Selecting Representative Days for More Efficient Dynamical Climate Downscaling: Application to Wind Energy

2013 ◽  
Vol 52 (1) ◽  
pp. 47-63 ◽  
Author(s):  
Daran L. Rife ◽  
Emilie Vanvyve ◽  
James O. Pinto ◽  
Andrew J. Monaghan ◽  
Christopher A. Davis ◽  
...  
Keyword(s):  
Wind Energy ◽  
Large Scale ◽  
Sampling Method ◽  
Climate Model ◽  
Regional Climate ◽  
Current Approach ◽  
New Method ◽  
Computationally Efficient ◽  
Climate Downscaling

AbstractThis paper describes a new computationally efficient and statistically robust sampling method for generating dynamically downscaled climatologies. It is based on a Monte Carlo method coupled with stratified sampling. A small yet representative set of “case days” is selected with guidance from a large-scale reanalysis. When downscaled, the sample closely approximates the long-term meteorological record at a location, in terms of the probability density function. The method is demonstrated for the creation of wind maps to help determine the suitability of potential sites for wind energy farms. Turbine hub-height measurements at five U.S. and European tall tower sites are used as a proxy for regional climate model (RCM) downscaled winds to validate the technique. The tower-measured winds provide an independent test of the technique, since RCM-based downscaled winds exhibit an inherent dependence upon the large-scale reanalysis fields from which the case days are sampled; these same reanalysis fields would provide the boundary conditions to the RCM. The new sampling method is compared with the current approach widely used within the wind energy industry for creating wind resource maps, which is to randomly select 365 case days for downscaling, with each day in the calendar year being represented. The new method provides a more accurate and repeatable estimate of the long-term record of winds at each tower location. Additionally, the new method can closely approximate the accuracy of the current (365 day) industry approach using only a 180-day sample, which may render climate downscaling more tractable for those with limited computing resources.

scholarly journals ICON in Climate Limited-area Mode (ICON release version 2.6.1): a new regional climate model

2021 ◽  
Vol 14 (2) ◽  
pp. 985-1005
Author(s):  
Trang Van Pham ◽  
Christian Steger ◽  
Burkhardt Rockel ◽  
Klaus Keuler ◽  
Ingo Kirchner ◽  
...  
Keyword(s):  
Large Scale ◽  
Model Comparison ◽  
Climate Model ◽  
Early Stage ◽  
Regional Climate ◽  
Climate Simulation ◽  
Small Scale ◽  
Limited Area ◽  
Stage Of Development

Abstract. For the first time, the Limited-Area Mode of the new ICON (Icosahedral Nonhydrostatic) weather and climate model has been used for a continuous long-term regional climate simulation over Europe. Built upon the Limited-Area Mode of ICON (ICON-LAM), ICON-CLM (ICON in Climate Limited-area Mode, hereafter ICON-CLM, available in ICON release version 2.6.1) is an adaptation for climate applications. A first version of ICON-CLM is now available and has already been integrated into a starter package (ICON-CLM_SP_beta1). The starter package provides users with a technical infrastructure that facilitates long-term simulations as well as model evaluation and test routines. ICON-CLM and ICON-CLM_SP were successfully installed and tested on two different computing systems. Tests with different domain decompositions showed bit-identical results, and no systematic outstanding differences were found in the results with different model time steps. ICON-CLM was also able to reproduce the large-scale atmospheric information from the global driving model. Comparison was done between ICON-CLM and the COnsortium for Small-scale MOdeling (COSMO)-CLM (the recommended model configuration by the CLM-Community) performance. For that, an evaluation run of ICON-CLM with ERA-Interim boundary conditions was carried out with the setup similar to the COSMO-CLM recommended optimal setup. ICON-CLM results showed biases in the same range as those of COSMO-CLM for all evaluated surface variables. While this COSMO-CLM simulation was carried out with the latest model version which has been developed and was carefully tuned for climate simulations on the European domain, ICON-CLM was not tuned yet. Nevertheless, ICON-CLM showed a better performance for air temperature and its daily extremes, and slightly better performance for total cloud cover. For precipitation and mean sea level pressure, COSMO-CLM was closer to observations than ICON-CLM. However, as ICON-CLM is still in the early stage of development, there is still much room for improvement.

Hydrological evaluation of high-resolution precipitation estimates from the WRF model in the Third Pole river basins

2021 ◽  
Author(s):  
He Sun ◽  
Fengge Su ◽  
Zhihua He ◽  
Tinghai Ou ◽  
Deliang Chen ◽  
...  
Keyword(s):  
Land Surface ◽  
Large Scale ◽  
Hydrological Modeling ◽  
Climate Model ◽  
Regional Climate ◽  
Wrf Model ◽  
Infiltration Capacity ◽  
Flood Prediction ◽  
Daily Streamflow ◽  
Precipitation Estimates

AbstractIn this study, two sets of precipitation estimates based on the regional Weather Research and Forecasting model (WRF) –the high Asia refined analysis (HAR) and outputs with a 9 km resolution from WRF (WRF-9km) are evaluated at both basin and point scales, and their potential hydrological utilities are investigated by driving the Variable Infiltration Capacity (VIC) large-scale land surface hydrological model in seven Third Pole (TP) basins. The regional climate model (RCM) tends to overestimate the gauge-based estimates by 20–95% in annual means among the selected basins. Relative to the gauge observations, the RCM precipitation estimates can accurately detect daily precipitation events of varying intensities (with absolute bias < 3 mm). The WRF-9km exhibits a high potential for hydrological application in the monsoon-dominated basins in the southeastern TP (with NSE of 0.7–0.9 and bias of -11% to 3%), while the HAR performs well in the upper Indus (UI) and upper Brahmaputra (UB) basins (with NSE of 0.6 and bias of -15% to -9%). Both the RCM precipitation estimates can accurately capture the magnitudes of low and moderate daily streamflow, but show limited capabilities in flood prediction in most of the TP basins. This study provides a comprehensive evaluation of the strength and limitation of RCMs precipitation in hydrological modeling in the TP with complex terrains and sparse gauge observations.

scholarly journals Comparison and assessment of large-scale surface temperature in climate model simulations

2019 ◽  
Vol 5 (1) ◽  
pp. 67-85
Author(s):  
Raquel Barata ◽  
Raquel Prado ◽  
Bruno Sansó
Keyword(s):  
Surface Temperature ◽  
Seasonal Changes ◽  
Large Scale ◽  
Climate Model ◽  
Internal Variability ◽  
Temperature Variability ◽  
Data Driven ◽  
Model Simulations ◽  
Climate Model Simulations

Abstract. We present a data-driven approach to assess and compare the behavior of large-scale spatial averages of surface temperature in climate model simulations and in observational products. We rely on univariate and multivariate dynamic linear model (DLM) techniques to estimate both long-term and seasonal changes in temperature. The residuals from the DLM analyses capture the internal variability of the climate system and exhibit complex temporal autocorrelation structure. To characterize this internal variability, we explore the structure of these residuals using univariate and multivariate autoregressive (AR) models. As a proof of concept that can easily be extended to other climate models, we apply our approach to one particular climate model (MIROC5). Our results illustrate model versus data differences in both long-term and seasonal changes in temperature. Despite differences in the underlying factors contributing to variability, the different types of simulation yield very similar spectral estimates of internal temperature variability. In general, we find that there is no evidence that the MIROC5 model systematically underestimates the amplitude of observed surface temperature variability on multi-decadal timescales – a finding that has considerable relevance regarding efforts to identify anthropogenic “fingerprints” in observational surface temperature data. Our methodology and results present a novel approach to obtaining data-driven estimates of climate variability for purposes of model evaluation.

scholarly journals Regional Climate Model Emulator based on Deep Learning: Concept and First Evaluation of a Novel Hybrid Downscaling Approach

2021 ◽  
Author(s):  
Antoine Doury ◽  
Samuel Somot ◽  
Sébastien Gadat ◽  
Aurélien Ribes ◽  
Lola Corre
Keyword(s):  
Climate Change ◽  
Network Architecture ◽  
Large Scale ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Future Climate ◽  
Near Surface ◽  
The Way

Abstract Providing reliable information on climate change at local scale remains a challenge of first importance for impact studies and policymakers. Here, we propose a novel hybrid downscaling method combining the strengths of both empirical statistical downscaling methods and Regional Climate Models (RCMs). The aim of this tool is to enlarge the size of high-resolution RCM simulation ensembles at low cost.We build a statistical RCM-emulator by estimating the downscaling function included in the RCM. This framework allows us to learn the relationship between large-scale predictors and a local surface variable of interest over the RCM domain in present and future climate. Furthermore, the emulator relies on a neural network architecture, which grants computational efficiency. The RCM-emulator developed in this study is trained to produce daily maps of the near-surface temperature at the RCM resolution (12km). The emulator demonstrates an excellent ability to reproduce the complex spatial structure and daily variability simulated by the RCM and in particular the way the RCM refines locally the low-resolution climate patterns. Training in future climate appears to be a key feature of our emulator. Moreover, there is a huge computational benefit in running the emulator rather than the RCM, since training the emulator takes about 2 hours on GPU, and the prediction is nearly instantaneous. However, further work is needed to improve the way the RCM-emulator reproduces some of the temperature extremes, the intensity of climate change, and to extend the proposed methodology to different regions, GCMs, RCMs, and variables of interest.

scholarly journals Improved Physical Processes in a Regional Climate Model and Their Impact on the Simulated Summer Monsoon Circulations over East Asia

2008 ◽  
Vol 21 (5) ◽  
pp. 963-979 ◽  
Author(s):  
Yoo-Bin Yhang ◽  
Song-You Hong
Keyword(s):  
Boundary Layer ◽  
Summer Monsoon ◽  
Large Scale ◽  
Climate Model ◽  
Asian Summer Monsoon ◽  
Regional Climate ◽  
Analysis Data ◽  
Cumulus Parameterization ◽  
Intraseasonal Variation ◽  
Thermal Roughness Length

Abstract This paper documents the sensitivity of the modeled evolution of the East Asian summer monsoon (EASM) to physical parameterization using the National Centers for Environmental Prediction (NCEP) Regional Spectral Model (RSM). To this end, perfect boundary condition experiments driven by analysis data are designed for August 2003 to investigate the individual role of the surface processes, boundary layer, and convection parameterization on the simulated monsoon. Also, 10-yr June–August (JJA) simulations from 1996 to 2005 are performed to evaluate the overall impacts of these revisions on the simulated EASM climatology. The one-month simulation for August 2003 reveals that the experiment with a realistic distribution of land use conditions and vegetation and smaller thermal roughness length simulates higher temperature and geopotential height. On the other hand, in the experiment with an improved boundary layer scheme, the rainfall amount is slightly decreased due to reduced vertical mixing. The simulation with revised subgrid-scale processes in the cumulus parameterization scheme reproduces a rainband over the subtropics, which is weakly simulated by the default package. The overall large-scale distribution from the experiment, which includes all three revised physics processes, shows the same direction as that of the revised convection run in the middle and upper troposphere, but is improved further when other newly enhanced processes are combined. These improvements are also achieved in a 10-yr summer simulation. It is distinct that the revised physics package improves the large-scale patterns by strengthening the intensity of the North Pacific high and reducing the intensity of the lower-level jet, which are critical components in the EASM. The general patterns of the interannual and intraseasonal variation of precipitation are also improved, in particular, over land.

scholarly journals Space-based geoengineering: Challenges and requirements

2009 ◽  
Vol 224 (3) ◽  
pp. 571-580 ◽  
Author(s):  
C R McInnes
Keyword(s):  
Climate Change ◽  
Carbon Dioxide ◽  
Large Scale ◽  
Climate Model ◽  
Carbon Dioxide Concentration ◽  
Complex Solution ◽  
Lagrange Point ◽  
Simple Climate Model ◽  
Earth’S Climate

The prospect of engineering the Earth's climate (geoengineering) raises a multitude of issues associated with climatology, engineering on macroscopic scales, and indeed the ethics of such ventures. Depending on personal views, such large-scale engineering is either an obvious necessity for the deep future, or yet another example of human conceit. In this article a simple climate model will be used to estimate requirements for engineering the Earth's climate, principally using space-based geoengineering. Active cooling of the climate to mitigate anthropogenic climate change due to a doubling of the carbon dioxide concentration in the Earth's atmosphere is considered. This representative scenario will allow the scale of the engineering challenge to be determined. It will be argued that simple occulting discs at the interior Lagrange point may represent a less complex solution than concepts for highly engineered refracting discs proposed recently. While engineering on macroscopic scales can appear formidable, emerging capabilities may allow such ventures to be seriously considered in the long term. This article is not an exhaustive review of geoengineering, but aims to provide a foretaste of the future opportunities, challenges, and requirements for space-based geoengineering ventures.

Response of Seasonal Simulations of a Regional Climate Model to High-Frequency Variability of Soil Moisture during the Summers of 1988 and 1993

2007 ◽  
Vol 8 (4) ◽  
pp. 738-757 ◽  
Author(s):  
Song Yang ◽  
S-H. Yoo ◽  
R. Yang ◽  
K. E. Mitchell ◽  
H. van den Dool ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Water Vapor ◽  
Diurnal Cycle ◽  
High Frequency ◽  
Large Scale ◽  
Climate Model ◽  
Regional Climate ◽  
Water Vapor Transport ◽  
Diurnal Variability ◽  
High Frequency Variability

Abstract This study employs the NCEP Eta Regional Climate Model to investigate the response of the model’s seasonal simulations of summer precipitation to high-frequency variability of soil moisture. Specifically, it focuses on the response of model precipitation and temperature over the U.S. Midwest and Southeast to imposed changes in the diurnal and synoptic variability of soil moisture in 1988 and 1993. High-frequency variability of soil moisture increases (decreases) precipitation in the 1988 drought (1993 flood) year in the central and southern-tier states, except along the Gulf Coast, but causes smaller changes in precipitation along the northern-tier states. The diurnal variability and synoptic variability of soil moisture produce similar patterns of precipitation change, indicating the importance of the diurnal cycle of land surface process. The increase (decrease) in precipitation is generally accompanied by a decrease (increase) in surface and lower-tropospheric temperatures, and the changes in precipitation and temperature are attributed to both the local effect of evaporation feedback and the remote influence of large-scale water vapor transport. The precipitation increase and temperature decrease in 1988 are accompanied by an increase in local evaporation and, more importantly, by an increase in the large-scale water vapor convergence into the Midwest and Southeast. Analogous but opposite-sign behavior occurs in 1993 (compared to 1988) in changes in precipitation, temperature, soil moisture, evaporation, and large-scale water vapor transport. Results also indicate that, in regions where the model simulates the diurnal cycle of soil moisture reasonably well, including this diurnal cycle in the simulations improves model performance. However, no notable improvement in model precipitation can be found in regions where the model fails to realistically simulate the diurnal variability of soil moisture.

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