Precipitation diurnal cycle and associated valley wind circulations over an Andean glacier region (Antizana, Ecuador)

2020 ◽  
Author(s):  
Clementine Junquas ◽  
Maria Belen Heredia ◽  
Thomas Condom ◽  
Jhan Carlo Espinoza ◽  
Jean Carlos Ruiz ◽  
...  
Keyword(s):  
Diurnal Cycle ◽  
Climate Model ◽  
Dynamical Downscaling ◽  
Regional Climate ◽  
Temporal Distribution ◽  
Tropical Andes ◽  
Time Step ◽  
Valley Wind ◽  
Spatio Temporal

<p>In the tropical Andes, the evolution of the mass balance of glaciers is strongly controlled by the variability of precipitation and humidity transport. It is therefore crucial to better understand the main patterns of precipitation in terms of spatio-temporal distribution at the local scale. In this study, we focus on the region of the Antizana ice cap, located in the Equatorial Andes about 50 km east of the city of Quito (Ecuador). In addition, the Antizana region is located in a very complex zonal climate gradient, with the Pacific Ocean to the west and the humid Amazonian plains to the east, including an area of ​​maximum precipitation on the Amazonian slope, also called "Precipitation hotspot".</p><p>In this study, we perform dynamical downscaling using a Regional Climate Model (RCM) to improve the understanding of the atmospheric processes controlling the spatio-temporal variability of precipitation. The WRF (Weather Research and Forecasting) model is used to perform a set of ten experiments with four one-way nesting domains (27km, 9km, 3km, 1km), with the highest resolution domain centered on the Antizana mountain, for the year 2005. For the model validation, we use the 3B42 satellite product of the Tropical Rainfall Measuring Mission (TRMM) at 3-hourly time step, the ORE Antizana meteorological station (SNO GLACIOCLIM, LMI GREATICE) at hourly time step, and 2 meteorological in-situ stations, installed by the Instituto Nacional de Metereología e Hidrologia (INAMHI) in the Antizana region, with a complete chronology of daily precipitation (mm/day) during the 2005 year.</p><p>We test different forcings of DEM (Digital Elevation Model), microphysic schemes, Cumulus schemes and convection-permitting simulation, and radiation/slope dependent options. The analysis focuses in particular on how the different representation of thermally driven valley wind circulation can affect the diurnal cycle of precipitation at the ORE Antizana in-situ station. The influence of the diurnal cycle of the regional humidity flux on the mountain precipitation is also analyzed.</p>

scholarly journals A Comparison between One-Step and Two-Step Nesting Strategy in the Dynamical Downscaling of Regional Climate Model COSMO-CLM at 2.2 km Driven by ERA5 Reanalysis

Atmosphere ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 260
Author(s):  
Mario Raffa ◽  
Alfredo Reder ◽  
Marianna Adinolfi ◽  
Paola Mercogliano
Keyword(s):  
Regional Climate Model ◽  
Climate Model ◽  
Dynamical Downscaling ◽  
Spatial Scales ◽  
Regional Climate ◽  
Weather Forecast ◽  
Medium Range Weather Forecast ◽  
Spatial And Temporal Scales ◽  
Starting Point ◽  
One Step

Recently, the European Centre for Medium Range Weather Forecast (ECMWF) has released a new generation of reanalysis, acknowledged as ERA5, representing at the present the most plausible picture for the current climate. Although ERA5 enhancements, in some cases, its coarse spatial resolution (~31 km) could still discourage a direct use of precipitation fields. Such a gap could be faced dynamically downscaling ERA5 at convection permitting scale (resolution < 4 km). On this regard, the selection of the most appropriate nesting strategy (direct one-step against nested two-step) represents a pivotal issue for saving time and computational resources. Two questions may be raised within this context: (i) may the dynamical downscaling of ERA5 accurately represents past precipitation patterns? and (ii) at what extent may the direct nesting strategy performances be adequately for this scope? This work addresses these questions evaluating two ERA5-driven experiments at ~2.2 km grid spacing over part of the central Europe, run using the regional climate model COSMO-CLM with different nesting strategies, for the period 2007–2011. Precipitation data are analysed at different temporal and spatial scales with respect to gridded observational datasets (i.e., E-OBS and RADKLIM-RW) and existing reanalysis products (i.e., ERA5-Land and UERRA). The present work demonstrates that the one-step experiment tendentially outperforms the two-step one when there is no spectral nudging, providing results at different spatial and temporal scales in line with the other existing reanalysis products. However, the results can be highly model and event dependent as some different aspects might need to be considered (i.e., the nesting strategies) during the configuration phase of the climate experiments. For this reason, a clear and consolidated recommendation on this topic cannot be stated. Such a level of confidence could be achieved in future works by increasing the number of cities and events analysed. Nevertheless, these promising results represent a starting point for the optimal experimental configuration assessment, in the frame of future climate studies.

scholarly journals Simulating river discharge in a snowy region of Japan using output from a regional climate model

2013 ◽  
Vol 35 ◽  
pp. 55-60 ◽  
Author(s):  
X. Ma ◽  
H. Kawase ◽  
S. Adachi ◽  
M. Fujita ◽  
H. G. Takahashi ◽  
...  
Keyword(s):  
Regional Climate Model ◽  
River Discharge ◽  
Climate Model ◽  
Dynamical Downscaling ◽  
Regional Climate ◽  
Eastern Coast ◽  
The Sea Of Japan ◽  
Efficiency Coefficient ◽  
Simulation Accuracy ◽  
Budget Analysis

Abstract. Snowfall amounts have fallen sharply along the eastern coast of the Sea of Japan since the mid-1980s. Toyama Prefecture, located approximately in the center of the Japan Sea region, includes high mountains of the northern Japanese Alps on three of its sides. The scarcity of meteorological observation points in mountainous areas limits the accuracy of hydrological analysis. With the development of computing technology, a dynamical downscaling method is widely applied into hydrological analysis. In this study, we numerically modeled river discharge using runoff data derived by a regional climate model (4.5-km spatial resolution) as input data to river networks (30-arcseconds resolution) for the Toyama Prefecture. The five main rivers in Toyama (the Oyabe, Sho, Jinzu, Joganji, and Kurobe rivers) were selected in this study. The river basins range in area from 368 to 2720 km2. A numerical experiment using climate comparable to that at present was conducted for the 1980s and 1990s. The results showed that seasonal river discharge could be represented and that discharge was generally overestimated compared with measurements, except for Oyabe River discharge, which was always underestimated. The average correlation coefficient for 10-year average monthly mean discharge was 0.8, with correlation coefficients ranging from 0.56 to 0.88 for all five rivers, whereas the Nash-Sutcliffe efficiency coefficient indicated that the simulation accuracy was insufficient. From the water budget analysis, it was possible to speculate that the lack of accuracy of river discharge may be caused by insufficient accuracy of precipitation simulation.

Decomposition of Future Moisture Flux Changes over the Tibetan Plateau Projected by Global and Regional Climate Models

2019 ◽  
Vol 32 (20) ◽  
pp. 7037-7053
Author(s):  
Hongwen Zhang ◽  
Yanhong Gao ◽  
Jianwei Xu ◽  
Yu Xu ◽  
Yingsha Jiang
Keyword(s):  
Tibetan Plateau ◽  
Climate Model ◽  
Dynamical Downscaling ◽  
Regional Climate ◽  
Moisture Flux ◽  
Historical Period ◽  
The Tibetan Plateau ◽  
Dynamic Component ◽  
Coarse Resolution ◽  
The Future

Abstract To meet the requirement of high-resolution datasets for many applications, a dynamical downscaling approach using a regional climate model (the WRF Model) driven by a global climate model (CCSM4) has been adopted. This study focuses on projections of future moisture flux changes over the Tibetan Plateau (TP). First, the downscaling results for the historical period (1980–2005) are evaluated for precipitation P, evaporation E, and precipitation minus evaporation P − E against Global Land Data Assimilation System (GLDAS) data. The mechanism of P − E changes is analyzed by decomposition into dynamic, thermodynamic, and transient eddy components. Whether the historical period changes and mechanisms continue into the future (2010–2100) is investigated using the WRF and CCSM model projections under the RCP4.5 and RCP8.5 scenarios. Compared with coarse-resolution forcing, downscaling was found to better reproduce the historical spatial patterns and seasonal mean of annual average P, E, and P − E over the TP. WRF projects a diverse spatial variation of P − E changes, with an increase in the northern TP and a decrease in the southern TP, compared with the uniform increase in CCSM. The dynamic component dominates P − E changes for the historical period in both the CCSM and WRF projections. In the future, however, the thermodynamic component in CCSM dominates P − E changes under RCP4.5 and RCP8.5 from the near-term (2010–39) to the long-term (2070–99) future. Unlike the CCSM projections, the WRF projections reproduce the mechanism seen in the historical period—that is, the dynamic component dominates P − E changes. Furthermore, future P − E changes in the dynamical downscaling are less sensitive to warming than its coarse-resolution forcing.

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.

Configuration and Evaluation of the WRF Model for the Study of Hawaiian Regional Climate

2012 ◽  
Vol 140 (10) ◽  
pp. 3259-3277 ◽  
Author(s):  
Chunxi Zhang ◽  
Yuqing Wang ◽  
Axel Lauer ◽  
Kevin Hamilton
Keyword(s):  
Land Surface ◽  
Climate Model ◽  
Dynamical Downscaling ◽  
Model Simulation ◽  
Regional Climate ◽  
Hawaiian Islands ◽  
Wrf Model ◽  
Trade Wind ◽  
Preliminary Evaluation ◽  
The Mean

Abstract The Weather Research and Forecasting (WRF) model V3.3 has been configured for the Hawaiian Islands as a regional climate model for the region (HRCM). This paper documents the model configuration and presents a preliminary evaluation based on a continuous 1-yr simulation forced by observed boundary conditions with 3-km horizontal grid spacing in the inner nested domain. The simulated vertical structure of the temperature and humidity are compared with twice-daily radiosonde observations at two stations. Generally the trade wind inversion (TWI) height and occurrence days are well represented. The simulation over the islands is compared with observations from nine surface climatological stations and a dense network of precipitation stations. The model simulation has generally small biases in the simulated surface temperature, relative humidity, and wind speed. The model realistically simulated the magnitude and geographical distribution of the mean rainfall over the Hawaiian Islands. In addition, the model simulation reproduced reasonably well the individual heavy rainfall events as seen from the time series of pentad mean rainfall averaged over island scales. Also the model reproduced the geographical variation of the mean diurnal rainfall cycle even though the observed diurnal cycle displays quite different features over different islands. Comparison with results obtained using the land surface dataset from the official release of the WRF model confirmed that the newly implemented land surface dataset generally improved the simulation of surface variables. These results demonstrate that the WRF can be a useful tool for dynamical downscaling of regional climate over the Hawaiian Islands.

scholarly journals Climate Model Evaluation in the Presence of Observational Uncertainty: Precipitation Indices over the Contiguous United States

2019 ◽  
Vol 20 (7) ◽  
pp. 1339-1357 ◽  
Author(s):  
Peter B. Gibson ◽  
Duane E. Waliser ◽  
Huikyo Lee ◽  
Baijun Tian ◽  
Elias Massoud
Keyword(s):  
United States ◽  
Model Evaluation ◽  
Climate Models ◽  
Climate Model ◽  
Dynamical Downscaling ◽  
Daily Precipitation ◽  
Regional Climate ◽  
Climate Model Evaluation ◽  
Observational Uncertainty ◽  
Precipitation Indices

Abstract Climate model evaluation is complicated by the presence of observational uncertainty. In this study we analyze daily precipitation indices and compare multiple gridded observational and reanalysis products with regional climate models (RCMs) from the North American component of the Coordinated Regional Climate Downscaling Experiment (NA-CORDEX) multimodel ensemble. In the context of model evaluation, observational product differences across the contiguous United States (CONUS) are also deemed nontrivial for some indices, especially for annual counts of consecutive wet days and for heavy precipitation indices. Multidimensional scaling (MDS) is used to directly include this observational spread into the model evaluation procedure, enabling visualization and interpretation of model differences relative to a “cloud” of observational uncertainty. Applying MDS to the evaluation of NA-CORDEX RCMs reveals situations of added value from dynamical downscaling, situations of degraded performance from dynamical downscaling, and the sensitivity of model performance to model resolution. On precipitation days, higher-resolution RCMs typically simulate higher mean and extreme precipitation rates than their lower-resolution pairs, sometimes improving model fidelity with observations. These results document the model spread and biases in daily precipitation extremes across the full NA-CORDEX model ensemble. The often-large divergence between in situ observations, satellite data, and reanalysis, shown here for CONUS, is especially relevant for data-sparse regions of the globe where satellite and reanalysis products are extensively relied upon. This highlights the need to carefully consider multiple observational products when evaluating climate models.

scholarly journals Uncertainties in climate change projections and regional downscaling in the tropical Andes: implications for water resources management

2010 ◽  
Vol 14 (7) ◽  
pp. 1247-1258 ◽  
Author(s):  
W. Buytaert ◽  
M. Vuille ◽  
A. Dewulf ◽  
R. Urrutia ◽  
A. Karmalkar ◽  
...  
Keyword(s):  
Climate Change ◽  
Water Resources ◽  
Water Resources Management ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Tropical Andes ◽  
Climate Change Projections ◽  
Resources Management

Abstract. Climate change is expected to have a large impact on water resources worldwide. A major problem in assessing the potential impact of a changing climate on these resources is the difference in spatial scale between available climate change projections and water resources management. Regional climate models (RCMs) are often used for the spatial disaggregation of the outputs of global circulation models. However, RCMs are time-intensive to run and typically only a small number of model runs is available for a certain region of interest. This paper investigates the value of the improved representation of local climate processes by a regional climate model for water resources management in the tropical Andes of Ecuador. This region has a complex hydrology and its water resources are under pressure. Compared to the IPCC AR4 model ensemble, the regional climate model PRECIS does indeed capture local gradients better than global models, but locally the model is prone to large discrepancies between observed and modelled precipitation. It is concluded that a further increase in resolution is necessary to represent local gradients properly. Furthermore, to assess the uncertainty in downscaling, an ensemble of regional climate models should be implemented. Finally, translating the climate variables to streamflow using a hydrological model constitutes a smaller but not negligible source of uncertainty.

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