scholarly journals Sensitivity Evaluation of Spectral Nudging Schemes in Historical Dynamical Downscaling for South Asia

2017 ◽  
Vol 2017 ◽  
pp. 1-20 ◽  
Author(s):  
Mehwish Ramzan ◽  
Suryun Ham ◽  
Muhammad Amjad ◽  
Eun-Chul Chang ◽  
Kei Yoshimura
Keyword(s):  
South Asia ◽  
Dynamical Downscaling ◽  
Regional Climate ◽  
Weather Conditions ◽  
Monsoon Precipitation ◽  
Short Term ◽  
Spectral Nudging ◽  
Sensitivity Evaluation ◽  
Constant Strength

Sensitivity experiments testing two scale-selective bias correction (SSBC) methods have been carried out to identify an optimal spectral nudging scheme for historical dynamically downscaled simulations of South Asia, using the coordinated regional climate downscaling experiment (CORDEX) protocol and the regional spectral model (RSM). Two time periods were selected under the category of short-term extreme summer and long-term decadal analysis. The new SSBC version applied nudging to full wind components, with an increased relaxation time in the lower model layers, incorporating a vertical weighted damping coefficient. An evaluation of the extraordinary weather conditions experienced in South Asia in the summer of 2005 confirmed the advantages of the new SSBC when modeling monsoon precipitation. Furthermore, the new SSBC scheme was found to predict precipitation and wind patterns more accurately than the older version in decadal analysis, which applies nudging only to the rotational wind field, with a constant strength at all heights.

The Impact of Aerosols on the Summer Rainfall Frequency in China

2008 ◽  
Vol 47 (6) ◽  
pp. 1802-1813 ◽  
Author(s):  
Yong-Sang Choi ◽  
Chang-Hoi Ho ◽  
Jinwon Kim ◽  
Dao-Yi Gong ◽  
Rokjin J. Park
Keyword(s):  
Regional Climate ◽  
Cloud Amount ◽  
Summer Rainfall ◽  
Aerosol Concentration ◽  
Short Term ◽  
Cloud Optical Depth ◽  
Cloud Properties ◽  
Rainfall Frequency ◽  
The Impact

Abstract The authors investigate the short-term relationship between aerosol concentrations and summer rainfall frequency in China using the daily surface observations of particulate matters with a diameter of less than 10 μm (PM10) mass concentration, rainfall, and satellite-observed cloud properties. Results in this study reveal that on the time scale of a few days aerosol concentration is positively correlated with the frequency of moderate-rainfall (10–20 mm day−1) days but is negatively correlated with the frequency of light-rainfall (<5 mm day−1) days. Satellite observations of cloud properties show that higher aerosol concentrations are positively correlated with the increase in mixed cloud amount, cloud effective radius, cloud optical depth, and cloud-top heights; this corresponds to the decrease in low-level liquid clouds and the increase in midlevel ice–mixed clouds. Based on this analysis, the authors hypothesize that the increase in aerosol concentration results in the increase in summer rainfall frequency in China via enhanced ice nucleation in the midtroposphere. However, over the past few decades, observations show an increasing long-term trend in aerosol concentration but decreasing trends in summer rainfall frequency and relative humidity (RH) in China. Despite the short-term positive relationship between summer rainfall frequency and aerosol concentration found in this study, the long-term variations in summer rainfall frequency in China are mainly determined by other factors including RH variation possibly caused by global and regional climate changes. A continuous decrease in RH resulting in less summer rainfall frequency may further enhance aerosol concentrations in the future in conjunction with the increase in the anthropogenic emissions.

Factors affecting colony attendance by Ancient Murrelets (Synthliboramphus antiquus)

1990 ◽  
Vol 68 (3) ◽  
pp. 433-441 ◽  
Author(s):  
Ian L. Jones ◽  
Anthony J. Gaston ◽  
J. Bruce Falls
Keyword(s):  
Weather Conditions ◽  
Weather Variables ◽  
Short Term ◽  
Weather Effects ◽  
Factors Affecting ◽  
Cyclical Pattern ◽  
The Hours ◽  
Nesting Season ◽  
Colony Attendance

We studied factors influencing variation in nightly levels of activity (birds arriving and vocalizing) and numbers of birds staging offshore at a colony of Ancient Murrelets at Reef Island, British Columbia, during 1984, 1985, and 1986. Activity was restricted to the hours of darkness and extremely variable in magnitude from night to night. The rate of entry into burrows tended to decrease, and the amount of vocalization and numbers of birds at the staging area increased during the nesting season. We detected an underlying 4-day cyclical pattern of attendance. Nightly variability of activity at the colony was affected by moonlight and weather conditions. Since activity, particularly vocalization, was reduced on moonlit nights, we suggest that nocturnal colony attendance is a strategy to avoid diurnal predators in this species. The largest numbers of birds were present and vocalizing at the colony on calm moonless nights. Weather conditions explained a substantial proportion of the night to night variability in murrelet activity. Among weather variables, wind speed had the most consistent effect and was particularly important in 1985. Both short-term, i.e., of a particular night, and long-term, i.e., over the previous 3 days, conditions influenced activity. Our observations suggest that direct weather effects at the colony may be more important than weather effects related to foraging conditions. Interyear differences in activity may have resulted from the interaction of weather and general foraging conditions.

scholarly journals Differences between downscaling with spectral and grid nudging using WRF

2012 ◽  
Vol 12 (8) ◽  
pp. 3601-3610 ◽  
Author(s):  
P. Liu ◽  
A. P. Tsimpidi ◽  
Y. Hu ◽  
B. Stone ◽  
A. G. Russell ◽  
...  
Keyword(s):  
Large Scale ◽  
Climate Models ◽  
Dynamical Downscaling ◽  
Global Climate ◽  
Regional Climate ◽  
Wrf Model ◽  
Global Climate Models ◽  
Small Scale ◽  
Data Set ◽  
Spectral Nudging

Abstract. Dynamical downscaling has been extensively used to study regional climate forced by large-scale global climate models. During the downscaling process, however, the simulation of regional climate models (RCMs) tends to drift away from the driving fields. Developing a solution that addresses this issue, by retaining the large scale features (from the large-scale fields) and the small-scale features (from the RCMs) has led to the development of "nudging" techniques. Here, we examine the performance of two nudging techniques, grid and spectral nudging, in the downscaling of NCEP/NCAR data with the Weather Research and Forecasting (WRF) Model. The simulations are compared against the results with North America Regional Reanalysis (NARR) data set at different scales of interest using the concept of similarity. We show that with the appropriate choice of wave numbers, spectral nudging outperforms grid nudging in the capacity of balancing the performance of simulation at the large and small scales.

Prediction of Extreme Roll Motion on an FPSO Using Long Term Statistics

2002 ◽  
Author(s):  
Tone M. Vestbo̸stad ◽  
Sverre Haver ◽  
Odd Jan Andersen ◽  
Arne Albert
Keyword(s):  
Probability Distribution ◽  
Wind Waves ◽  
Weather Conditions ◽  
Full Scale ◽  
Roll Motion ◽  
Short Term ◽  
Sea State ◽  
Term Analysis

This paper presents a method for predicting extreme roll motion on an FPSO using long-term statistics. The method consists of a long-term simulation where a database of consecutive short-term sea states with combined weather conditions, including direction and magnitude of wind, wind waves and swell waves, is used. The vessel heading in given weather conditions is simulated. For each combined sea state, the short-term roll motion maxima are calculated to form a long-term probability distribution, and the extreme roll motion, e.g. the 100-year value, can be estimated from the distribution. For an example FPSO, the results from the long-term analysis have been compared with full-scale measurements, giving a validation of the method. This paper is a shortened version of [1].

scholarly journals Positive Correlations between Short-Term and Average Long-Term Fluctuations in Wind Power Output

Energies ◽  
2021 ◽  
Vol 14 (7) ◽  
pp. 1861
Author(s):  
Chiyori T. Urabe ◽  
Tetsuo Saitou ◽  
Kazuto Kataoka ◽  
Takashi Ikegami ◽  
Kazuhiko Ogimoto
Keyword(s):  
Power Systems ◽  
Wind Power ◽  
Power Output ◽  
Renewable Energy Sources ◽  
Electrical Power ◽  
Weather Conditions ◽  
Electricity Sector ◽  
Linear Functions ◽  
Short Term

Wind power has been increasingly deployed in the last decade to decarbonize the electricity sector. Wind power output changes intermittently depending on weather conditions. In electrical power systems with high shares of variable renewable energy sources, such as wind power, system operators aim to respond flexibly to fluctuations in output. Here, we investigated very short-term fluctuations, short-term fluctuations (STFs), and long-term fluctuations (LTFs) in wind power output by analyzing historical output data for two northern and one southern balancing areas in Japan. We found a relationship between STFs and the average LTFs. The percentiles of the STFs in each month are approximated by linear functions of the monthly average LTFs. Furthermore, the absolute value of the slope of this function decreases with wind power capacity in the balancing area. The LTFs reflect the trend in wind power output. The results indicate that the flexibility required for power systems can be estimated based on wind power predictions. This finding could facilitate the design of the balancing market in Japan.

scholarly journals Impact of Nudging Parameters on Dynamical Downscaling over CORDEX East Asia Phase II Domain: The Case of Summer 2003

2019 ◽  
Vol 58 (12) ◽  
pp. 2755-2771
Author(s):  
Linyun Yang ◽  
Shuyu Wang ◽  
Jianping Tang ◽  
Xiaorui Niu ◽  
Congbin Fu
Keyword(s):  
Relaxation Time ◽  
East Asia ◽  
Large Scale ◽  
Dynamical Downscaling ◽  
Regional Climate ◽  
Wrf Model ◽  
Precipitation Event ◽  
Weather Research And Forecasting ◽  
Spectral Nudging ◽  
Thermodynamic Variables

AbstractIn this paper, the sensitivity of the Weather Research and Forecasting (WRF) Model to the nudging parameters in simulating July–August (JJA) precipitation was assessed with 16 experiments over the Coordinated Regional Climate Downscaling Experiment East Asia II (CORDEX-EA-II) domain. The effects of various nudging parameters in spectral nudging (referred to as SN) and grid nudging (referred to as AN) experiments are examined, including wavenumbers, relaxation time, nudging levels, and nudging variables for SN and relaxation time and nudging variables for AN. Results showed that the applications of spectral nudging and grid nudging methods in WRF simulations can improve the model’s ability to reproduce the JJA extreme precipitation event and accompanying large-scale fields in 2003. The major findings include 1) spectral nudging is superior to grid nudging in simulating heavy rainfall and low-level circulation, 2) nudging both kinematic and thermodynamic variables is efficient to better simulate the JJA precipitation for both SN and AN simulations, 3) in SN simulations, the options of wavenumbers display stronger impact on JJA precipitation if nudging solely the kinematic variables instead of both kinematic and thermodynamic variables over wet subregions, and 4) the free developed large-scale processes associated with small nudging wavenumbers can diminish the improvement from nudging both kinematic and thermodynamic variables in simulating subseasonal variations of precipitation. Overall, the experiment that adopts spectral nudging of both kinematic and thermodynamic variables, 1-h relaxation time, and four or eight nudging wavenumbers captures the characteristics of summer climate more reasonably.

Long-term changes in numbers of geese stopping over and wintering in south-western Poland

2012 ◽  
Vol 7 (3) ◽  
pp. 495-506 ◽  
Author(s):  
Andrzej Wuczyński ◽  
Bartosz Smyk ◽  
Paweł Kołodziejczyk ◽  
Wiesław Lenkiewicz ◽  
Grzegorz Orłowski ◽  
...  
Keyword(s):  
Weather Conditions ◽  
Short Term ◽  
Regional Trends ◽  
Bean Goose ◽  
Greylag Goose ◽  
Sw Poland ◽  
Large Water ◽  
Anser Fabalis ◽  
And Shifts

AbstractSouth-western Poland belongs to the key staging areas for geese in Europe, supporting some 100000 birds in recent years. We compared goose counts conducted in the 1970s, 1990s and during 2009–2011 in this region, and linked the findings to the recent assessments of trends in the flyway-populations. Numbers increased several dozen times between the first two counts and have stabilized to the present. More than 14% of the flyway Tundra Bean Goose (Anser fabalis rossicus) stopped over in SW Poland on passage. Smaller numbers of White-fronted Goose (A. albifrons), Greylag Goose (A. anser), and four other rarer species, have all increased since the 1970s. The likely factors responsible for these changes are mild weather conditions, increased availability of large water bodies and shifts in winter ranges of particular species. Temporal mismatch between SW Poland and the total flyways in Bean and White-fronted Geese was recorded when we compared the long-term and the short-term population trends. Increasing reports of other species in SW Poland match the general tendencies in Europe. These data document that regional trends are not a simple reflection of those in flyways as a whole. To understand changes in goose populations a re-established international count network is desired.

Rainfall Characteristics from Convection-Permitting Downscaling over the Western Maritime Continent

2021 ◽  
Author(s):  
Venkatraman Prasanna ◽  
Sandeep Sahany ◽  
Aurel F. Moise ◽  
Xin Rong Chua ◽  
Gerald Lim ◽  
...  
Keyword(s):  
Climate Model ◽  
Dynamical Downscaling ◽  
Regional Climate ◽  
Sea Surface ◽  
Added Value ◽  
Maritime Continent ◽  
Variable Resolution ◽  
Rainfall Characteristics ◽  
Satellite Retrievals

<p>Long-term convection-permitting dynamical downscaling has been carried out over the western Maritime Continent, using the Singapore Variable Resolution Regional Climate Model (SINGV-RCM) at 8km and 2km spatial resolutions. The SINGV-RCM is forced with ERA-5 reanalyses data for a 36-year period (1979-2014) at 8km resolution over Southeast Asia (79E-160E;16S-24N) with regular update of the sea surface temperature at 6-hr interval; further, this 8km domain simulation is used for forcing a smaller domain over the western Maritime continent at a resolution of 2km (93E-110E;7.2S-9.9N) for a 20-year period (1995-2014). Rainfall characteristics including the diurnal cycle and extremes from the two simulations evaluated against satellite retrievals, and the added value from dynamical downscaling will be presented.</p>

scholarly journals Does Spectral Nudging Have an Effect on Dynamical Downscaling Applied in Small Regional Model Domains?

2017 ◽  
Vol 145 (10) ◽  
pp. 4303-4311 ◽  
Author(s):  
Benjamin Schaaf ◽  
Hans von Storch ◽  
Frauke Feser
Keyword(s):  
Large Scale ◽  
Climate Models ◽  
Dynamical Downscaling ◽  
Regional Climate ◽  
Regional Scale ◽  
Regional Climate Models ◽  
Small Scale ◽  
Spectral Nudging ◽  
Atmospheric State ◽  
Model Region

Spectral nudging is a method that was developed to constrain regional climate models so that they reproduce the development of the large-scale atmospheric state, while permitting the formation of regional-scale details as conditioned by the large scales. Besides keeping the large-scale development in the interior close to a given state, the method also suppresses the emergence of ensemble variability. The method is mostly applied to reconstructions of past weather developments in regions with an extension of typically 1000–8000 km. In this article, the authors examine if spectral nudging is having an effect on simulations with model regions of the size of about 700 km × 500 km at midlatitudes located mainly over flat terrain. First two pairs of simulations are compared, two runs each with and without spectral nudging, and it is found that the four simulations are very similar, without systematic or intermittent phases of divergence. Smooth fields, which are mainly determined by spatial patterns, such as air pressure, show hardly any differences, while small-scale and heterogeneous fields such as precipitation vary strongly, mostly on the gridpoint scale, irrespective if spectral nudging is employed or not. It is concluded that the application of spectral nudging has little effect on the simulation when the model region is relatively small.

scholarly journals Predicting global patterns of long-term climate change from short-term simulations using machine learning

2020 ◽  
Vol 3 (1) ◽  
Author(s):  
L. A. Mansfield ◽  
P. J. Nowack ◽  
M. Kasoar ◽  
R. G. Everitt ◽  
W. J. Collins ◽  
...  
Keyword(s):  
Climate Change ◽  
Machine Learning ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Mitigation Measures ◽  
Climate Modelling ◽  
Short Term ◽  
Climate Change Projections

AbstractUnderstanding and estimating regional climate change under different anthropogenic emission scenarios is pivotal for informing societal adaptation and mitigation measures. However, the high computational complexity of state-of-the-art climate models remains a central bottleneck in this endeavour. Here we introduce a machine learning approach, which utilises a unique dataset of existing climate model simulations to learn relationships between short-term and long-term temperature responses to different climate forcing scenarios. This approach not only has the potential to accelerate climate change projections by reducing the costs of scenario computations, but also helps uncover early indicators of modelled long-term climate responses, which is of relevance to climate change detection, predictability, and attribution. Our results highlight challenges and opportunities for data-driven climate modelling, especially concerning the incorporation of even larger model datasets in the future. We therefore encourage extensive data sharing among research institutes to build ever more powerful climate response emulators, and thus to enable faster climate change projections.

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