scholarly journals Inter-annual Variability of Snowfall in the Lower Peninsula of Michigan

2021 ◽  
Vol 3 ◽  
Author(s):  
Lei Meng ◽  
Bandhan Dutta Ayon ◽  
Nirjala Koirala ◽  
Kathleen M. Baker
Keyword(s):  
Local Community ◽  
Lake Michigan ◽  
Climate Model ◽  
Weather Forecasting ◽  
Negative Relationship ◽  
Community Safety ◽  
Enso Events ◽  
Annual Variability ◽  
Air Temperatures ◽  
Lower Peninsula

Winter snowfall, particularly lake-contributed snowfall, has a significant impact on the society and environment in the Great Lakes regions including transportation, tourism, agriculture, and ecosystem. Understanding the inter-annual variability of snowfall will provide sound basis for local community safety management and reduce its environmental impacts on agriculture and ecosystems. This study attempts to understand the trend and inter-annual variability in snowfall in the Lower Peninsula of Michigan (LPM) using statistical analysis based on snowfall measurements from eight weather stations. Our study demonstrates that snowfall has significantly increased from 1932 to 2015. Correlation analysis suggests that regional average air temperatures have a strong negative relationship with snowfall in the LPM. On average, approximately 27% of inter-annual variability in snowfall can be explained by regional average air temperatures. ENSO events are also negatively related to snowfall in the LPM and can explain ~8% of inter-annual variability. The North Atlantic Oscillation (NAO) does not have strong influence on snowfall. Composite analysis demonstrates that on an annual basis, more snowfall occurs during the years with higher maximum ice cover (MIC) than during the years with lower MIC in Lake Michigan. Higher MIC is often associated with lower air temperatures which are negatively related to snowfall. This study could provide insight on future snow related climate model improvement and weather forecasting.

scholarly journals Projections of surface air temperature required to sustain permafrost and importance of adaptation to climate change in the Daisetsu Mountains, Japan

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Tokuta Yokohata ◽  
Go Iwahana ◽  
Toshio Sone ◽  
Kazuyuki Saito ◽  
Noriko N. Ishizaki ◽  
...  
Keyword(s):  
Climate Model ◽  
Surface Air Temperature ◽  
Climatic Conditions ◽  
Alpine Ecosystems ◽  
Adaptation To Climate Change ◽  
Freezing And Thawing ◽  
Air Temperatures ◽  
Statistical Relationships ◽  
The Stability ◽  
Slope Displacement

AbstractPermafrost is known to occur in high mountainous areas such as the Daisetsu Mountains in Japan, which are located at the southernmost limit of the permafrost distribution in the world. In this study, areas with climatic conditions suitable for sustaining permafrost in the Daisetsu Mountains are projected using bias-corrected and downscaled climate model outputs and statistical relationships between surface air temperatures and permafrost areas. Using freezing and thawing indices, the size of the area in the Daisetsu Mountains where climatic conditions were suitable for permafrost were estimated to be approximately 150 km2 in 2010. Under the RCP8.5 scenario, this area is projected to decrease to about 30 km2 by 2050 and it is projected to disappear by around 2070. Under the RCP2.6 scenario, the area is projected to decrease to approximately 20 km2 by 2100. The degradation of mountain permafrost could potentially affect the stability of trekking trails due to slope displacement, and it may also have deleterious effects on current alpine ecosystems. It is therefore important to accurately monitor changes in the mountain ecosystem environment and to implement measures to adapt to an environment that is projected to change significantly in the future.

scholarly journals HYPERstream: a multi-scale framework for streamflow routing in large-scale hydrological model

2016 ◽  
Vol 20 (5) ◽  
pp. 2047-2061 ◽  
Author(s):  
Sebastiano Piccolroaz ◽  
Michele Di Lazzaro ◽  
Antonio Zarlenga ◽  
Bruno Majone ◽  
Alberto Bellin ◽  
...  
Keyword(s):  
Large Scale ◽  
Climate Models ◽  
Climate Model ◽  
Transfer Functions ◽  
Weather Forecasting ◽  
Computational Grid ◽  
River Network ◽  
Multi Scale ◽  
Continental Scale ◽  
Routing Scheme

Abstract. We present HYPERstream, an innovative streamflow routing scheme based on the width function instantaneous unit hydrograph (WFIUH) theory, which is specifically designed to facilitate coupling with weather forecasting and climate models. The proposed routing scheme preserves geomorphological dispersion of the river network when dealing with horizontal hydrological fluxes, irrespective of the computational grid size inherited from the overlaying climate model providing the meteorological forcing. This is achieved by simulating routing within the river network through suitable transfer functions obtained by applying the WFIUH theory to the desired level of detail. The underlying principle is similar to the block-effective dispersion employed in groundwater hydrology, with the transfer functions used to represent the effect on streamflow of morphological heterogeneity at scales smaller than the computational grid. Transfer functions are constructed for each grid cell with respect to the nodes of the network where streamflow is simulated, by taking advantage of the detailed morphological information contained in the digital elevation model (DEM) of the zone of interest. These characteristics make HYPERstream well suited for multi-scale applications, ranging from catchment up to continental scale, and to investigate extreme events (e.g., floods) that require an accurate description of routing through the river network. The routing scheme enjoys parsimony in the adopted parametrization and computational efficiency, leading to a dramatic reduction of the computational effort with respect to full-gridded models at comparable level of accuracy. HYPERstream is designed with a simple and flexible modular structure that allows for the selection of any rainfall-runoff model to be coupled with the routing scheme and the choice of different hillslope processes to be represented, and it makes the framework particularly suitable to massive parallelization, customization according to the specific user needs and preferences, and continuous development and improvements.

scholarly journals Black Carbon Increases Frequency of Extreme ENSO Events

2019 ◽  
Vol 32 (23) ◽  
pp. 8323-8333 ◽  
Author(s):  
Sijia Lou ◽  
Yang Yang ◽  
Hailong Wang ◽  
Jian Lu ◽  
Steven J. Smith ◽  
...  
Keyword(s):  
Black Carbon ◽  
Climate Models ◽  
Climate Model ◽  
Southern Oscillation ◽  
Global Climate ◽  
Global Climate Model ◽  
Co2 Concentration ◽  
Enso Events ◽  
Aerosol Forcing ◽  
Earth’S Climate

ABSTRACT El Niño–Southern Oscillation (ENSO) is the leading mode of Earth’s climate variability at interannual time scales with profound ecological and societal impacts, and it is projected to intensify in many climate models as the climate warms under the forcing of increasing CO2 concentration. Since the preindustrial era, black carbon (BC) emissions have substantially increased in the Northern Hemisphere. But how BC aerosol forcing may influence the occurrence of the extreme ENSO events has rarely been investigated. In this study, using simulations of a global climate model, we show that increases in BC emissions from both the midlatitudes and Arctic weaken latitudinal temperature gradients and northward heat transport, decrease tropical energy divergence, and increase sea surface temperature over the tropical oceans, with a surprising consequential increase in the frequency of extreme ENSO events. A corollary of this study is that reducing BC emissions might serve to mitigate the possible increasing frequency of extreme ENSO events under greenhouse warming, if the modeling result can be translated into the climate in reality.

scholarly journals Progress towards a probabilistic Earth system model: examining the impact of stochasticity in the atmosphere and land component of EC-Earth v3.2

2019 ◽  
Vol 12 (7) ◽  
pp. 3099-3118 ◽  
Author(s):  
Kristian Strommen ◽  
Hannah M. Christensen ◽  
Dave MacLeod ◽  
Stephan Juricke ◽  
Tim N. Palmer
Keyword(s):  
Climate Model ◽  
Weather Forecasting ◽  
Southern Oscillation ◽  
Earth System Model ◽  
System Model ◽  
Earth System ◽  
Beneficial Impact ◽  
The Impact ◽  
Mean State

Abstract. We introduce and study the impact of three stochastic schemes in the EC-Earth climate model: two atmospheric schemes and one stochastic land scheme. These form the basis for a probabilistic Earth system model in atmosphere-only mode. Stochastic parametrization have become standard in several operational weather-forecasting models, in particular due to their beneficial impact on model spread. In recent years, stochastic schemes in the atmospheric component of a model have been shown to improve aspects important for the models long-term climate, such as El Niño–Southern Oscillation (ENSO), North Atlantic weather regimes, and the Indian monsoon. Stochasticity in the land component has been shown to improve the variability of soil processes and improve the representation of heatwaves over Europe. However, the raw impact of such schemes on the model mean is less well studied. It is shown that the inclusion of all three schemes notably changes the model mean state. While many of the impacts are beneficial, some are too large in amplitude, leading to significant changes in the model's energy budget and atmospheric circulation. This implies that in order to maintain the benefits of stochastic physics without shifting the mean state too far from observations, a full re-tuning of the model will typically be required.

Impact of Indo-Pacific Feedback Interactions on ENSO Dynamics Diagnosed Using Ensemble Climate Simulations

2012 ◽  
Vol 25 (21) ◽  
pp. 7743-7763 ◽  
Author(s):  
A. Santoso ◽  
M. H. England ◽  
W. Cai
Keyword(s):  
Indian Ocean ◽  
Climate Model ◽  
Southern Oscillation ◽  
Ocean Basin ◽  
Climate Feedback ◽  
Enso Events ◽  
Thermocline Feedback ◽  
Enso Dynamics ◽  
The Indian Ocean ◽  
The Impact

The impact of Indo-Pacific climate feedback on the dynamics of El Niño–Southern Oscillation (ENSO) is investigated using an ensemble set of Indian Ocean decoupling experiments (DCPL), utilizing a millennial integration of a coupled climate model. It is found that eliminating air–sea interactions over the Indian Ocean results in various degrees of ENSO amplification across DCPL simulations, with a shift in the underlying dynamics toward a more prominent thermocline mode. The DCPL experiments reveal that the net effect of the Indian Ocean in the control runs (CTRL) is a damping of ENSO. The extent of this damping appears to be negatively correlated to the coherence between ENSO and the Indian Ocean dipole (IOD). This type of relationship can arise from the long-lasting ENSO events that the model simulates, such that developing ENSO often coincides with Indian Ocean basin-wide mode (IOBM) anomalies during non-IOD years. As demonstrated via AGCM experiments, the IOBM enhances western Pacific wind anomalies that counteract the ENSO-enhancing winds farther east. In the recharge oscillator framework, this weakens the equatorial Pacific air–sea coupling that governs the ENSO thermocline feedback. Relative to the IOBM, the IOD is more conducive for ENSO growth. The net damping by the Indian Ocean in CTRL is thus dominated by the IOBM effect which is weaker with stronger ENSO–IOD coherence. The stronger ENSO thermocline mode in DCPL is consistent with the absence of any IOBM anomalies. This study supports the notion that the Indian Ocean should be viewed as an integral part of ENSO dynamics.

scholarly journals Diagnosis of the summertime warm and dry bias over the U.S. Southern Great Plains in the GFDL climate model using a weather forecasting approach

2006 ◽  
Vol 33 (18) ◽  
pp. n/a-n/a ◽  
Author(s):  
Stephen A. Klein ◽  
Xianan Jiang ◽  
Jim Boyle ◽  
Sergey Malyshev ◽  
Shaocheng Xie
Keyword(s):  
Great Plains ◽  
Climate Model ◽  
Weather Forecasting ◽  
Southern Great Plains ◽  
The U.S ◽  
Dry Bias

scholarly journals Technical challenges and solutions in representing lakes when using WRF in downscaling applications

2014 ◽  
Vol 7 (5) ◽  
pp. 7121-7150 ◽  
Author(s):  
M. S. Mallard ◽  
C. G. Nolte ◽  
T. L. Spero ◽  
O. R. Bullock ◽  
K. Alapaty ◽  
...  
Keyword(s):  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Regional Climate ◽  
Wrf Model ◽  
Ice Cover ◽  
Alternative Methods ◽  
Weather Research And Forecasting ◽  
Inland Lakes ◽  
Air Temperatures

Abstract. The Weather Research and Forecasting (WRF) model is commonly used to make high resolution future projections of regional climate by downscaling global climate model (GCM) outputs. Because the GCM fields are typically at a much coarser spatial resolution than the target regional downscaled fields, inland lakes are often poorly resolved in the driving global fields, if they are resolved at all. In such an application, using WRF's default interpolation methods can result in unrealistic lake temperatures and ice cover at inland water points. Prior studies have shown that lake temperatures and ice cover impact the simulation of other surface variables, such as air temperatures and precipitation, two fields that are often used in regional climate applications to understand the impacts of climate change on human health and the environment. Here, alternative methods for setting lake surface variables in WRF for downscaling simulations are presented and contrasted.

scholarly journals "Changes" of the thermal continentality in Central Europe between the years 1951 and 2013: case study – Slovak Republic

2015 ◽  
Vol 6 (2) ◽  
pp. 1261-1275 ◽  
Author(s):  
J. Vilček ◽  
J. Škvarenina ◽  
J. Vido ◽  
R. Kandrík ◽  
J. Škvareninová ◽  
...  
Keyword(s):  
Climate Change ◽  
Central Europe ◽  
21St Century ◽  
Climate Model ◽  
Slovak Republic ◽  
Vegetation Distribution ◽  
Climate Conditions ◽  
Air Temperatures

Abstract. The influence of continents and oceans plays conceptually the key role in the climate conditions of Europeans regions. Continentality is also an important phytogeographic factor of vegetation distribution in Slovakia. This study analysed continentality development at six meteorological stations in Slovakia during the periods 1951–2013, or 1961–2013. Rising trend of the maximal and minimal temperature has been observed at all meteorological stations (lowland as well as mountainous stations) in this periods. However the results showed non-significant increase of continentality index during the monitored period of 63 (53) years. Based on the results of CCM 2000 climate model we cannot expect significant changes of continentality by the end of the 21st century, but the climate change will be significantly manifested by the increase of maximum and minimum air temperatures.

scholarly journals Inter-annual variability of the carbon dioxide oceanic sink south of Tasmania

2007 ◽  
Vol 4 (5) ◽  
pp. 3639-3671 ◽  
Author(s):  
A. V. Borges ◽  
B. Tilbrook ◽  
N. Metzl ◽  
A. Lenton ◽  
B. Delille
Keyword(s):  
Large Scale ◽  
Dissolved Inorganic Carbon ◽  
Negative Relationship ◽  
Large Data ◽  
Atmospheric Co2 ◽  
Data Set ◽  
Subtropical Zone ◽  
Future Evolution ◽  
Annual Variability ◽  
Sst Anomalies

Abstract. We compiled a large data-set from 22 cruises spanning from 1991 to 2003, of the partial pressure of CO2 (pCO2) in surface waters over the continental shelf (CS) and adjacent open ocean (43° to 46° S; 145° to 150° E), south of Tasmania. Sea surface temperature (SST) anomalies (as intense as 2°C) are apparent in the subtropical zone (STZ) and subAntarctic zone (SAZ). These SST anomalies also occur on the CS, and seem to be related to large-scale coupled atmosphere-ocean oscillations. Anomalies of pCO2 normalized to a constant temperature are negatively related to SST anomalies. A depressed winter-time vertical input of dissolved inorganic carbon (DIC) during phases of positive SST anomalies, related to a poleward shift of westerly winds, and a concomitant local decrease in wind stress are the likely cause of the negative relationship between pCO2 and SST anomalies. The observed trend is an increase of the sink for atmospheric CO2 associated with positive SST anomalies, although strongly modulated by inter-annual variability of wind speed. Assuming that phases of positive SST anomalies are indicative of the future evolution of regional ocean biogeochemistry under global warming, we show using a purely observational based approach that some provinces of the Southern Ocean could provide a potential negative feedback on increasing atmospheric CO2.

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