A Pragmatic Approach to Build a Reduced Regional Climate Projection Ensemble for Germany Using the EURO-CORDEX 8.5 Ensemble

2018 ◽  
Vol 57 (3) ◽  
pp. 477-491 ◽  
Author(s):  
C. Dalelane ◽  
B. Früh ◽  
C. Steger ◽  
A. Walter
Keyword(s):  
Regional Climate ◽  
Surface Air Temperature ◽  
Reduction Technique ◽  
Climate Projection ◽  
Specific Humidity ◽  
Shortwave Radiation ◽  
Near Surface ◽  
Tuning Parameters ◽  
Regional Climate Projection ◽  
Regional Downscaling

AbstractThe application of an ensemble reduction technique to the European branch of the World Climate Research Program Coordinated Regional Downscaling Experiment (EURO-CORDEX) ensemble at resolution “EUR-11” (~12.5 km) under the RCP8.5 scenario is presented. The technique is based on monthly mean changes between a reference and two future time periods, calculated for eight regions in Germany, of the parameters near-surface air temperature (tas), precipitation totals (pr), contribution of precipitation from very wet days to precipitation totals (R95pTOT), near-surface specific humidity (huss), and surface downwelling shortwave radiation (rsds). The sensitivity of the reduction procedure with respect to a number of tuning parameters is investigated. When the optimal combination of tuning parameters is applied, the technique allows the reduction from 15 to 7 ensemble members, while the reduced ensemble reproduces about 94% of the spread of the full ensemble. Keeping in mind that climate projection ensembles are expected to grow substantially in the near future, this ensemble reduction technique can be useful to limit the computational efforts necessary for further processing and applications such as impact modeling.

Future Extreme Climates Projection over Huang-Huai-Hai Region of China

2014 ◽  
Vol 955-959 ◽  
pp. 3887-3892 ◽  
Author(s):  
Huang He Gu ◽  
Zhong Bo Yu ◽  
Ji Gan Wang
Keyword(s):  
Climate Changes ◽  
Climate Model ◽  
Regional Climate ◽  
Surface Air Temperature ◽  
Daily Rainfall ◽  
Heavy Rain ◽  
Near Surface ◽  
Temperature And Precipitation ◽  
Huai River ◽  
The Future

This study projects the future extreme climate changes over Huang-Huai-Hai (3H) region in China using a regional climate model (RegCM4). The RegCM4 performs well in “current” climate (1970-1999) simulations by compared with the available surface station data, focusing on near-surface air temperature and precipitation. Future climate changes are evaluated based on experiments driven by European-Hamburg general climate model (ECHAM5) in A1B future scenario (2070-2099). The results show that the annual temperature increase about 3.4 °C-4.2 °C and the annual precipitation increase about 5-15% in most of 3H region at the end of 21st century. The model predicts a generally less frost days, longer growing season, more hot days, no obvious change in heat wave duration index, larger maximum five-day rainfall, more heavy rain days, and larger daily rainfall intensity. The results indicate a higher risk of floods in the future warmer climate. In addition, the consecutive dry days in Huai River Basin will increase, indicating more serve drought and floods conditions in this region.

scholarly journals Evaluation of Upper Indus Near-Surface Climate Representation by WRF in the High Asia Refined Analysis

2019 ◽  
Vol 20 (3) ◽  
pp. 467-487 ◽  
Author(s):  
David M. W. Pritchard ◽  
Nathan Forsythe ◽  
Hayley J. Fowler ◽  
Greg M. O’Donnell ◽  
Xiao-Feng Li
Keyword(s):  
Regional Climate ◽  
Critical Role ◽  
Critical Evaluation ◽  
Longwave Radiation ◽  
Indus Basin ◽  
Shortwave Radiation ◽  
Cold Bias ◽  
Near Surface ◽  
High Asia ◽  
High Bias

Abstract Data paucity is a severe barrier to the characterization of Himalayan near-surface climates. Regional climate modeling can help to fill this gap, but the resulting data products need critical evaluation before use. This study aims to extend the appraisal of one such dataset, the High Asia Refined Analysis (HAR). Focusing on the upper Indus basin (UIB), the climatologies of variables needed for process-based hydrological and cryospheric modeling are evaluated, leading to three main conclusions. First, precipitation in the 10-km HAR product shows reasonable correspondence with most in situ measurements. It is also generally consistent with observed runoff, while additionally reproducing the UIB’s strong vertical precipitation gradients. Second, the HAR shows seasonally varying bias patterns. A cold bias in temperature peaks in spring but reduces in summer, at which time the high bias in relative humidity diminishes. These patterns are concurrent with summer overestimation (underestimation) of incoming shortwave (longwave) radiation. Finally, these seasonally varying biases are partly related to deficiencies in cloud, snow, and albedo representations. In particular, insufficient cloud cover in summer leads to the overestimation of incoming shortwave radiation. This contributes to the reduced cold bias in summer by enhancing surface warming. A persistent high bias in albedo also plays a critical role, particularly by suppressing surface heating in spring. Improving representations of cloud, snow cover, and albedo, and thus their coupling with seasonal climate transitions, would therefore help build upon the considerable potential shown by the HAR to fill a vital data gap in this immensely important basin.

scholarly journals Influence of Precipitation Assimilation on a Regional Climate Model’s Surface Water and Energy Budgets

2007 ◽  
Vol 8 (4) ◽  
pp. 642-664 ◽  
Author(s):  
Ana M. B. Nunes ◽  
John O. Roads
Keyword(s):  
Surface Water ◽  
Energy Budget ◽  
Prediction Models ◽  
Regional Climate ◽  
Longwave Radiation ◽  
Specific Humidity ◽  
Climate Simulation ◽  
Energy Budgets ◽  
Near Surface ◽  
Regional Reanalysis

Abstract Initialization of the moisture profiles has been used to overcome the imbalance between analysis schemes and prediction models that generates the so-called spinup problem seen in the hydrological fields. Here precipitation assimilation through moisture adjustment has been proposed as a technique to reduce this problem in regional climate simulations by adjusting the specific humidity according to 3-hourly North American Regional Reanalysis rain rates during two simulated years: 1988 and 1993. A control regional simulation provided the initial condition fields for both simulations. The precipitation assimilation simulation was then compared to the control regional climate simulation, reanalyses, and observations to determine whether assimilation of precipitation had a positive influence on modeled surface water and energy budget terms. In general, rainfall assimilation improved the regional model surface water and energy budget terms over the conterminous United States. Precipitation and runoff correlated better than the control and the global reanalysis fields to the regional reanalysis and available observations. Upward shortwave and downward short- and longwave radiation fluxes had regional seasonal cycles closer to the observed values than the control, and the near-surface temperature anomalies were also improved.

Modeling the Effects of Lakes in the Tibetan Plateau on Diurnal Variations of Regional Climate and Their Seasonality

2020 ◽  
Vol 21 (11) ◽  
pp. 2523-2536
Author(s):  
Lingjing Zhu ◽  
Jiming Jin ◽  
Yimin Liu
Keyword(s):  
Tibetan Plateau ◽  
Regional Climate ◽  
Wrf Model ◽  
Surface Air Temperature ◽  
Diurnal Variations ◽  
The Tibetan Plateau ◽  
Near Surface ◽  
Local Climate ◽  
Lake Model ◽  
Physically Based

AbstractIn this study, we investigated the effects of lakes in the Tibetan Plateau (TP) on diurnal variations of local climate and their seasonal changes by using the Weather Research and Forecasting (WRF) Model coupled with a one-dimensional physically based lake model. We conducted WRF simulations for the TP over 2000–10, and the model showed excellent performance in simulating near-surface air temperature, precipitation, lake surface temperature, and lake-region precipitation when compared to observations. We carried out additional WRF simulations where all the TP lakes were replaced with the nearest land-use types. The differences between these two sets of simulations were analyzed to quantify the effects of the TP lakes on the local climate. Our results indicate that the strongest lake-induced cooling occurred during the spring daytime, while the most significant warming occurred during the fall nighttime. The cooling and warming effects of the lakes further inhibited precipitation during summer afternoons and evenings and motivated it during fall early mornings, respectively. This study lays a solid foundation for further exploration of the role of TP lakes in climate systems at different time scales.

scholarly journals Regional climate modeling on European scales: a joint standard evaluation of the EURO-CORDEX RCM ensemble

2014 ◽  
Vol 7 (1) ◽  
pp. 217-293 ◽  
Author(s):  
S. Kotlarski ◽  
K. Keuler ◽  
O. B. Christensen ◽  
A. Colette ◽  
M. Déqué ◽  
...  
Keyword(s):  
Performance Metrics ◽  
Climate Model ◽  
Regional Climate ◽  
Model Performance ◽  
Surface Air Temperature ◽  
Quality Standard ◽  
European Continent ◽  
Near Surface ◽  
Mean Values ◽  
European Climate

Abstract. EURO-CORDEX is an international climate downscaling initiative that aims to provide high-resolution climate scenarios for Europe. Here an evaluation of the ERA-Interim-driven EURO-CORDEX regional climate model (RCM) ensemble is presented. The study documents the performance of the individual models in representing the basic spatio-temporal patterns of the European climate for the period 1989–2008. Model evaluation focuses on near-surface air temperature and precipitation, and uses the E-OBS dataset as observational reference. The ensemble consists of 17 simulations carried out by seven different models at grid resolutions of 12 km (nine experiments) and 50 km (eight experiments). Several performance metrics computed from monthly and seasonal mean values are used to assess model performance over eight sub-domains of the European continent. Results are compared to those for the ERA40-driven ENSEMBLES simulations. The analysis confirms the ability of RCMs to capture the basic features of the European climate, including its variability in space and time. But it also identifies non-negligible deficiencies of the simulations for selected metrics, regions and seasons. Seasonally and regionally averaged temperature biases are mostly smaller than 1.5 °C, while precipitation biases are typically located in the ±40% range. Some bias characteristics, such as a predominant cold and wet bias in most seasons and over most parts of Europe and a warm and dry summer bias over southern and south-eastern Europe reflect common model biases. For seasonal mean quantities averaged over large European sub-domains, no clear benefit of an increased spatial resolution (12 km vs. 50 km) can be identified. The bias ranges of the EURO-CORDEX ensemble mostly correspond to those of the ENSEMBLES simulations, but some improvements in model performance can be identified (e.g., a less pronounced southern European warm summer bias). The temperature bias spread across different configurations of one individual model can be of a similar magnitude as the spread across different models, demonstrating a strong influence of the specific choices in physical parameterizations and experimental setup on model performance. Based on a number of simply reproducible metrics, the present study quantifies the currently achievable accuracy of RCMs used for regional climate simulations over Europe and provides a quality standard for future model developments.

Evaluation of MM5 and HadGEM3-RA hindcast in the CORDEX East Asia Phase Ⅱ: near-surface air temperature

2020 ◽  
Author(s):  
Seok-Woo Shin ◽  
Dong-Hyun Cha ◽  
Taehyung Kim ◽  
Gayoung Kim ◽  
Changyoung Park ◽  
...  
Keyword(s):  
East Asia ◽  
Air Temperature ◽  
Climate Models ◽  
Extreme Values ◽  
Regional Climate ◽  
Surface Air Temperature ◽  
Regional Climate Models ◽  
Near Surface ◽  
The Mean ◽  
Cordex East Asia

<p>Extreme temperature can have a devastating impact on the ecological environment (i.e., human health and crops) and the socioeconomic system. To adapt to and cope with the rapidly changing climate, it is essential to understand the present climate and to estimate the future change in terms of temperature. In this study, we evaluate the characteristics of near-surface air temperature (SAT) simulated by two regional climate models (i.e., MM5 and HadGEM3-RA) over East Asia, focusing on the mean and extreme values. To analyze extreme climate, we used the indices for daily maximum (Tmax) and minimum (Tmin) temperatures among the developed Expert Team on Climate Change Detection and Indices (ETCCDI) indices. In the results of the CORDEX-East Asia phase Ⅰ, the mean and extreme values of SAT for DJF (JJA) tend to be colder (warmer) than observation data over the East Asian region. In those of CORDEX-East Asia phase Ⅱ, the mean and extreme values of SAT for DJF and JJA have warmer than those of the CORDEX-East Asia phase Ⅰ except for those of HadGEM3-RA for DJF. Furthermore, the Extreme Temperature Range (ETR, maximum value of Tmax - minimum value of Tmin) of CORDEX-East Asia phase Ⅰ data, which are significantly different from those of observation data, are reduced in that of CORDEX-East Asia phase Ⅱ. Consequently, the high-resolution regional climate models play a role in the improvement of the cold bias having the relatively low-resolution ones. To understand the reasons for the improved and weak points of regional climate models, we investigated the atmospheric field (i.e., flow, air mass, precipitation, and radiation) influencing near-surface air temperature. Model performances for SAT over East Asia were influenced by the expansion of the western North Pacific subtropical high and the location of convective precipitation in JJA and by the contraction of the Siberian high, the spatial distribution of snowfall and associated upwelling longwave radiation in DJF.</p>

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