution ◽  
Intercomparison Project ◽  
Level Scale ◽  
The Impact

Abstract. Lockdowns to avoid the spread of COVID-19 have created an unprecedented reduction in human emissions. While the country-level scale of emissions changes can be estimated in near real time, the more detailed, gridded emissions estimates that are required to run general circulation models (GCMs) of the climate will take longer to collect. In this paper we use recorded and projected country-and-sector activity levels to modify gridded predictions from the MESSAGE-GLOBIOM SSP2-4.5 scenario. We provide updated projections for concentrations of greenhouse gases, emissions fields for aerosols, and precursors and the ozone and optical properties that result from this. The code base to perform similar modifications to other scenarios is also provided. We outline the means by which these results may be used in a model intercomparison project (CovidMIP) to investigate the impact of national lockdown measures on climate, including regional temperature, precipitation, and circulation changes. This includes three strands: an assessment of short-term effects (5-year period) and of longer-term effects (30 years) and an investigation into the separate effects of changes in emissions of greenhouse gases and aerosols. This last strand supports the possible attribution of observed changes in the climate system; hence these simulations will also form part of the Detection and Attribution Model Intercomparison Project (DAMIP).

scholarly journals Differing responses of the QBO to SO<sub>2</sub> injections in two global models

2020 ◽  
Author(s):  
Ulrike Niemeier ◽  
Jadwiga H. Richter ◽  
Simone Tilmes
Keyword(s):  
General Circulation ◽  
Climate Model ◽  
Numerical Models ◽  
General Circulation Models ◽  
Injection Rate ◽  
Equatorial Region ◽  
Quasi Biennial Oscillation ◽  
Vertical Advection ◽  
Model Studies ◽  
The Impact

Abstract. Artificial injections of sulfur dioxide (SO2) into the stratosphere show in several model studies an impact on stratospheric dynamics. The quasi-biennial oscillation (QBO) has been shown to slow down or even vanish, under higher SO2 injections in the equatorial region. But the impact is only qualitatively, but not quantitatively consistent across the different studies using different numerical models. The aim of this study is to understand the reasons behind the differences in the QBO response to SO2 injections between two general circulation models, the Whole Atmosphere Community Climate Model (WACCM-110L) and MAECHAM5-HAM. We show that the response of the QBO to injections with the same SO2 injection rate is very different in the two models, but similar when a similar stratospheric heating rate is induced by SO2 injections of different amounts. The reason for the different response of the QBO corresponding to the same injection rate is very different vertical advection in the two models, even in the control simulation. The stronger vertical advection in WACCM results in a higher aerosol burden and stronger heating of the aerosols, and, consequently in a vanishing QBO at lower injection rate than in simulations with MAECHAM5-HAM.

scholarly journals Accounting for uncertainty in assessing the impact of climate change on biodiversity hotspots in Spain

2019 ◽  
pp. 355-367 ◽  
Author(s):  
D. Romero ◽  
J. Olivero ◽  
R. Real
Keyword(s):  
Climate Change ◽  
Predictive Models ◽  
General Circulation ◽  
General Circulation Models ◽  
Range Shifts ◽  
Biodiversity Hotspots ◽  
Relative Importance ◽  
Vertebrate Species ◽  
Taxonomic Uncertainty ◽  
The Impact

Our limited understanding of the complexity of nature generates uncertainty in mathematical and cartographical models used to predict the effects of climate change on species’ distributions. We developed predictive models of distributional range shifts of threatened vertebrate species in mainland Spain, and in their accumulation in biodiversity hotspots due to climate change. We considered two relevant sources of climatological uncertainty that affect predictions of future climate: general circulation models and socio–economic scenarios. We also examined the relative importance of climate as a driver of species’ distribution and taxonomic uncertainty as additional biogeographical causes of uncertainty. Uncertainty was detected in all the forecasts derived from models in which climate was a significant explanatory factor, and in the species with taxonomic uncertainty. Uncertainty in forecasts was mainly located in areas not occupied by the species, and increased with time difference from the present. Mapping this uncertainty allowed us to assess the consistency of predictions regarding future changes in the distribution of hotspots of threatened vertebrates in Spain.

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