Can Regional Climate Models Represent the Indian Monsoon?

2011 ◽  
Vol 12 (5) ◽  
pp. 849-868 ◽  
Author(s):  
Philippe Lucas-Picher ◽  
Jens H. Christensen ◽  
Fahad Saeed ◽  
Pankaj Kumar ◽  
Shakeel Asharaf ◽  
...  
Keyword(s):  
Climate Models ◽  
Indian Monsoon ◽  
Regional Climate ◽  
Regional Scale ◽  
Regional Distribution ◽  
Regional Climate Models ◽  
Monsoon Period ◽  
Sea Temperature ◽  
The North ◽  
The One

Abstract The ability of four regional climate models (RCMs) to represent the Indian monsoon was verified in a consistent framework for the period 1981–2000 using the 45-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-40) as lateral boundary forcing data. During the monsoon period, the RCMs are able to capture the spatial distribution of precipitation with a maximum over the central and west coast of India, but with important biases at the regional scale on the east coast of India in Bangladesh and Myanmar. Most models are too warm in the north of India compared to the observations. This has an impact on the simulated mean sea level pressure from the RCMs, being in general too low compared to ERA-40. Those biases perturb the land–sea temperature and pressure contrasts that drive the monsoon dynamics and, as a consequence, lead to an overestimation of wind speed, especially over the sea. The timing of the monsoon onset of the RCMs is in good agreement with the one obtained from observationally based gridded datasets, while the monsoon withdrawal is less well simulated. A Hovmöller diagram representation of the mean annual cycle of precipitation reveals that the meridional motion of the precipitation simulated by the RCMs is comparable to the one observed, but the precipitation amounts and the regional distribution differ substantially between the four RCMs. In summary, the spread at the regional scale between the RCMs indicates that important feedbacks and processes are poorly, or not, taken into account in the state-of-the-art regional climate models.

scholarly journals Spatial and temporal characteristics in streamflow-related hydroclimatic variables over western Canada. Part 2: future projections

2016 ◽  
Vol 48 (4) ◽  
pp. 932-944 ◽  
Author(s):  
H. C. L. O'Neil ◽  
T. D. Prowse ◽  
B. R. Bonsal ◽  
Y. B. Dibike
Keyword(s):  
Snow Depth ◽  
Climate Models ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Cold Season ◽  
Maximum Temperature ◽  
Western Canada ◽  
The North ◽  
Spring Freshet ◽  
Hydroclimatic Variables

Much of the freshwater in western Canada originates in the Rocky Mountains as snowpack. Temperature and precipitation patterns throughout the region control the amount of snow accumulated and stored throughout the winter, and the intensity and timing of melt during the spring freshet. Therefore, changes in temperature, precipitation, snow depth, and snowmelt over western Canada are examined through comparison of output from the current and future periods of a series of regional climate models for the time periods 1971–2000 and 2041–2070. Temporal and spatial analyses of these hydroclimatic variables indicate that minimum temperature is likely to increase more than maximum temperature, particularly during the cold season, possibly contributing to earlier spring melt. Precipitation is projected to increase, particularly in the north. In the coldest months of the year snow depth is expected to increase in northern areas and decrease across the rest of study area. Snowmelt results indicate increases in mid-winter melt events and an earlier onset of the spring freshet. This study provides a summary of potential future climate using key hydroclimatic variables across western Canada with regard to the effects these changes may have on streamflow and the spring freshet, and thus water resources, throughout the study area.

scholarly journals The KLIWAS North Sea Climatology. Part I: Processing of the Atmospheric Data

2018 ◽  
Vol 35 (1) ◽  
pp. 111-126 ◽  
Author(s):  
Remon Sadikni ◽  
Nils H. Schade ◽  
Axel Andersson ◽  
Annika Jahnke-Bornemann ◽  
Iris Hinrichs ◽  
...  
Keyword(s):  
North Sea ◽  
Climate Models ◽  
Sampling Error ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Climate Data ◽  
The North ◽  
Dewpoint Temperature ◽  
The Baltic ◽  
The University

AbstractClimatological reference data serve as validation of regional climate models, as the boundary condition for the model runs, and as input for assimilation systems used by reanalyses. Within the framework of the interdisciplinary research program Climate Water Navigation (KLIWAS): Impacts of Climate Change on Waterways and Navigation of the German Federal Ministry of Transport and Digital Infrastructure, a new climatology of the North Sea and adjacent regions was developed in an joint effort by the Federal Maritime and Hydrographic Agency, the German Weather Service [Deutscher Wetterdienst (DWD)], and the Integrated Climate Data Center (ICDC) of the University of Hamburg. Long-term records of monthly and annual mean 2-m air temperature, dewpoint temperature, and sea level pressure data from 1950 to 2010 were calculated on a horizontal 1° × 1° grid. All products were based on quality-controlled data from DWD’s Marine Data Centre. Correction methods were implemented for each parameter to reduce the sampling error resulting from the sparse coverage of observations in certain regions. Comparisons between sampling error estimates based on ERA-40 and the climatology products show that the sampling error was reduced effectively. The climatologies are available for download on the ICDC’s website and will be updated regularly regarding new observations and additional parameters. An extension to the Baltic Sea is in progress.

scholarly journals Species Favourability Shift in Europe due to Climate Change: A Case Study for Fagus sylvatica L. and Picea abies (L.) Karst. Based on an Ensemble of Climate Models

2013 ◽  
Vol 2013 ◽  
pp. 1-18 ◽  
Author(s):  
Wolfgang Falk ◽  
Nils Hempelmann
Keyword(s):  
Climate Change ◽  
Species Distribution ◽  
Climate Models ◽  
Species Distribution Model ◽  
Regional Climate ◽  
European Beech ◽  
Regional Climate Models ◽  
Distribution Model ◽  
Continental Scale ◽  
The North

Climate is the main environmental driver determining the spatial distribution of most tree species at the continental scale. We investigated the distribution change of European beech and Norway spruce due to climate change. We applied a species distribution model (SDM), driven by an ensemble of 21 regional climate models in order to study the shift of the favourability distribution of these species. SDMs were parameterized for 1971–2000, as well as 2021–2050 and 2071–2100 using the SRES scenario A1B and three physiological meaningful climate variables. Growing degree sum and precipitation sum were calculated for the growing season on a basis of daily data. Results show a general north-eastern and altitudinal shift in climatological favourability for both species, although the shift is more marked for spruce. The gain of new favourable sites in the north or in the Alps is stronger for beech compared to spruce. Uncertainty is expressed as the variance of the averaged maps and with a density function. Uncertainty in species distribution increases over time. This study demonstrates the importance of data ensembles and shows how to deal with different outcomes in order to improve impact studies by showing uncertainty of the resulting maps.

scholarly journals A quantitative method to decompose SWE differences between regional climate models and reanalysis datasets

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Yun Xu ◽  
Andrew Jones ◽  
Alan Rhoades
Keyword(s):  
Sierra Nevada ◽  
Climate Models ◽  
Snow Water Equivalent ◽  
Driving Forces ◽  
Regional Climate ◽  
Model Development ◽  
Regional Climate Models ◽  
The North ◽  
Snow Water ◽  
Regional Downscaling

Abstract The simulation of snow water equivalent (SWE) remains difficult for regional climate models. Accurate SWE simulation depends on complex interacting climate processes such as the intensity and distribution of precipitation, rain-snow partitioning, and radiative fluxes. To identify the driving forces behind SWE difference between model and reanalysis datasets, and guide model improvement, we design a framework to quantitatively decompose the SWE difference contributed from precipitation distribution and magnitude, ablation, temperature and topography biases in regional climate models. We apply this framework within the California Sierra Nevada to four regional climate models from the North American Coordinated Regional Downscaling Experiment (NA-CORDEX) run at three spatial resolutions. Models generally predict less SWE compared to Landsat-Era Sierra Nevada Snow Reanalysis (SNSR) dataset. Unresolved topography associated with model resolution contribute to dry and warm biases in models. Refining resolution from 0.44° to 0.11° improves SWE simulation by 35%. To varying degrees across models, additional difference arises from spatial and elevational distribution of precipitation, cold biases revealed by topographic correction, uncertainties in the rain-snow partitioning threshold, and high ablation biases. This work reveals both positive and negative contributions to snow bias in climate models and provides guidance for future model development to enhance SWE simulation.

scholarly journals Future Decreases in Freezing Days across North America

2016 ◽  
Vol 29 (19) ◽  
pp. 6923-6935 ◽  
Author(s):  
Michael A. Rawlins ◽  
Raymond S. Bradley ◽  
Henry F. Diaz ◽  
John S. Kimball ◽  
David A. Robinson
Keyword(s):  
North America ◽  
Climate Models ◽  
Regional Climate ◽  
Regional Climate Models ◽  
The United States ◽  
Rate Of Change ◽  
Mean Annual Temperature ◽  
The North ◽  
Air Temperatures ◽  
Climate Change Assessment

Abstract This study used air temperatures from a suite of regional climate models participating in the North American Climate Change Assessment Program (NARCCAP) together with two atmospheric reanalysis datasets to investigate changes in freezing days (defined as days with daily average temperature below freezing) likely to occur between 30-yr baseline (1971–2000) and midcentury (2041–70) periods across most of North America. Changes in NARCCAP ensemble mean winter temperature show a strong gradient with latitude, with warming of over 4°C near Hudson Bay. The decline in freezing days ranges from less than 10 days across north-central Canada to nearly 90 days in the warmest areas of the continent that currently undergo seasonally freezing conditions. The area experiencing freezing days contracts by 0.9–1.0 × 106 km2 (5.7%–6.4% of the total area). Areas with mean annual temperature between 2° and 6°C and a relatively low rate of change in climatological daily temperatures (<0.2°C day−) near the time of spring thaw will encounter the greatest decreases in freezing days. Advances in the timing of spring thaw will exceed the delay in fall freeze across much of the United States, with the reverse pattern likely over most of Canada.

scholarly journals Greenhouse Gas–Induced Changes in Summer Precipitation over Colorado in NARCCAP Regional Climate Models*

2013 ◽  
Vol 26 (21) ◽  
pp. 8690-8697 ◽  
Author(s):  
Michael A. Alexander ◽  
James D. Scott ◽  
Kelly Mahoney ◽  
Joseph Barsugli
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Summer Precipitation ◽  
Regional Climate Change ◽  
Regional Climate Models ◽  
Specific Humidity ◽  
The North ◽  
Climate Model Simulations ◽  
Climate Change Assessment

Abstract Precipitation changes between 32-yr periods in the late twentieth and mid-twenty-first centuries are investigated using regional climate model simulations provided by the North American Regional Climate Change Assessment Program (NARCCAP). The simulations generally indicate drier summers in the future over most of Colorado and the border regions of the adjoining states. The decrease in precipitation occurs despite an increase in the surface specific humidity. The domain-averaged decrease in daily summer precipitation occurs in all of the models from the 50th through the 95th percentile, but without a clear agreement on the sign of change for the most extreme (top 1% of) events.

scholarly journals Dynamical Downscaling in Seasonal Climate Forecasts: Comparison between RegCM- and WRF-Based Approaches

Atmosphere ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 757
Author(s):  
Lorenzo Sangelantoni ◽  
Antonio Ricchi ◽  
Rossella Ferretti ◽  
Gianluca Redaelli
Keyword(s):  
Large Scale ◽  
Climate Models ◽  
Dynamical Downscaling ◽  
Regional Climate ◽  
Regional Scale ◽  
Central Italy ◽  
Probabilistic Approach ◽  
Regional Climate Models ◽  
Added Value ◽  
Temperature Fields

The purpose of the present study is to assess the large-scale signal modulation produced by two dynamically downscaled Seasonal Forecasting Systems (SFSs) and investigate if additional predictive skill can be achieved, compared to the driving global-scale Climate Forecast System (CFS). The two downscaled SFSs are evaluated and compared in terms of physical values and anomaly interannual variability. Downscaled SFSs consist of two two-step dynamical downscaled ensembles of NCEP-CFSv2 re-forecasts. In the first step, the CFS field is downscaled from 100 km to 60 km over Southern Europe (D01). The second downscaling, driven by the corresponding D01, is performed at 12 km over Central Italy (D02). Downscaling is performed using two different Regional Climate Models (RCMs): RegCM v.4 and WRF 3.9.1.1. SFS skills are assessed over a period of 21 winter seasons (1982–2002), by means of deterministic and probabilistic approach and with a metric specifically designed to isolate downscaling signal over different percentiles of distribution. Considering the temperature fields and both deterministic and probabilistic metrics, regional-scale SFSs consistently improve the original CFS Seasonal Anomaly Signal (SAS). For the precipitation, the added value of downscaled SFSs is mainly limited to the topography driven refinement of precipitation field, whereas the SAS is mainly “inherited” by the driving CFS. The regional-scale SFSs do not seem to benefit from the second downscaling (D01 to D02) in terms of SAS improvement. Finally, WRF and RegCM show substantial differences in both SAS and climatologically averaged fields, highlighting a different impact of the common SST driving field.

scholarly journals Zustand und Entwicklung der Trockenheit in Schweizer Wäldern

2015 ◽  
Vol 166 (6) ◽  
pp. 352-360 ◽  
Author(s):  
Jan Remund ◽  
Sabine Augustin
Keyword(s):  
Regional Differences ◽  
Climate Models ◽  
Potential Evapotranspiration ◽  
Regional Climate ◽  
Regional Scale ◽  
Climate Scenario ◽  
Regional Climate Models ◽  
Weather Extremes ◽  
Climatic Regions ◽  
Site Water

State and development of drought in Swiss forests Climate scenarios for the 21st century for Switzerland show increasing temperatures and more frequent weather extremes and the risk of drought will become more important. The objective of the study was the calculation of indicators which allow the estimation and evaluation of drought risks on a regional scale. The site water balance and the ratio between actual and potential evapotranspiration (ETa/ETp) were used as indicators. They are closely related to vitality parameters of trees. For projections in the future were used the A1B climate scenario, which assumes a warming of 2.7 to 4.1°C in Switzerland, and three regional climate models (CLM, RCA, REGCM3), which predict different developments regarding precipitation and temperature. Historical time series between 1951 and 2012 and scenarios up to 2100 for different climatic regions were calculated. The indicators reproduce well the measured trends and the regional differences. In all regions there was in the past a trend to increased drought. The Geneva/ Vaud region as well as the western midlands and north Switzerland show the most pronounced changes. Projections with the CLM model (which reproduced best the historic trend 1981–2010 for Switzerland) show increasing drought and, in general, an increasing variability of the climate for the mid-century.

scholarly journals The regional impact of urban emissions on air quality in Europe: the role of the urban canopy effects

2021 ◽  
Vol 21 (18) ◽  
pp. 14309-14332
Author(s):  
Peter Huszar ◽  
Jan Karlický ◽  
Jana Marková ◽  
Tereza Nováková ◽  
Marina Liaskoni ◽  
...  
Keyword(s):  
Air Quality ◽  
Land Surface ◽  
Climate Models ◽  
Regional Climate ◽  
Regional Scale ◽  
Urban Canopy ◽  
Regional Climate Models ◽  
Near Surface ◽  
Urban Emissions ◽  
The Impact

Abstract. Urban areas are hot spots of intense emissions, and they influence air quality not only locally but on a regional or even global scale. The impact of urban emissions over different scales depends on the dilution and chemical transformation of the urban plumes which are governed by the local- and regional-scale meteorological conditions. These are influenced by the presence of urbanized land surface via the so-called urban canopy meteorological forcing (UCMF). In this study, we investigate for selected central European cities (Berlin, Budapest, Munich, Prague, Vienna and Warsaw) how the urban emission impact (UEI) is modulated by the UCMF for present-day climate conditions (2015–2016) using two regional climate models, the regional climate models RegCM and Weather Research and Forecasting model coupled with Chemistry (WRF-Chem; its meteorological part), and two chemistry transport models, Comprehensive Air Quality Model with Extensions (CAMx) coupled to either RegCM and WRF and the “chemical” component of WRF-Chem. The UCMF was calculated by replacing the urbanized surface by a rural one, while the UEI was estimated by removing all anthropogenic emissions from the selected cities. We analyzed the urban-emission-induced changes in near-surface concentrations of NO2, O3 and PM2.5. We found increases in NO2 and PM2.5 concentrations over cities by 4–6 ppbv and 4–6 µg m−3, respectively, meaning that about 40 %–60 % and 20 %–40 % of urban concentrations of NO2 and PM2.5 are caused by local emissions, and the rest is the result of emissions from the surrounding rural areas. We showed that if UCMF is included, the UEI of these pollutants is about 40 %–60 % smaller, or in other words, the urban emission impact is overestimated if urban canopy effects are not taken into account. In case of ozone, models due to UEI usually predict decreases of around −2 to −4 ppbv (about 10 %–20 %), which is again smaller if UCMF is considered (by about 60 %). We further showed that the impact on extreme (95th percentile) air pollution is much stronger, and the modulation of UEI is also larger for such situations. Finally, we evaluated the contribution of the urbanization-induced modifications of vertical eddy diffusion to the modulation of UEI and found that it alone is able to explain the modeled decrease in the urban emission impact if the effects of UCMF are considered. In summary, our results showed that the meteorological changes resulting from urbanization have to be included in regional model studies if they intend to quantify the regional footprint of urban emissions. Ignoring these meteorological changes can lead to the strong overestimation of UEI.

Future Snow Water Equivalent and Snowmelt Extremes from NA-CORDEX Ensembles

2020 ◽  
Author(s):  
Eunsang Cho ◽  
Rachel R. McCrary ◽  
Jennifer M. Jacobs
Keyword(s):  
21St Century ◽  
Extreme Events ◽  
Climate Models ◽  
Snow Water Equivalent ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Natural Environments ◽  
The North ◽  
Snow Water ◽  
Late 21St Century

<p>Snowpack and snowmelt driven extreme events can have large societal and economic consequences. Extreme snow can damage infrastructure and buildings. Snow meltwater is a dominant driver of severe spring flooding in the north-central and -eastern U.S. and southern Canada with impacts to the built and natural environments. However, the currently there is very limited guidance regarding the magnitude of “future” snow-driven extremes in a changing climate as needed to plan, design, and manage potentially vulnerable infrastructure and ecosystems. Regional climate models (RCMs) are commonly used to study and quantify regional climate changes, even though the ability of these models to accurately represent snow varies. In this study, trends and designs of extreme 25- and 100-year snowpack (snow water equivalent; SWE) and snowmelt events are estimated in the mid and late 21st century using the North America - Coordinated Regional Climate Downscaling Experiment (NA-CORDEX) ensemble of RCMs under Representative Con-centration Pathways 8.5 (RCP 8.5). This study aims to answer the following three research questions:</p><ol><li>How much will snow-driven extreme events be changed in the mid and late 21st century?</li> <li>Which regions have the largest differences among models?</li> <li>Which RCM models are the source of these regional uncertainties?</li> </ol>

Sign in / Sign up

Export Citation Format

Share Document