Evaluation of present and future North American Regional Climate Change Assessment Program (NARCCAP) regional climate simulations over the southeast United States

In order to make well-informed decisions in response to future climate change, officials and the public require reliable climate projections at the scale of tens of kilometers, rather than the hundreds of kilometers that the current atmosphere-ocean general circulation models provide. Recent efforts such as the North American Regional Climate Change Assessment Program (NARCCAP) aim to address this need. This study has two principal aims: (1) evaluate the seasonal performance of the NARCCAP simulations over the southeast United States for both present (1971-2000) and future (2041-2070) periods and (2) assess the impact of a performance-based weighting scheme on bias and uncertainty. Application of the weighting scheme results in a substantial reduction in magnitude and percent area exhibiting significant bias in all seasons for both temperature and precipitation. The weighting scheme is then expanded to evaluate future change. Temperature changes are universally positive and outside the bounds of natural variability over the entire region and in all seasons. Application of the weighting scheme tightens confidence intervals by as much as 1.6°C. Future precipitation changes are modest, are of mixed sign, and vary by season and location. Though uncertainty is reduced by as much as 50%, the projected changes are generally not outside the bounds of natural background variability. Thus, under the NARCCAP simulations, stress on water resources is most likely to come from increased temperatures and not changes in mean seasonal precipitation. For energy use, the implication is that the ∼3°C temperature increase during the peak use summer season may place additional strain on power grids

Tracking the impacts of precipitation phase changes through the hydrologic cycle in snowy regions: From precipitation to reservoir storage

Cool season precipitation plays a critical role in regional water resource management in the western United States. Throughout the twenty-first century, regional precipitation will be impacted by rising temperatures and changing circulation patterns. Changes to precipitation magnitude remain challenging to project; however, precipitation phase is largely dependent on temperature, and temperature predictions from global climate models are generally in agreement. To understand the implications of this dependence, we investigate projected patterns in changing precipitation phase for mountain areas of the western United States over the twenty-first century and how shifts from snow to rain may impact runoff. We downscale two bias-corrected global climate models for historical and end-century decades with the Weather Research and Forecasting (WRF) regional climate model to estimate precipitation phase and spatial patterns at high spatial resolution (9 km). For future decades, we use the RCP 8.5 scenario, which may be considered a very high baseline emissions scenario to quantify snow season differences over major mountain chains in the western U.S. Under this scenario, the average annual snowfall fraction over the Sierra Nevada decreases by >45% by the end of the century. In contrast, for the colder Rocky Mountains, the snowfall fraction decreases by 29%. Streamflow peaks in basins draining the Sierra Nevada are projected to arrive nearly a month earlier by the end of the century. By coupling WRF with a water resources model, we estimate that California reservoirs will shift towards earlier maximum storage by 1–2 months, suggesting that water management strategies will need to adapt to changes in streamflow magnitude and timing

Mass balance and hydrological modeling of the Hardangerjøkulen ice cap in south-central Norway

A detailed, physically based, one dimensional column snowpack model (Crocus) has been incorporated into the hydrological model, Weather Research and Forecasting (WRF)-Hydro, to allow for direct surface mass balance simulation of glaciers and subsequent modeling of meltwater discharge from glaciers. The new system (WRF-Hydro/Glacier) is only activated over a priori designated glacier areas. This glacier area is initialized with observed glacier thickness and assumed to be pure ice (with corresponding ice density). This allows for melting of the glacier to continue after all accumulated snow has melted. Furthermore, the simulation of surface albedo over the glacier is more realistic, as surface albedo is represented by snow, where there is accumulated snow, and glacier ice, when all accumulated snow is melted. To evaluate the WRF-Hydro/Glacier system over a glacier in southern Norway, WRF atmospheric model simulations were downscaled to 1 km grid spacing. This provided meteorological forcing data to the WRF-Hydro/Glacier system at 100 m grid spacing for surface and streamflow simulation. Evaluation of the WRF downscaling showed a good comparison with in situ meteorological observations for most of the simulation period. The WRF-Hydro/Glacier system reproduced the glacier surface winter/summer and net mass balance, snow depth, surface albedo and glacier runoff well compared to observations. The improved estimation of albedo has an appreciable impact on the discharge from the glacier during frequent precipitation periods. We have shown that the integrated snowpack system allows for improved glacier surface mass balance studies and hydrological studies

Investigating the representation of heatwaves from an ensemble of km-scale regional climate simulations within CORDEX-FPS convection

Heatwaves (HWs) are high-impact phenomena stressing both societies and ecosystems. Their intensity and frequency are expected to increase in a warmer climate over many regions of the world. While these impacts can be wide-ranging, they are potentially influenced by local to regional features such as topography, land cover, and urbanization. Here, we leverage recent advances in the very high-resolution modelling required to elucidate the impacts of heatwaves at these fine scales. Further, we aim to understand how the new generation of km-scale regional climate models (RCMs) modulates the representation of heatwaves over a well-known climate change hot spot. We analyze an ensemble of 15 convection-permitting regional climate model (CPRCM, ~ 2–4 km grid spacing) simulations and their driving, convection-parameterized regional climate model (RCM, ~ 12–15 km grid spacing) simulations from the CORDEX Flagship Pilot Study on Convection. The focus is on the evaluation experiments (2000–2009) and three subdomains with a range of climatic characteristics. During HWs, and generally in the summer season, CPRCMs exhibit warmer and drier conditions than their driving RCMs. Higher maximum temperatures arise due to an altered heat flux partitioning, with daily peaks up to ~ 150 W/m$^{2}$ larger latent heat in RCMs compared to the CPRCMs. This is driven by a 5–25% lower soil moisture content in the CPRCMs, which is in turn related to longer dry spell length (up to double). It is challenging to ascertain whether these differences represent an improvement. However, a point-scale distribution-based maximum temperature evaluation, suggests that this CPRCMs warmer/drier tendency is likely more realistic compared to the RCMs, with ~ 70% of reference sites indicating an added value compared to the driving RCMs, increasing to 95% when only the distribution right tail is considered. Conversely, a CPRCMs slight detrimental effect is found according to the upscaled grid-to-grid approach over flat areas. Certainly, CPRCMs enhance dry conditions, with knock-on implications for summer season temperature overestimation. Whether this improved physical representation of HWs also has implications for future changes is under investigation

Precipitation frequency in Med-CORDEX and EURO-CORDEX ensembles from 0.44° to convection-permitting resolution: impact of model resolution and convection representation

Recent studies using convection-permitting (CP) climate simulations have demonstrated a step-change in the representation of heavy rainfall and rainfall characteristics (frequency-intensity) compared to coarser resolution Global and Regional climate models. The goal of this study is to better understand what explains the weaker frequency of precipitation in the CP ensemble by assessing the triggering process of precipitation in the different ensembles of regional climate simulations available over Europe. We focus on the statistical relationship between tropospheric temperature, humidity and precipitation to understand how the frequency of precipitation over Europe and the Mediterranean is impacted by model resolution and the representation of convection (parameterized vs. explicit). We employ a multi-model data-set with three different resolutions (0.44°, 0.11° and 0.0275°) produced in the context of the MED-CORDEX, EURO-CORDEX and the CORDEX Flagship Pilot Study "Convective Phenomena over Europe and the Mediterranean" (FPSCONV). The multi-variate approach is applied to all model ensembles, and to several surface stations where the integrated water vapor (IWV) is derived from Global Positioning System (GPS) measurements. The results show that all model ensembles capture the temperature dependence of the critical value of IWV (IWVcv), above which an increase in precipitation frequency occurs, but the differences between the models in terms of the value of IWVcv, and the probability of its being exceeded, can be large at higher temperatures. The lower frequency of precipitation in convection-permitting simulations is not only explained by higher temperatures but also by a higher IWVcv necessary to trigger precipitation at similar temperatures, and a lower probability to exceed this critical value. The spread between models in simulating IWVcv and the probability of exceeding IWVcv is reduced over land in the ensemble of models with explicit convection, especially at high temperatures, when the convective fraction of total precipitation becomes more important and the influence of the representation of entrainment in models thus becomes more important. Over lowlands, both model resolution and convection representation affect precipitation triggering while over mountainous areas, resolution has the highest impact due to orography-induced triggering processes. Over the sea, since lifting is produced by large-scale convergence, the probability to exceed IWVcv does not depend on temperature, and the model resolution does not have a clear impact on the results

Reconciling conflicting evidence for the cause of the observed early 21st century Eurasian cooling

It is now well established that the Arctic is warming at a faster rate than the global average. This warming, which has been accompanied by a dramatic decline in sea ice, has been linked to cooling over the Eurasian subcontinent over recent decades, most dramatically during the period 1998–2012. This is a counter-intuitive impact under global warming given that land regions should warm more than ocean (and the global average). Some studies have proposed a causal teleconnection from Arctic sea-ice retreat to Eurasian wintertime cooling; other studies argue that Eurasian cooling is mainly driven by internal variability. Overall, there is an impression of strong disagreement between those holding the “ice-driven” versus “internal variability” viewpoints. Here, we offer an alternative framing showing that the sea ice and internal variability views can be compatible. Key to this is viewing Eurasian cooling through the lens of dynamics (linked primarily to internal variability with some potential contribution from sea ice; cools Eurasia) and thermodynamics (linked to sea-ice retreat; warms Eurasia). This approach, combined with recognition that there is uncertainty in the hypothesized mechanisms themselves, allows both viewpoints (and others) to co-exist and contribute to our understanding of Eurasian cooling. A simple autoregressive model shows that Eurasian cooling of this magnitude is consistent with internal variability, with some periods exhibiting stronger cooling than others, either by chance or by forced changes. Rather than posit a “yes-or-no” causal relationship between sea ice and Eurasian cooling, a more constructive way forward is to consider whether the cooling trend was more likely given the observed sea-ice loss, as well as other sources of low-frequency variability. Taken in this way both sea ice and internal variability are factors that affect the likelihood of strong regional cooling in the presence of ongoing global warming.</p

The first multi-model ensemble of regional climate simulations at kilometer-scale resolution. Part I: Evaluation of precipitation

Here we present the first multi-model ensemble of regional climate simulations at kilometer-scale horizontal grid spacing over a decade long period. A total of 23 simulations run with a horizontal grid spacing of ∼ 3 km, driven by ERA-Interim reanalysis, and performed by 22 European research groups are analysed. Six different regional climate models (RCMs) are represented in the ensemble. The simulations are compared against available high-resolution precipitation observations and coarse resolution (∼ 12 km) RCMs with parameterized convection. The model simulations and observations are compared with respect to mean precipitation, precipitation intensity and frequency, and heavy precipitation on daily and hourly timescales in different seasons. The results show that kilometer-scale models produce a more realistic representation of precipitation than the coarse resolution RCMs. The most significant improvements are found for heavy precipitation and precipitation frequency on both daily and hourly time scales in the summer season. In general, kilometer-scale models tend to produce more intense precipitation and reduced wet-hour frequency compared to coarse resolution models. On average, the multi-model mean shows a reduction of bias from ∼ −40 at 12 km to ∼ −3 at 3 km for heavy hourly precipitation in summer. Furthermore, the uncertainty ranges i.e. the variability between the models for wet hour frequency is reduced by half with the use of kilometer-scale models. Although differences between the model simulations at the kilometer-scale and observations still exist, it is evident that these simulations are superior to the coarse-resolution RCM simulations in the representing precipitation in the present-day climate, and thus offer a promising way forward for investigations of climate and climate change at local to regional scales. © 2021, The Author(s)

The first multi-model ensemble of regional climate simulations at kilometer-scale resolution, part I: evaluation of precipitation

Here we present the first multi-model ensemble of regional climate simulations at kilometer-scale horizontal grid spacing over a decade long period. A total of 23 simulations run with a horizontal grid spacing of ∼3 km, driven by ERA-Interim reanalysis, and performed by 22 European research groups are analysed. Six different regional climate models (RCMs) are represented in the ensemble. The simulations are compared against available high-resolution precipitation observations and coarse resolution (∼ 12 km) RCMs with parameterized convection. The model simulations and observations are compared with respect to mean precipitation, precipitation intensity and frequency, and heavy precipitation on daily and hourly timescales in different seasons. The results show that kilometer-scale models produce a more realistic representation of precipitation than the coarse resolution RCMs. The most significant improvements are found for heavy precipitation and precipitation frequency on both daily and hourly time scales in the summer season. In general, kilometer-scale models tend to produce more intense precipitation and reduced wet-hour frequency compared to coarse resolution models. On average, the multi-model mean shows a reduction of bias from ∼ −40% at 12 km to ∼ −3% at 3 km for heavy hourly precipitation in summer. Furthermore, the uncertainty ranges i.e. the variability between the models for wet hour frequency is reduced by half with the use of kilometer-scale models. Although differences between the model simulations at the kilometer-scale and observations still exist, it is evident that these simulations are superior to the coarse-resolution RCM simulations in the representing precipitation in the present-day climate, and thus offer a promising way forward for investigations of climate and climate change at local to regional scales

Impact of Quasi‐Idealized Future Land Cover Scenarios at High Latitudes in Complex Terrain

Abstract Afforestation is gaining popularity as a climate mitigation policy in many countries, including high latitude regions such as Norway. However, the impacts of afforestation on local‐to‐regional climate is poorly understood. This study uses the Weather Research and Forecasting model to investigate the biogeophysical impacts of different forestry scenarios on the local‐to‐regional climate of Norway. The forestry scenarios considered are the conversion of open spaces to either evergreen forest by active afforestation or to mixed forest by natural succession. Results show both forestry scenarios lead to additional warming of surface temperatures in winter and spring (between 1.0°C and 1.5°C) and cooling in summer (between −1.6°C and −1.3°C). A temperature decomposition analysis shows that the warming in winter and spring is driven by surface albedo changes while summer cooling is driven by changes in sensible heat fluxes for afforestation and surface albedo for natural succession. Maximum 2 m air temperature increases considerably in spring in both forestry scenarios (∼0.8°C to 1.0°C). Analysis of precipitation, multiple climate indices and extremes, reveal little or no response to the different forestry scenarios. The largest societally relevant response to the forestry scenarios is the partial mitigation of the reduction in snow days expected from global warming by 10–20 days. This suggests that implementing current afforestation policies for climate mitigation in Norway may adversely exacerbate some effects of global warming locally while mitigating others. As such, the impacts of afforestation on the local‐to‐regional climate at high latitudes are complex and cannot support or dismiss afforestation as a climate mitigation policy

Intermittency of Arctic–mid-latitude teleconnections: stratospheric pathway between autumn sea ice and the winter North Atlantic Oscillation

There is an observed relationship linking Arctic sea ice conditions in autumn to mid-latitude weather the following winter. Of interest in this study is a hypothesized stratospheric pathway whereby reduced sea ice in the Barents and Kara seas enhances upward wave activity and wave-breaking in the stratosphere, leading to a weakening of the polar vortex and a transition of the North Atlantic Oscillation (NAO) to its negative phase. The Causal Effect Networks (CEN) framework is used to explore the stratospheric pathway between late autumn Barents–Kara sea ice and the February NAO, focusing on its seasonal evolution, timescale dependence, and robustness. Results indicate that the pathway is statistically detectable and has been relatively active over the 39-year observational period used here, explaining approximately 26&thinsp;% of the interannual variability in the February NAO. However, a bootstrap-based resampling test reveals that the pathway is highly intermittent: the full stratospheric pathway appears in only 16&thinsp;% of the sample populations derived from observations, with individual causal linkages ranging from 46&thinsp;% to 84&thinsp;% in occurrence rates. The pathway's intermittency is consistent with the weak signal-to-noise ratio of the atmospheric response to Arctic sea ice variability in modelling experiments and suggests that Arctic–mid-latitude teleconnections might be favoured in certain background states. On shorter timescales, the CEN detects two-way interactions between Barents–Kara sea ice and the mid-latitude circulation that indicate a role for synoptic variability associated with blocking over the Urals region and moist air intrusions from the Euro-Atlantic sector. This synoptic variability has the potential to interfere with the stratospheric pathway, thereby contributing to its intermittency. This study helps quantify the robustness of causal linkages within the stratospheric pathway, and provides insight into which linkages are most subject to sampling issues within the relatively short observational record. Overall, the results should help guide the analysis and design of ensemble modelling experiments required to improve physical understanding of Arctic–mid-latitude teleconnections.</p