scholarly journals Dynamical Downscaling of Surface Air Temperature and Wind Field Variabilities over the Southeastern Levantine Basin, Mediterranean Sea

Climate ◽  
2021 ◽  
Vol 9 (10) ◽  
pp. 150
Author(s):  
Mohamed ElBessa ◽  
Saad Mesbah Abdelrahman ◽  
Kareem Tonbol ◽  
Mohamed Shaltout
Keyword(s):  
Wind Speed ◽  
Air Temperature ◽  
Wind Field ◽  
Climate Model ◽  
Dynamical Downscaling ◽  
Surface Wind ◽  
Surface Air Temperature ◽  
Warming Trend ◽  
Climate Data ◽  
Near Surface

The characteristics of near surface air temperature and wind field over the Southeastern Levantine (SEL) sub-basin during the period 1979–2018 were simulated. The simulation was carried out using a dynamical downscaling approach, which requires running a regional climate model system (RegCM-SVN6994) on the study domain, using lower-resolution climate data (i.e., the fifth generation of ECMWF atmospheric reanalysis of the global climate ERA5 datasets) as boundary conditions. The quality of the RegCM-SVN simulation was first verified by comparing its simulations with ERA5 for the studied region from 1979 to 2018, and then with the available five WMO weather stations from 2007 to 2018. The dynamical downscaling results proved that RegCM-SVN in its current configuration successfully simulated the observed surface air temperature and wind field. Moreover, RegCM-SVN was proved to provide similar or even better accuracy (during extreme events) than ERA5 in simulating both surface air temperature and wind speed. The simulated annual mean T2m by RegCM-SVN (from 1979 to 2018) was 20.9 °C, with a positive warming trend of 0.44 °C/decade over the study area. Moreover, the annual mean wind speed by RegCM-SVN was 4.17 m/s, demonstrating an annual negative trend of wind speed over 92% of the study area. Surface air temperatures over SEL mostly occurred within the range of 4–31 °C; however, surface wind speed rarely exceeded 10 m/s. During the study period, the seasonal features of T2m showed a general warming trend along the four seasons and showed a wind speed decreasing trend during spring and summer. The results of the RegCM-SVN simulation constitute useful information that could be utilized to fully describe the study area in terms of other atmospheric parameters.

Evaluating temperature extremes in CMIP6 simulations using statistically proper evaluation methods

2021 ◽  
Author(s):  
Thordis Thorarinsdottir ◽  
Jana Sillmann ◽  
Marion Haugen ◽  
Nadine Gissibl ◽  
Marit Sandstad
Keyword(s):  
Air Temperature ◽  
Model Evaluation ◽  
Climate Models ◽  
Climate Model ◽  
Mean Squared Error ◽  
Surface Air Temperature ◽  
Cmip5 Models ◽  
Model Output ◽  
Intergovernmental Panel ◽  
Near Surface

<p>Reliable projections of extremes in near-surface air temperature (SAT) by climate models become more and more important as global warming is leading to significant increases in the hottest days and decreases in coldest nights around the world with considerable impacts on various sectors, such as agriculture, health and tourism.</p><p>Climate model evaluation has traditionally been performed by comparing summary statistics that are derived from simulated model output and corresponding observed quantities using, for instance, the root mean squared error (RMSE) or mean bias as also used in the model evaluation chapter of the fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR5). Both RMSE and mean bias compare averages over time and/or space, ignoring the variability, or the uncertainty, in the underlying values. Particularly when interested in the evaluation of climate extremes, climate models should be evaluated by comparing the probability distribution of model output to the corresponding distribution of observed data.</p><p>To address this shortcoming, we use the integrated quadratic distance (IQD) to compare distributions of simulated indices to the corresponding distributions from a data product. The IQD is the proper divergence associated with the proper continuous ranked probability score (CRPS) as it fulfills essential decision-theoretic properties for ranking competing models and testing equality in performance, while also assessing the full distribution.</p><p>The IQD is applied to evaluate CMIP5 and CMIP6 simulations of monthly maximum (TXx) and minimum near-surface air temperature (TNn) over the data-dense regions Europe and North America against both observational and reanalysis datasets. There is not a notable difference between the model generations CMIP5 and CMIP6 when the model simulations are compared against the observational dataset HadEX2. However, the CMIP6 models show a better agreement with the reanalysis ERA5 than CMIP5 models, with a few exceptions. Overall, the climate models show higher skill when compared against ERA5 than when compared against HadEX2. While the model rankings vary with region, season and index, the model evaluation is robust against changes in the grid resolution considered in the analysis.</p>

scholarly journals Outdoor thermal performance simulation in campus area during the dry season, Yogyakarta

2019 ◽  
Vol 2 (1) ◽  
pp. 15
Author(s):  
Hasti Widyasamratri ◽  
Arif Kusumawanto ◽  
Fadhilla Tri Nugrahaini
Keyword(s):  
Wind Speed ◽  
Air Temperature ◽  
Thermal Performance ◽  
Meteorological Parameters ◽  
Anthropogenic Activities ◽  
Surface Air Temperature ◽  
Dry Season ◽  
Performance Simulation ◽  
Near Surface ◽  
Significant Area

The outdoor thermal performance reflects the microclimate condition in any significant area. This study simulated the thermal performance with measured and modeled three meteorological parameters, air temperature (Ta), relative humidity (RH), and wind speed in the dry season tropical city. The research focused on thermal performance simulation and distribution, here, we were neglecting anthropogenic activities as the heat source. The result showed that there were different ranges between a measured and simulated value of Ta, RH, and wind speed. The highest Ta difference between measure and simulation occurred at 11 AM, which was 1.97⸰C. The highest difference of RH occurred at 13 PM (26.75%), and the highest different of wind speed was at 11 AM (0.37 m/s) respectively. The heat distribution in the focus area was influenced by the solar direction which impacted the ground and near-surface air temperature.  

scholarly journals Evaluation of Arctic sea-ice drift and its dependency on near-surface wind and sea-ice concentration and thickness in the coupled regional climate model HIRHAM-NAOSIM

2019 ◽  
Author(s):  
Xiaoyong Yu ◽  
Annette Rinke ◽  
Wolfgang Dorn ◽  
Gunnar Spreen ◽  
Christof Lüpkes ◽  
...  
Keyword(s):  
Wind Speed ◽  
Sea Ice ◽  
Climate Model ◽  
Regional Climate ◽  
Surface Wind ◽  
Arctic Sea Ice ◽  
Near Surface ◽  
Drift Speed ◽  
Ice Drift ◽  
Sea Ice Drift

Abstract. We examine the simulated Arctic sea-ice drift speed for the period 2003–2014 in the coupled Arctic regional climate model HIRHAM-NAOSIM 2.0. In particular, we evaluate the dependency of the drift speed on the near-surface wind speed and sea-ice conditions. Considering the seasonal cycle of Arctic basin averaged drift speed, the model reproduces the summer-autumn drift speed well, but significantly overestimates the winter-spring drift speed, compared to satellite-derived observations. Also, the model does not capture the observed seasonal phase lag between drift and wind speed, but the simulated drift speed is more in phase with near-surface wind. The model calculates a realistic negative relationship between drift speed and ice thickness and between drift speed and ice concentration during summer-autumn when concentration is relatively low, but the correlation is weaker than observed. A daily grid-scale diagnostic indicates that the model reproduces the observed positive relationship between drift and wind speed. The strongest impact of wind changes on drift speed occurs for high and moderate wind speeds, with a low impact for calm conditions. The correlation under low-wind conditions is overestimated in the simulations, compared to observation/reanalysis. A sensitivity experiment demonstrates the significant effects of sea-ice form drag included by an improved parameterization of the transfer coefficients for momentum and heat over sea ice. However, this does not improve the agreement of the modelled drift speed/wind speed ratio with observations based on reanalysis for wind and remote sensing for sea ice drift. An improvement might be possible, among others, by tuning the open parameters of the parameterization in future.

scholarly journals Verification of the EURO-CORDEX RCM Historical Run Results over the Pannonian Basin for the Summer Season

Atmosphere ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 714
Author(s):  
Irida Lazić ◽  
Milica Tošić ◽  
Vladimir Djurdjević
Keyword(s):  
Air Temperature ◽  
Climate Models ◽  
Climate Model ◽  
Dynamical Downscaling ◽  
Pannonian Basin ◽  
Global Climate Model ◽  
Precipitation Amount ◽  
Summer Season ◽  
Positive Temperature ◽  
Near Surface

In previous projects that focused on dynamical downscaling over Europe, e.g., PRUDENCE and ENSEMBLES, many regional climate models (RCMs) tended to overestimate summer air temperature and underestimate precipitation in this season in Southern and Southeastern Europe, leading to the so-called summer drying problem. This bias pattern occurred not only in the RCM results but also in the global climate model (GCM) results, so knowledge of the model uncertainties and their cascade is crucial for understanding and interpreting future climate. Our intention with this study was to examine whether a warm-and-dry bias is also present in the state-of-the-art EURO-CORDEX multi-model ensemble results in the summer season over the Pannonian Basin. Verification of EURO-CORDEX RCMs was carried out by using the E-OBS gridded dataset of daily mean, minimum, and maximum near-surface air temperature and total precipitation amount with a horizontal resolution of 0.1 degrees (approximately 12 km × 12 km) over the 1971–2000 time period. The model skill for selected period was expressed in terms of four verification scores: bias, centered root mean square error (RMSE), spatial correlation coefficient, and standard deviation. The main findings led us to conclude that most of the RCMs that overestimate temperature also underestimate precipitation. For some models, the positive temperature and negative precipitation bias were more emphasized, which led us to conclude that the problem was still present in most of the analyzed simulations.

scholarly journals Polyphony of Short-Term Climatic Variations

Atmosphere ◽  
2021 ◽  
Vol 12 (9) ◽  
pp. 1145
Author(s):  
Dmitry M. Sonechkin ◽  
Nadezda V. Vakulenko
Keyword(s):  
Surface Air Temperature ◽  
Warming Trend ◽  
Chandler Wobble ◽  
Climate Data ◽  
Near Surface ◽  
Global Mean Temperature ◽  
Climate Evolution ◽  
Meteorological Observations ◽  
External Forces ◽  
Global Mean

It is widely accepted to believe that humanity is mainly responsible for the worldwide temperature growth during the period of instrumental meteorological observations. This paper aims to demonstrate that it is not so simple. Using a wavelet analysis on the example of the time series of the global mean near-surface air temperature created at the American National Climate Data Center (NCDC), some complex structures of inter-annual to multidecadal global mean temperature variations were discovered. The origin of which seems to be better attributable to the Chandler wobble in the Earth’s Pole motion, the Luni-Solar nutation, and the solar activity cycles. Each of these external forces is individually known to climatologists. However, it is demonstrated for the first time that responses of the climate system to these external forces in their integrity form a kind of polyphony superimposed on a general warming trend. Certainly, the general warming trend as such remains to be unconsidered. However, its role is not very essential in the timescale of a few decades. Therefore, it is this polyphony that will determine climate evolution in the nearest future, i.e., during the time most important for humanity currently.

scholarly journals Near-surface mean and gust wind speed in ERA5 across Sweden: towards an improved gust parametrization

2020 ◽  
Author(s):  
Lorenzo Minola ◽  
Fuqing Zhang ◽  
Cesar Azorin-Molina ◽  
Amir Ali Safaei Pirooz ◽  
Richard Flay ◽  
...  
Keyword(s):  
Wind Speed ◽  
Surface Wind ◽  
Surface Air Temperature ◽  
Surface Wind Speed ◽  
Economic Losses ◽  
Wind Gust ◽  
Reanalysis Dataset ◽  
Near Surface ◽  
Extreme Wind ◽  
Wind Events

<p>Driven by the twenty-century surface air temperature rise, extreme wind events could change in their frequency and magnitude of occurrence, with drastic impacts on human and ecosystems. As a matter of fact, windstorms and extreme wind conditions contribute to more than half of the economic losses associated with natural disasters in Europe. Across Scandinavia, the occurrence of wind gust events can affect aviation security, as well as damage buildings and forests, representing severe hazards to people, properties and transport. Comprehensive extreme wind datasets and analysis can help improving our understanding of these changes and help the society to cope with these changes. Unfortunately, due to the difficulty in measuring wind gust and the lack of homogeneous and continuous datasets across Sweden, it is challenging to assess and attribute their changes. Global reanalysis products represent a potential tool for assessing changes and impact of extreme winds, only if their ability in representing observed near-surface wind statistics can be demonstrated.</p><p>In this study the new ERA5 reanalysis product has been compared with hourly near-surface wind speed and gust observations across Sweden for 2013-2017. We found that ERA5 shows better agreement with both mean wind speed and gust measurements compared to the previous ERA-Interim reanalysis dataset. Especially across coastal regions, ERA5 has a closer agreement with observed climate statistics. However, significant discrepancies are still found for inland and high-altitude regions. Therefore, the gust parametrization used in ERA5 is further analyzed to better understand if the adopted gust formulation matches the physical processes behind the gust occurrence. Finally, an improved formulation of the gust parametrization is developed across Sweden and further tested for Norway, which is characterized by more complex topography.</p>

scholarly journals Evaluation of Arctic sea ice drift and its dependency on near-surface wind and sea ice conditions in the coupled regional climate model HIRHAM–NAOSIM

2020 ◽  
Vol 14 (5) ◽  
pp. 1727-1746
Author(s):  
Xiaoyong Yu ◽  
Annette Rinke ◽  
Wolfgang Dorn ◽  
Gunnar Spreen ◽  
Christof Lüpkes ◽  
...  
Keyword(s):  
Wind Speed ◽  
Sea Ice ◽  
Climate Model ◽  
Regional Climate ◽  
Surface Wind ◽  
Arctic Sea Ice ◽  
Near Surface ◽  
Drift Speed ◽  
Ice Drift ◽  
Sea Ice Drift

Abstract. We examine the simulated Arctic sea ice drift speed for the period 2003–2014 in the coupled Arctic regional climate model HIRHAM–NAOSIM 2.0. In particular, we evaluate the dependency of the drift speed on the near-surface wind speed and sea ice conditions. Considering the seasonal cycle of the Arctic basin averaged drift speed, the model reproduces the summer–autumn drift speed well but significantly overestimates the winter–spring drift speed, compared to satellite-derived observations. Also, the model does not capture the observed seasonal phase lag between drift and wind speed, but the simulated drift speed is more in phase with the near-surface wind. The model calculates a realistic negative correlation between drift speed and ice thickness and between drift speed and ice concentration during summer–autumn when the ice concentration is relatively low, but the correlation is weaker than observed. A daily grid-scale diagnostic indicates that the model reproduces the observed positive correlation between drift and wind speed. The strongest impact of wind changes on drift speed occurs for high and moderate wind speeds, with a low impact for rather calm conditions. The correlation under low-wind conditions is overestimated in the simulations compared to observation/reanalysis data. A sensitivity experiment demonstrates the significant effects of sea ice form drag from floe edges included by an improved parameterization of the transfer coefficients for momentum and heat over sea ice. However, this does not improve the agreement of the modeled drift speed / wind speed ratio with observations based on reanalysis data for wind and remote sensing data for sea ice drift. An improvement might be achieved by tuning parameters that are not well established by observations.

scholarly journals Validation of the ALARO-0 model within the EURO-CORDEX framework

2016 ◽  
Vol 9 (3) ◽  
pp. 1143-1152 ◽  
Author(s):  
Olivier Giot ◽  
Piet Termonia ◽  
Daan Degrauwe ◽  
Rozemien De Troch ◽  
Steven Caluwaerts ◽  
...  
Keyword(s):  
Air Temperature ◽  
Climate Model ◽  
Regional Climate ◽  
Surface Air Temperature ◽  
Convective Precipitation ◽  
Microphysics Scheme ◽  
Near Surface ◽  
Temperature And Precipitation ◽  
European Climate ◽  
Jackknife Procedure

Abstract. Using the regional climate model ALARO-0, the Royal Meteorological Institute of Belgium and Ghent University have performed two simulations of the past observed climate within the framework of the Coordinated Regional Climate Downscaling Experiment (CORDEX). The ERA-Interim reanalysis was used to drive the model for the period 1979–2010 on the EURO-CORDEX domain with two horizontal resolutions, 0.11 and 0.44°. ALARO-0 is characterised by the new microphysics scheme 3MT, which allows for a better representation of convective precipitation. In Kotlarski et al. (2014) several metrics assessing the performance in representing seasonal mean near-surface air temperature and precipitation are defined and the corresponding scores are calculated for an ensemble of models for different regions and seasons for the period 1989–2008. Of special interest within this ensemble is the ARPEGE model by the Centre National de Recherches Météorologiques (CNRM), which shares a large amount of core code with ALARO-0. Results show that ALARO-0 is capable of representing the European climate in an acceptable way as most of the ALARO-0 scores lie within the existing ensemble. However, for near-surface air temperature, some large biases, which are often also found in the ARPEGE results, persist. For precipitation, on the other hand, the ALARO-0 model produces some of the best scores within the ensemble and no clear resemblance to ARPEGE is found, which is attributed to the inclusion of 3MT. Additionally, a jackknife procedure is applied to the ALARO-0 results in order to test whether the scores are robust, meaning independent of the period used to calculate them. Periods of 20 years are sampled from the 32-year simulation and used to construct the 95 % confidence interval for each score. For most scores, these intervals are very small compared to the total ensemble spread, implying that model differences in the scores are significant.

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