When using the Weather Research and Forecasting (WRF) modelling system it is necessary to choose between many parametrisations for each physics option. This study examines the performance of various ...physics scheme combinations on the simulation of a series of rainfall events near the south-east coast of Australia known as East Coast Lows. A thirty-six member multi-physics ensemble was created such that each member had a unique set of physics parametrisations. No single ensemble member was found to perform best for all events, variables and metrics. This is reflected in the fact that different climate variables are found to be sensitive to different physical parametrisations. While a standardised super-metric can be used to identify best performers, a step-wise decision approach described here, allows explicit recognition of the “robustness” of choosing one parameterisation over another, allowing the identification of a group of “equally robustly” performing physics combinations. These results suggest that the Mellor-Yamada-Janjic planetary boundary layer scheme and the Betts-Miller-Janjic cumulus scheme can be chosen with some robustness. Possibly with greater confidence, the results also suggest that the Yonsei University planetary boundary layer scheme, Kain-Fritsch cumulus scheme and RRTMG radiation scheme should not be used in combination in this region. Results further indicate that the selection of physics scheme options has larger impact on model performance during the more intensive rainfall events.
Global reanalysis products are important tools across disciplines to study past meteorological changes and are especially useful for wind energy resource evaluations. Studies of observed wind speed ...show that land surface wind speed declined globally since the 1960s (known as global terrestrial stilling) but reversed with a turning point around 2010. Whether the declining trend and the turning point have been captured by reanalysis products remains unknown so far. To fill this research gap, a systematic assessment of climatological winds and trends in five reanalysis products (ERA5, ERA-Interim, MERRA-2, JRA-55, and CFSv2) was conducted by comparing gridcell time series of 10-m wind speed with observational data from 1439 in situ meteorological stations for the period 1989–2018. Overall, ERA5 is the closest to the observations according to the evaluation of climatological winds. However, substantial discrepancies were found between observations and simulated wind speeds. No reanalysis product showed similar change to that of the global observations, although some showed regional agreement. This discrepancy between observed and reanalysis land surface wind speed indicates the need for prudence when using reanalysis products for the evaluation and prediction of winds. The possible reasons for the inconsistent wind speed trends between reanalysis products and observations are analyzed. The results show that wind energy production should select different products for different regions to minimize the discrepancy with observations.
Dynamical downscaling attempts to provide regional detail to climate change projections that subsequently can be used as input to climate change impact models. However, unlike forecasts by numerical ...weather prediction models, downscaled projections cannot be tested for skill because the future of interest is decades away. Nevertheless, models can be tested in terms of how well they simulate current weather or climate, thus giving an indication of skill in representing the process of interest. Here, six configurations using different combinations of three microphysics and two planetary boundary layer schemes are assessed on their skill to simulate desired characteristics in daily rainfall fields from three two week simulations in southeast Australia; ‘desired’ meaning desirable in relation to the intended application. Of different metrics and analysis assessed, a metric based on variography analysis, summarising characteristics about spatial variability and dissimilarity, is shown to provide the most informative guidance relative to the desirable characteristics.
•Six configurations of a regional climate model are assessed for water resource impact work.•Model ensemble comprises three microphysics and two planetary boundary layer parameter schemes.•Meaningful metrics are derived from an understanding of model application needs.•Metrics targeting spatial characteristics in daily rainfall fields are applied to determine skill.•Variography analysis quantifies desirable characteristics in daily rainfall patterns.
Convective permitting simulations are increasingly pursued for providing physically more credible climate projections of rainfall. Their value is likely to be greater for regions where increased ...resolution not only resolves physical processes better, but also the topographic features of the target domain. Here, we assess the skill of convective permitting simulations to simulate rainfall for water resource assessment work in a climate change context for southeast Australia. Output on 2 and 10 km grid‐length resolution from a 5‐year regional climate model simulation is assessed for skill in simulating mean seasonal climatologies for days with low or high observed rainfall intensities. Comparison is conducted on spatial grids and for 25 catchments across the study region. No significant difference in skill was found in the loss differential when using absolute error for spatial fields of mean climatologies. Measures focusing on spatial similarity and accuracy in position of high rainfall areas indicate somewhat better skill in the 2 km simulation with regard to positioning (in autumn and winter), and with regard to spatial variability (in autumn and spring). Significant difference in skill was shown when comparing the simulated data sets on a catchment basis; seasonally 5–7 catchments in favor of the 10 km output and somewhat less for the 2 km output (3–6 catchments). When using correlation skill as the test measure, results are overwhelmingly in favor of the 2 km output. We cautiously suggest that results may be overly pessimistic for the 2 km simulation because of inadequate representation of rainfall in high altitude areas in observations.
Key Points
Convective permitting rainfall fields were visually more similar to observed, but not significantly better than coarser resolution output
Positional errors of high rainfall areas in convective permitting output have marked influence on objective verification metrics
Assessing skill on catchment scale enhance the influence of displacement errors, favoring coarser and smoother resolution simulations
This study examines the subset climate model ensemble size required to reproduce certain statistical characteristics from a full ensemble. The ensemble characteristics examined are the root mean ...square error, the ensemble mean and standard deviation. Subset ensembles are created using measures that consider the simulation performance alone or include a measure of simulation independence relative to other ensemble members. It is found that the independence measure is able to identify smaller subset ensembles that retain the desired full ensemble characteristics than either of the performance based measures. It is suggested that model independence be considered when choosing ensemble subsets or creating new ensembles.
Marine pollution impacts coastal nations around the world, and more so: (a) in confined maritime areas with significant marine traffic, (b) where exploitation of natural and mineral resources is ...taking place, or (c) in regions witnessing pressure from tourism, local population growth, and industry. In this work, Digital Elevation Models, hydrographic, and climatic data are used together with computer simulations to understand the control of climate change on marine pollution. The results show that different climate change signals can potentially alter the flow and concentration of pollution in the European Seas, when compared to the present day. Ultimately, this work identifies the main sources of marine pollution as: (1) rivers and streams near cities and industrialised areas, (2) coastal areas experiencing sudden demographic pressures, (3) offshore shipping lanes in which oil and other marine debris are released, and (4) areas of rugged seafloor where industrial fishing takes place. This paper finishes by describing new educational material prepared to teach school children around the world. It explains why how a new training curriculum and e-game developed by Sea4All can be crucial in future Environmental Education and Education for a Sustainable Development.
The term ‘downscaling’ refers to the process of translating information from global climate model simulations to a finer spatial resolution. There are numerous methods by which this translation of ...information can occur. For users of downscaled information, it is important to have some understanding of the properties of different methods (in terms of their capabilities and limitations to convey the change signal, as simulated by the global model), as these dictate the type of applications that the downscaled information can be used for in impact, adaptation, and vulnerability research. This article provides an appraisal of downscaling in terms of its perceived purpose and value for informing on plausible impacts due to climate change and for underpinning regional risk assessments. The concepts climate realism and physical plausibility of change are introduced to qualify the broad scale properties associated with different categories of downscaling approaches; the former concerning the skill of different approaches to represent regional climate characteristics and the latter their skill in simulating regional climate change. Aspects of change not captured by global climate models, due to resolution or regional factors, may be captured by downscaling. If these aspects are of interest, then downscaling may be useful once it has been demonstrated to add value. For cases where the broad scale change to the mean climate is of interest, or where there is no demonstrated added value from downscaling, then there is a wide range of regionalization methods that are suitable for practitioners in the impact, adaptation, and vulnerability field. WIREs Clim Change 2015, 6:301–319. doi: 10.1002/wcc.339
This article is categorized under:
Assessing Impacts of Climate Change > Scale Issues
Assessing Impacts of Climate Change > Scenario Development and Application
There are few studies providing a more comprehensive picture of advanced hybrid closed-loop (AHCL) systems in clinical practice. The aim was to evaluate the effects of the AHCL systems, Tandem
t: ...slim X2™ with Control IQ™, and MiniMed™ 780G, on glucose control, safety, treatment satisfaction, and practical barriers for individuals with type 1 diabetes.
One hundred forty-two randomly selected adults with type 1 diabetes at six diabetes outpatient clinics in Sweden at any time treated with either the Tandem Control IQ (TCIQ) or the MiniMed 780G system were included. Glycated hemoglobin A1c (HbA1c) and glucose metrics were evaluated. Treatment satisfaction and practical barriers were examined via questionnaires.
Mean age was 42 years, median follow-up was 1.7 years, 58 (40.8%) were females, 65% used the TCIQ system. Glycated hemoglobin A1c was reduced by 0.6% (6.8 mmol/mol; 95% confidence interval CI = 0.5-0.8% 5.3-8.2 mmol/mol;
< .001), from 7.3% to 6.7% (57-50 mmol/mol). Time in range (TIR) increased with 14.5% from 57.0% to 71.5% (95% CI = 12.2%-16.9%;
< .001). Time below range (TBR) (<70 mg/dL, <3.9 mmol/L) decreased from 3.8% to 1.6% (
< .001). The standard deviation of glucose values was reduced from 61 to 51 mg/dL (3.4-2.9 mmol/L,
< .001) and the coefficient of variation from 35% to 33% (
< .001). Treatment satisfaction increased, score 14.8 on the Diabetes Treatment Satisfaction Questionnaire (DTSQ) (change version ranging from -18 to 18,
< .001). Four severe hypoglycemia events were detected and no cases of ketoacidosis. Skin problems were experienced by 32.4% of the study population.
Advanced hybrid closed-loop systems improve glucose control with a reasonable safety profile and high treatment satisfaction. Skin problems are common adverse events.
The nonhomogeneous hidden Markov model (NHMM) statistical downscaling model, 38 catchments in southeast Australia and 19 general circulation models (GCMs) were used in this study to demonstrate ...statistical downscaling uncertainties caused by equifinality to and transferability. That is to say, there could be multiple sets of predictors that give similar daily rainfall simulation results for both calibration and validation periods, but project different amounts (or even directions of change) of rainfall changing in the future. Results indicated that two sets of predictors (Set 1 with predictors of sea level pressure north-south gradient, u-wind at 700hPa, v-wind at 700hPa, and specific humidity at 700hPa and Set 2 with predictors of sea level pressure north-south gradient, u-wind at 700hPa, v-wind at 700hPa, and dewpoint temperature depression at 850hPa) as inputs to the NHMM produced satisfactory results of seasonal rainfall in comparison with observations. For example, during the model calibration period, the relative errors across the 38 catchments ranged from 0.48 to 1.76% with a mean value of 1.09% for the predictor Set 1, and from 0.22 to 2.24% with a mean value of 1.16% for the predictor Set 2. However, the changes of future rainfall from NHMM projections based on 19 GCMs produced projections with a different sign for these two different sets of predictors: Set 1 predictors project an increase of future rainfall with magnitudes depending on future time periods and emission scenarios, but Set 2 predictors project a decline of future rainfall. Such divergent projections may present a significant challenge for applications of statistical downscaling as well as climate change impact studies, and could potentially imply caveats in many existing studies in the literature.
•The choice of predictor is one of the most influential steps in the application and development of statistical downscaling;•This study provides evidence for the existence of equifinality and transferability issuese;•The equifinality and transferability present a significant challenge for applications of statistical downscaling;•The equifinality and transferability could imply caveats for many existing studies in the literature;•A few guidelines are discussed for selecting predictor set, which provides a reliable rainfall projection for a future climate.
Bluetongue, an economically important animal disease, can be spread over long distances by carriage of insect vectors (
Culicoides
biting midges) on the wind. The weather conditions which influence ...the midge’s flight are controlled by synoptic scale atmospheric circulations. A method is proposed that links wind-borne dispersion of the insects to synoptic circulation through the use of a dispersion model in combination with principal component analysis (PCA) and cluster analysis. We illustrate how to identify the main synoptic situations present during times of midge incursions into the UK from the European continent. A PCA was conducted on high-pass-filtered mean sea-level pressure data for a domain centred over north-west Europe from 2005 to 2007. A clustering algorithm applied to the PCA scores indicated the data should be divided into five classes for which averages were calculated, providing a classification of the main synoptic types present. Midge incursion events were found to mainly occur in two synoptic categories; 64.8% were associated with a pattern displaying a pressure gradient over the North Atlantic leading to moderate south-westerly flow over the UK and 17.9% of the events occurred when high pressure dominated the region leading to south-easterly or easterly winds. The winds indicated by the pressure maps generally compared well against observations from a surface station and analysis charts. This technique could be used to assess frequency and timings of incursions of virus into new areas on seasonal and decadal timescales, currently not possible with other dispersion or biological modelling methods.
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