Trend analysis of watershed-scale annual and seasonal precipitation in Northern California based on dynamically downscaled future climate projections

2018 ◽  
Vol 11 (1) ◽  
pp. 86-105 ◽  
Author(s):  
K. Ishida ◽  
A. Ercan ◽  
T. Trinh ◽  
S. Jang ◽  
M. L. Kavvas ◽  
...  

Abstract Impact of future climate change on watershed-scale precipitation was investigated over Northern California based on future climate projections by means of the dynamical downscaling approach. Thirteen different future climate projection realizations from two general circulation models (GCMs: ECHAM5 and CCSM3) based on four emission scenarios (SRES A1B, A1FI, A2, and B1) were dynamically downscaled to 9-km resolution grids over eight watersheds in Northern California for a period of 90 water years (2010–2100). Analysis of daily precipitation over the eight watersheds showed that precipitation values obtained from dynamical downscaling of the 1981 to 1999 control runs of ECHAM5 and CCSM3 GCMs compared well with the PRISM data. Long-term future trends of annual and seasonal basin-average precipitation were investigated. Although a large variability exists for the projected annual basin-average precipitation within each of the 13 individual realizations, there was no significant long-term trend over the eight study watersheds except for the downward trend in the A1FI scenario. On the other hand, significant upward and downward trends were detected in the seasonal basin-average precipitation except in the winter months (January, February, and March). The trend analysis results in this study indicated the importance of considering seasonal variability, scenario, and model uncertainty.

2018 ◽  
Vol 11 (1) ◽  
pp. 93-112 ◽  
Author(s):  
Stanislav Myslenkov ◽  
Alisa Medvedeva ◽  
Victor Arkhipkin ◽  
Margarita Markina ◽  
Galina Surkova ◽  
...  

Author(s):  
Alan M. Haywood ◽  
Andy Ridgwell ◽  
Daniel J. Lunt ◽  
Daniel J. Hill ◽  
Matthew J. Pound ◽  
...  

Given the inherent uncertainties in predicting how climate and environments will respond to anthropogenic emissions of greenhouse gases, it would be beneficial to society if science could identify geological analogues to the human race’s current grand climate experiment . This has been a focus of the geological and palaeoclimate communities over the last 30 years, with many scientific papers claiming that intervals in Earth history can be used as an analogue for future climate change. Using a coupled ocean–atmosphere modelling approach, we test this assertion for the most probable pre-Quaternary candidates of the last 100 million years: the Mid- and Late Cretaceous, the Palaeocene–Eocene Thermal Maximum (PETM), the Early Eocene, as well as warm intervals within the Miocene and Pliocene epochs. These intervals fail as true direct analogues since they either represent equilibrium climate states to a long-term CO 2 forcing—whereas anthropogenic emissions of greenhouse gases provide a progressive (transient) forcing on climate—or the sensitivity of the climate system itself to CO 2 was different. While no close geological analogue exists, past warm intervals in Earth history provide a unique opportunity to investigate processes that operated during warm (high CO 2 ) climate states. Palaeoclimate and environmental reconstruction/modelling are facilitating the assessment and calculation of the response of global temperatures to increasing CO 2 concentrations in the longer term (multiple centuries); this is now referred to as the Earth System Sensitivity, which is critical in identifying CO 2 thresholds in the atmosphere that must not be crossed to avoid dangerous levels of climate change in the long term. Palaeoclimatology also provides a unique and independent way to evaluate the qualities of climate and Earth system models used to predict future climate.


2021 ◽  
Author(s):  
Giovanni Di Virgilio ◽  
Jason P. Evans ◽  
Alejandro Di Luca ◽  
Michael R. Grose ◽  
Vanessa Round ◽  
...  

<p>Coarse resolution global climate models (GCM) cannot resolve fine-scale drivers of regional climate, which is the scale where climate adaptation decisions are made. Regional climate models (RCMs) generate high-resolution projections by dynamically downscaling GCM outputs. However, evidence of where and when downscaling provides new information about both the current climate (added value, AV) and projected climate change signals, relative to driving data, is lacking. Seasons and locations where CORDEX-Australasia ERA-Interim and GCM-driven RCMs show AV for mean and extreme precipitation and temperature are identified. A new concept is introduced, ‘realised added value’, that identifies where and when RCMs simultaneously add value in the present climate and project a different climate change signal, thus suggesting plausible improvements in future climate projections by RCMs. ERA-Interim-driven RCMs add value to the simulation of summer-time mean precipitation, especially over northern and eastern Australia. GCM-driven RCMs show AV for precipitation over complex orography in south-eastern Australia during winter and widespread AV for mean and extreme minimum temperature during both seasons, especially over coastal and high-altitude areas. RCM projections of decreased winter rainfall over the Australian Alps and decreased summer rainfall over northern Australia are collocated with notable realised added value. Realised added value averaged across models, variables, seasons and statistics is evident across the majority of Australia and shows where plausible improvements in future climate projections are conferred by RCMs. This assessment of varying RCM capabilities to provide realised added value to GCM projections can be applied globally to inform climate adaptation and model development.</p>


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