R. Davy

Here, I present the climatology of the planetary boundary layer depth in 18 contemporary general circulation models (GCMs) in simulations of the late-twentieth-century climate that were part of phase 5 of the Coupled Model Intercomparison Project (CMIP5). We used a bulk Richardson methodology to establish the boundary layer depth from the 6-hourly synoptic-snapshot data available in the CMIP5 archives. We present an ensemble analysis of the climatological mean, diurnal cycle, and seasonal cycle of the boundary layer depth in these models and compare it to the climatologies from the ECMWF ERA-Interim reanalysis. Overall, we find that the CMIP5 models do a reasonably good job of reproducing the distribution of mean boundary layer depth, although the geographical patterns vary considerably between models. However, the models are biased toward weaker diurnal and seasonal cycles in the boundary layer depth and generally produce much deeper boundary layers at night and during the winter than are found in the reanalysis. These biases are likely to reduce the ability of these models to accurately represent other properties of the diurnal and seasonal cycles, and the sensitivity of these cycles to climate change.

R. Davy, L. Chen, E. Hanna

One of the defining features of both recent and historical cases of global climate change is Arctic amplification (AA). This is the more rapid change in the surface air temperature (SAT) in the Arctic compared to some wider reference region, such as the Northern Hemisphere (NH) mean. Many different metrics have been developed to quantify the degree of AA based on SAT anomalies, trends and variability. The use of different metrics, as well as the choice of data set to use, can affect conclusions about the magnitude and temporal variability of AA. Here we review the established metrics of AA to see how well they agree upon the temporal signature of AA, such as the multi‐decadal variability, and assess the consistency in these metrics across different commonly used data sets which cover both the early and late 20th century warming in the Arctic. We find the NOAA 20th century reanalysis most closely matches the observations when using metrics based upon SAT trends (A2), variability (A3) and regression (A4) of the SAT anomalies, and the ERA 20th century reanalysis is closest to the observations in the SAT anomalies (A1) and variability of SAT anomalies (A3). However, there are large seasonal differences in the consistency between data sets. Moreover, the largest differences between the century‐long reanalysis products and observations are during the early warming period, likely due to the sparseness of the observations in the Arctic at that time. In the modern warming period, the high density of observations strongly constrains all the reanalysis products, whether they include satellite observations or only surface observations. Thus, all the reanalysis and observation products produce very similar magnitudes and temporal variability in the degree of AA during the recent warming period.

R. Davy, I. Esau

The Earth has warmed in the last century and a large component of that warming has been attributed to increased anthropogenic greenhouse gases. There are also numerous processes that introduce strong, regionalized variations to the overall warming trend. However, the ability of a forcing to change the surface air temperature depends on its spatial and temporal distribution. Here we show that the efficacy of a forcing is determined by the effective heat capacity of the atmosphere, which in cold and dry climates is defined by the depth of the planetary boundary layer. This can vary by an order of magnitude on different temporal and spatial scales, and so we get a strongly amplified temperature response in shallow boundary layers. This must be accounted for to assess the efficacy of a climate forcing, and also implies that multiple climate forcings cannot be linearly combined to determine the temperature response.

After extensive efforts over the course of a decade, convective-scale weather forecasts with horizontal grid spacings of 1–5 km are now operational at national weather services around the world, accompanied by ensemble prediction systems (EPSs). However, though already operational, the capacity of forecasts for this scale is still to be fully exploited by overcoming the fundamental difficulty in prediction: the fully three-dimensional and turbulent nature of the atmosphere. The prediction of this scale is totally different from that of the synoptic scale (103 km), with slowly evolving semigeostrophic dynamics and relatively long predictability on the order of a few days.

Even theoretically, very little is understood about the convective scale compared to our extensive knowledge of the synoptic-scale weather regime as a partial differential equation system, as well as in terms of the fluid mechanics, predictability, uncertainties, and stochasticity. Furthermore, there is a requirement for a drastic modification of data assimilation methodologies, physics (e.g., microphysics), and parameterizations, as well as the numerics for use at the convective scale. We need to focus on more fundamental theoretical issues—the Liouville principle and Bayesian probability for probabilistic forecasts—and more fundamental turbulence research to provide robust numerics for the full variety of turbulent flows.

The present essay reviews those basic theoretical challenges as comprehensibly as possible. The breadth of the problems that we face is a challenge in itself: an attempt to reduce these into a single critical agenda should be avoided.

R. Davy, N. Gnatiuk, L. Pettersson, L. Bobylev

We may anticipate that climate change will bring changes to the intensity and variability of near surface winds, either through local effects or by altering the large-scale flow. The impact of climate change on European wind resources has been assessed using a single-model-ensemble of the latest regional climate model from the Rossby Centre, RCA4. These simulations used data from five of the global climate models in the contemporary Climate Model Intercomparison Project (CMIP5) as boundary conditions, and the results are publicly available under the COordinated Regional climate Downscaling EXperiment (CORDEX) project. Overall we find a consistent pattern of a decrease in the wind resources over the European domain under both the RCP 4.5 and RCP 8.5 scenarios, although there are some regions, principally North Africa and the Barents Sea, with projected increases in wind resources. The pattern of change is both robust across the choice of scenario, and persistent: there is a very similar pattern of change found in the latter part of the 21st century as in the earlier. A case study was chosen to assess the potential for offshore wind-farms in the Black Sea region. We developed a realistic methodology for extrapolating near-surface wind speeds up to hub-height using a time-varying roughness length, and determined the extractable wind power at hub-height using a realistic model of contemporary wind-turbine energy production. We demonstrate that, unlike much of the Mediterranean basin, there is no robust pattern of a negative climate change impact on wind resources in the studied regions of the Black Sea. Furthermore, the seasonality of wind resources, with a strong peak in the winter, matches well to the seasonality of energy-demand in the region, making offshore wind-farms in the Black Sea region a viable source of energy for neighboring countries.

R. Davy, N. Gnatiuk, L. Pettersson, L. Bobylev

We may anticipate that climate change will bring changes to the intensity and variability of near surface winds, either through local effects or by altering the large-scale flow. The impact of climate change on European wind resources has been assessed using a single-model-ensemble of the latest regional climate model from the Rossby Centre, RCA4. These simulations used data from five of the global climate models in the contemporary Climate Model Intercomparison Project (CMIP5) as boundary conditions, and the results are publicly available under the COordinated Regional climate Downscaling EXperiment (CORDEX) project. Overall we find a consistent pattern of a decrease in the wind resources over the European domain under both the RCP 4.5 and RCP 8.5 scenarios, although there are some regions, principally North Africa and the Barents Sea, with projected increases in wind resources. The pattern of change is both robust across the choice of scenario, and persistent: there is a very similar pattern of change found in the latter part of the 21st century as in the earlier. A case study was chosen to assess the potential for offshore wind-farms in the Black Sea region. We developed a realistic methodology for extrapolating near-surface wind speeds up to hub-height using a time-varying roughness length, and determined the extractable wind power at hub-height using a realistic model of contemporary wind-turbine energy production. We demonstrate that, unlike much of the Mediterranean basin, there is no robust pattern of a negative climate change impact on wind resources in the studied regions of the Black Sea. Furthermore, the seasonality of wind resources, with a strong peak in the winter, matches well to the seasonality of energy-demand in the region, making offshore wind-farms in the Black Sea region a viable source of energy for neighboring countries.

A long-term climatology of cloudiness over the Norwegian, Barents, and Kara Seas (NBK) based on visual surface observations is presented. Annual mean total cloud cover (TCC) is almost equal over solid-ice (SI) and open-water (OW) regions of the NBK (73% ± 3% and 76% ± 2%, respectively). In general, TCC has higher intra- and interannual variability over SI than over OW. A decrease of TCC in the middle of the twentieth century and an increase in the last few decades was found at individual stations and for the NBK as a whole. In most cases these changes are statistically significant with magnitudes exceeding the data uncertainty that is associated with the surface observations. The most pronounced trends are observed in autumn when the largest changes to the sea ice concentration (SIC) occur. TCC over SI correlates significantly with SIC in the Barents Sea, with a statistically significant correlation coefficient between annual TCC and SIC of −0.38 for the period 1936–2013. Cloudiness over OW shows nonsignificant correlation with SIC. An overall increase in the frequency of broken and scattered cloud conditions and a decrease in the frequency of overcast and cloudless conditions were found over OW. These changes are statistically significant and likely to be connected with the long-term changes of morphological types (an increase of convective and a decrease of stratiform cloud amounts).

  • LinkedIn Social Icon
  • Facebook Social Icon
  • Twitter Social Icon
  • researchgate-logo

©2018 by Richard Davy. Proudly created with Wix.com