TopoCLIM: Rapid topography-based downscaling of regional climate model output in complex terrain v.1.0

This study describes and evaluates a new downscaling scheme that specifically addresses the need for hillslope scale atmospheric forcing time-series for modeling the local impact of regional climate change projections on the land surface in complex terrain. The method has a global scope and is able to generate the full suite of model forcing variables required for hydrological and land surface modeling at hourly timesteps. It achieves this by utilising the previously published TopoSCALE scheme (Fiddes et al. 2014) to generate a synthetic observation of current climate at hillslope scale while accounting for a broad range of surface-atmosphere interactions. These synthetic observations are then used to debias (downscale) CORDEX climate variables using the quantile mapping method. A further temporal disaggregation step produces sub-daily fields. This approach has the advantages of other empirical-statistical methods, namely speed of use while avoiding the need for ground data, which is often limited. It is therefore a suitable method for a wide range of remote regions where ground data is absent, incomplete, or not of sufficient length. The approach is evaluated using a network of high elevation stations across the Swiss Alps and a test application of modelling climate change impacts on Alpine snow cover is given.

Historical and projected future hydroclimatic risk on seasonal yield in the irrigated rice paddies of Malaysia

<p>Food security is an increasing threat to rice-consuming nations in the face of a changing climate. In this study, we present a framework for analysing  the historical and projecting the future relationship between climate variability and rice yield in the context of weather index insurance. The case study is the Muda rice granary, the largest rice paddy planting area in Malaysia producing approximately 40% of the national output. First, correlation and linear regression are used to explore the response of seasonal rice yield to various average and extreme precipitation, temperature and streamflow-based indices over a 16 year period between 2001 to 2016.  The highest Pearson correlation (r) and coefficient of determination (R<sup>2</sup>) values were obtained with June minimum temperature in the dry season, and December maximum 1 day precipitation and  January mean streamflow in the wet season. The results suggest that rice yield is most at risk from the impact of hydroclimatic variability and change during the flowering and maturity stages of crop growth. Next, findings from the statistical analysis are integrated with hydro-crop simulation of the 4,515 km2 catchment area, using a calibrated Soil Water Assessment Tool (SWAT) and bias-corrected Regional Climate Model output from the Coordinated Regional Downscaling Experiment for South East Asia (CORDEX-SEA). The output is finally used to construct projected future risk profiles for rice production in the area. </p>

Is the impact of climate oscillations changing over the Greenland Ice Sheet?

<p>Greenland Block Index (GBI) and North Atlantic Oscillation (NAO) are climate indices widely used for climatological studies especially over the Greenland Ice Sheet (GrIS). Particularly in summer, they are highly and negatively correlated; both have a strong relationship to near surface processes around the GrIS; their magnitude creates non-linear feedbacks and influences the low troposphere, shaping spatial accumulation and ablation patterns.</p><p>NAO is a measure of the surface pressure difference over the North Atlantic, providing insight of intensity and location of the jet stream. GBI denotes the general circulation over Greenland at the 500-hPa level and depending on its signal promotes heat and moist advection towards inland.</p><p>Based on the 1959-2019 period, the extreme summer melt of 2019 recorded the highest mean summer GBI while the extreme summer melt of 2012 recorded the lowest mean summer NAO. Their impact, however, goes beyond the melting season since the inter-seasonal phase change of these two indices may enhance/ postpone early melt/late refreezing and vice-versa.</p><p>Supported by 62 years of high-resolution regional climate model output (RACMO2.3p2), this work uses a statistical approach to analyze inter-seasonal variability of climate oscillations and their impact on the surface energy budget components over the GrIS. Also, teleconnection changes in a changing climate are hypothesized.</p>

The contribution of föhn winds to northeast Greenland summer melt and their relationship with atmospheric rivers

<p>Atmospheric Rivers (ARs), narrow filaments of concentrated water vapor transport, have direct impacts on the surface mass balance (SMB) of the western Greenland Ice Sheet through increased summer melting in the ablation area and increased snowfall in higher altitudes. Here, we show that an additional effect of ARs on SMB comes from the development of föhn winds, whereby the air is adiabatically warmed as it descends. As ARs pass over the ice sheet and deposit precipitation in northwest Greenland, the air subsequently flows down the leeward slope and the warm, dry conditions contribute to increased melting in the northeast, and more specifically on the Nioghalvfjerdsfjorden (or 79N) Glacier.</p><p> </p><p>We identify föhn conditions using an automated detection algorithm applied to MAR and RACMO2 regional climate model output. These data are paired with an AR detection algorithm and self-organizing map (SOM) classification applied to MERRA-2 and ERA5 reanalyses, in order to investigate connections between regional circulation patterns, ARs, föhn winds, and ice sheet SMB. We find that föhn conditions and associated surface melt are increased for periods of 1–3 days after anomalous southerly and southwesterly water vapor transport by ARs through Baffin Bay and the Nares Strait. Approximately 70% of the ARs which make landfall in the northwest sector of Greenland lead to the development of föhn winds on the northeast coast. The frequency of AR-induced föhn conditions in the northeast has increased in the last 40 years, in line with an increase in the strongest ARs in the northwest. We also find that anomalous northerly moisture transport from the Lincoln Sea generates enhanced melt in the lowest (0–500m) elevations of northeast Greenland, while below-average surface melt occurs during all other identified moisture transport regimes.</p>

A Hybrid Downscaling Approach for Future Temperature and Precipitation Change

We used empirical–statistical downscaling in a pseudoreality context, in which both large-scale predictors and small-scale predictands were based on climate model results. The large-scale conditions were taken from a global climate model, and the small-scale conditions were taken from dynamical downscaling of the same global model with a convection-permitting regional climate model covering southern Norway. This hybrid downscaling approach, a “perfect model”–type experiment, provided 120 years of data under the CMIP5 high-emission scenario. Ample calibration samples made rigorous testing possible, enabling us to evaluate the effect of empirical–statistical model configurations and predictor choices and to assess the stationarity of the statistical models by investigating their sensitivity to different calibration intervals. The skill of the statistical models was evaluated in terms of their ability to reproduce the interannual correlation and long-term trends in seasonal 2-m temperature T2m, wet-day frequency fw, and wet-day mean precipitation μ. We found that different 30-yr calibration intervals often resulted in differing statistical models, depending on the specific choice of years. The hybrid downscaling approach allowed us to emulate seasonal mean regional climate model output with a high spatial resolution (0.05° latitude and 0.1° longitude grid) for up to 100 GCM runs while circumventing the issue of short calibration time, and it provides a robust set of empirically downscaled GCM runs.

Modelling future glacier evolution: Which feedbacks are relevant?

<div> <div>Numerous models to project the future evolution of mountain glaciers in response to ongoing climate change are available, both at the local and the global scale. However, a suite of partly major simplifications is necessary in these models given the restrictions in data availability. Whereas most models account for the primary feedbacks, such as the snow-ice albedo feedback and the dynamic glacier response in some way, a considerable number of yet poorly understood or less investigated feedbacks is present that might significantly hamper the reliability of current glaciological projections.</div> <div> </div> <div>Here, we present results of a detailed modelling study for the example of Vadret da Morteratsch, Swiss Alps. A surface mass balance model accounting for ice dynamics is forced with downscaled regional climate model output (68 scenarios, CH2018) for the period 2015 to 2100. Various processes are either parameterized or explicitly accounted for. We focus on the use of a fully distributed surface energy-balance approach in comparison to simplified degree-day methods. The relevance of projected changes in different components of the energy balance is assessed using model experiments. In particular, the importance of feedback effects due to (1) the spatio-temporal evolution of supraglacial debris, (2) the formation of new proglacial lakes, and (3) changes in bare-ice albedo and local direct solar irradiance is investigated.</div> <div> </div> <div>We find that the above feedback effects all have a rather small potential to substantially impact on the rates of expected glacier retreat. In some cases, this is unexpected (e.g. for debris coverage and proglacial lakes) but can be explained by compensating processes. We also discuss and visualize the future wastage of Vadret da Morteratsch under the newest generation of climate scenarios, and put these results into context with previous studies, as well as with plans to artificially reduce the rate of glacier mass loss.</div> </div>

Southeast Greenland Winter Precipitation Strongly Linked to the Icelandic Low Position

Greenland’s largest precipitation flux occurs in its southeast (SE) region during the winter, controlled primarily by easterly winds and frequent cyclogenesis in the North Atlantic. Several studies have attempted to link SE Greenland precipitation to the North Atlantic Oscillation (NAO) but results are inconsistent. This work uses reanalysis, automatic weather station data, and regional climate model output to show that the east–west position of the Icelandic low is a better predictor of SE Greenland precipitation (average correlation of r = −0.48 in DJF) than climate indices such as the NAO (r = −0.06 in DJF). In years when the Icelandic low is positioned extremely west, moisture transport increases up to ~40% (or up to 40 kg m−1 s−1) off the SE Greenland coast compared to when the low is in an extreme east position. Furthermore, in years when the Icelandic low is positioned extremely west, storm track density and intensity increase just off the SE coast of Greenland. Thus, the Icelandic low’s longitudinal position dominates SE Greenland ice sheet’s wintertime precipitation, a positive term in the ice sheet mass balance. Given SE Greenland’s importance in the overall ice sheet mass balance, the position of the Icelandic low is therefore important for making projections of future sea level.