Km-resolution climate models: prospects and challenges

<p>Currently major efforts are underway toward refining the horizontal grid spacing of climate models to about 1 km, using both global and regional climate models. There is the well-founded hope that this increase in resolution will improve climate models, as it enables replacing the parameterizations of moist convection and gravity-wave drag by explicit treatments. Results suggest that this approach has a high potential in improving the representation of the water cycle and extreme events, and in reducing uncertainties in climate change projections. The presentation will provide examples of these developments in the areas of heavy precipitation and severe weather events over Europe. In addition, it will be argued that km-resolution is a promising approach toward constraining uncertainties in global climate change projections, due to improvements in the representation of tropical and subtropical clouds. Work in the latter area has only recently started and results are highly encouraging.</p> <p>For a few years there have also been attempts to make km-resolution available in global climate models for decade-long simulations. Developing this approach requires a concerted effort. Key challenges include the exploitation of the next generation hardware architectures using accelerators (e.g. graphics processing units, GPUs), the development of suitable approaches to overcome the output avalanche, and the maintenance of the rapidly-developing model source codes on a number of different compute architectures. Despite these challenges, it will be argued that km-resolution GCMs with a capacity to run at 1 SYPD (simulated year per day), might be much closer than commonly believed.</p> <p>The presentation is largely based on a recent collaborative paper (Schär et al., 2020, BAMS, https://doi.org/10.1175/BAMS-D-18-0167.1) and ongoing studies. It will also present aspects of a recent Swiss project in this area (EXCLAIM, https://exclaim.ethz.ch/).</p>

Understanding the uncertainty cascaded in climate change projections for agricultural decision making

Climate projections have confirmed the need to adapt to a changing climate, but have been less beneficial in guiding how to effectively adapt. The reason is the uncertainty cascade, from assumptions about future emissions of greenhouse gases to what that means for the climate to real decisions on a local scale. Each of the steps in the process contains uncertainty and these uncertainties from various levels of the assessment accumulate. This cascade of uncertainty should be critically analyzed to inform decision makers about the certain range of future changes. Most widely used approaches like Bayesian and Monte Carlo gives specific values of parameters and their confidence, yet for agricultural decision making the range of possible changes itself is required as such to understand impact at every point of these ranges. This paper addresses these issues and examines the uncertainties in climate projections at a local scale. In the study locations (Coimbatore and Thanjavur), irrespective of the models, scenarios and time slices, the maximum and minimum temperatures are projected to increase with seasonal variations. With certainty, the projected increase in maximum and minimum temperature over Coimbatore is 0.2 to 4.1 ºC and 0.3 to 5.3 ºC and over Thanjavur is 0.3 to 4.6 ºC and 0.2 to 5.2 ºC, respectively. Rainfall is projected to vary between a decrease of 15.0 to an increase of 73.1 percent for Coimbatore and a decrease of 15.3 to an increase of 80.7 per cent for Thanjavur during the 21st century. On comparing the monsoon seasons, southwest monsoon (SWM) is projected to have a higher increase in both maximum and minimum temperature than northeast monsoon (NEM) for both the study locations, similar to their current trends. Rainfall is projected to increase more in NEM than in SWM.

Making Agriculture Carbon Neutral Amid a Changing Climate: The Case of South-Western Australia

Making Australian agriculture carbon neutral by 2050 is a goal espoused by several agricultural organisations in Australia. How costly might it be to attain that goal, especially when adverse climate change projections apply to agriculture in southern Australia? This study uses scenario analysis to examine agricultural emissions and their abatement via reforestation in south-western Australia under projected climate change. Most scenarios include the likelihood of agricultural emissions being reduced in the coming decades. However, the impact of projected adverse climate change on tree growth and tree survival means that the cost of achieving agricultural carbon neutrality via reforestation is forecast to increase in south-western Australia. Agricultural R&D and innovation that enable agricultural emissions to diminish in the coming decades will be crucial to lessen the cost of achieving carbon neutrality. On balance, the more likely scenarios reveal the real cost of achieving carbon neutrality will not greatly increase. The cost of achieving carbon neutrality under the various scenarios is raised by an additional AUD22 million to AUD100 million per annum in constant 2020 dollar terms. This magnitude of cost increase is very small relative to the region’s gross value of agricultural production that is regularly greater than AUD10 billion.

Anticipated maximum scale precipitation for calculating the worst-case floods

Against increasing number of unprecedented heavy rains and typhoons reflecting climate change, the Japanese Government decided saving life as the top priority considering a ‘worst-case’ scenario. Accordingly, the Flood Risk Management Act was amended in 2015 to use the anticipated maximum scale precipitation (AMSP) for flood inundation calculation. In order to estimate the AMSP, the Ministry of Land, Infrastructure, Transport and Tourism (MLIT) chose historical maximum areal precipitation in the form of duration–area–depth (DAD) curves rather than climate change projections' dataset d4PDF. In this paper, policy development and detailed estimation procedures for the AMSP were reviewed and discussed. It was concluded that the current climate change projections are still not accurate enough to be used as the basis for real local operations, while long accumulated ground observations and ground-based radars are available in good quality all over Japan. But at the same time, historical maximum should always be updated as past records are renewed. Also, regional partitioning should not be done at too coarse of scale for proper regionalization of DAD. Such strategy would serve as a useful reference for other nations.

Water Quality of the Seyfe Lake Basin, Turkey

Seyfe Lake is an important part of the natural ecosystem of Central Anatolia and lies within a 1487 km2 closed basin. Groundwater withdrawal for irrigation and recent climatic change have caused lake area to decrease for decades and to completely disappear briefly in August 2008. Groundwater quality is crucial for sustainable irrigation in the Seyfe Basin. A key finding of this study is the difference in the Hardie-Eugster alkalinity-to-calcium ratio of the lake water and that of most groundwater wells in the basin. This difference in the chemical signature of Seyfe Lake and basin groundwater means the evaporative salinization pathway of most groundwater discharged into the lake cannot account for the composition of Seyfe Lake. The ratio of actual evapotranspiration to precipitation will increase under current climate change projections. A second finding, with implications for soil salinization, is that most groundwater in Seyfe Basin has a Hardie-Eugster alkalinity-tocalcium ratio greater than unity, meaning soil alkalization will accompany soil salinization.