Present day bias and future change signal of temperature over China in a series of multi-GCM driven RCM simulations

Abstract Simulation of surface air temperature over China from a set of regional climate model (RCM) climate change experiments are analyzed with the focus on bias and change signal of the RCM and driving general circulation models (GCMs). The set consists of 4 simulations by the RCM of RegCM4 driven by 4 different GCMs for the period of 1979–2099 under the mid-range RCP4.5 (representative concentration pathway) scenario. Results show that for present day conditions, the RCM provides with more spatial details of the distribution and in general reduces the biases of GCM, in particular in DJF (December–January–February) and over areas with complex topography. Bias patterns show some correlation between the RCM and driving GCM in DJF but not in JJA (June–July–August). In JJA, the biases in RCM simulations show similar pattern and low sensitivity to the driving GCM, which can be attributed to the large effect of internal model physics in the season. For change signals, dominant forcings from the driving GCM are evident in the RCM simulations as shown by the magnitude, large scale spatial distribution, as well as interannual variation of the changes. The added value of RCM projection is characterized by the finer spatial detail in sub-regional (river basins) and local scale. In DJF, profound warming over the Tibetan Plateau is simulated by RCM but not GCMs. In general no clear relationships are found between the model bias and change signal, either for the driving GCMs or nested RCM.

Download Full-text

Bias correction of temperature and precipitation over China for RCM simulations using the QM and QDM methods

Climate Dynamics ◽

10.1007/s00382-020-05447-4 ◽

2020 ◽

Cited By ~ 2

Author(s):

Yao Tong ◽

Xuejie Gao ◽

Zhenyu Han ◽

Yaqi Xu ◽

Ying Xu ◽

...

Keyword(s):

Bias Correction ◽

General Circulation ◽

Climate Model ◽

Regional Climate ◽

General Circulation Models ◽

Grid Spacing ◽

Quantile Mapping ◽

Temperature And Precipitation ◽

June July August ◽

June July

Abstract Two different bias correction methods, the quantile mapping (QM) and quantile delta mapping (QDM), are applied to simulated daily temperature and precipitation over China from a set of 21st century regional climate model (the ICTP RegCM4) projections. The RegCM4 is driven by five different general circulation models (GCMs) under the representative concentration pathway RCP4.5 at a grid spacing of 25 km using the CORDEX East Asia domain. The focus is on mean temperature and precipitation in December–January–February (DJF) and June–July–August (JJA). The impacts of the two methods on the present day biases and future change signals are investigated. Results show that both the QM and QDM methods are effective in removing the systematic model biases during the validation period. For the future changes, the QDM preserves the temperature change signals well, in both magnitude and spatial distribution, while the QM artificially modifies the change signal by decreasing the warming and modifying the patterns of change. For precipitation, both methods preserve the change signals well but they produce greater magnitude of the projected increase, especially the QDM. We also show that the effects of bias correction are variable- and season-dependent. Our results show that different bias correction methods can affect in different way the simulated change signals, and therefore care has to be taken in carrying out the bias correction process.

Download Full-text

Panama’s Current Climate Replicability in a Non-Hydrostatic Regional Climate Model Nested in an Atmospheric General Circulation Model

Atmosphere ◽

10.3390/atmos12121543 ◽

2021 ◽

Vol 12 (12) ◽

pp. 1543

Author(s):

Reinhardt Pinzón ◽

Noriko N. Ishizaki ◽

Hidetaka Sasaki ◽

Tosiyuki Nakaegawa

Keyword(s):

Regional Climate Model ◽

Air Temperature ◽

General Circulation ◽

Climate Model ◽

Regional Climate ◽

Surface Air Temperature ◽

Circulation Model ◽

Horizontal Resolution ◽

Temperature And Precipitation ◽

Current Climate

To simulate the current climate, a 20-year integration of a non-hydrostatic regional climate model (NHRCM) with grid spacing of 5 and 2 km (NHRCM05 and NHRCM02, respectively) was nested within the AGCM. The three models did a similarly good job of simulating surface air temperature, and the spatial horizontal resolution did not affect these statistics. NHRCM02 did a good job of reproducing seasonal variations in surface air temperature. NHRCM05 overestimated annual mean precipitation in the western part of Panama and eastern part of the Pacific Ocean. NHRCM05 is responsible for this overestimation because it is not seen in MRI-AGCM. NHRCM02 simulated annual mean precipitation better than NHRCM05, probably due to a convection-permitting model without a convection scheme, such as the Kain and Fritsch scheme. Therefore, the finer horizontal resolution of NHRCM02 did a better job of replicating the current climatological mean geographical distributions and seasonal changes of surface air temperature and precipitation.

Download Full-text

Description and Evaluation of the specified-dynamics experiment in the Chemistry-Climate Model Initiative

Atmospheric Chemistry and Physics ◽

10.5194/acp-20-3809-2020 ◽

2020 ◽

Vol 20 (6) ◽

pp. 3809-3840 ◽

Cited By ~ 2

Author(s):

Clara Orbe ◽

David A. Plummer ◽

Darryn W. Waugh ◽

Huang Yang ◽

Patrick Jöckel ◽

...

Keyword(s):

Seasonal Cycle ◽

General Circulation ◽

Large Scale ◽

Climate Model ◽

Phase 1 ◽

General Circulation Models ◽

Atmospheric Composition ◽

Cycle Amplitude ◽

Free Running ◽

Dynamics Simulations

Abstract. We provide an overview of the REF-C1SD specified-dynamics experiment that was conducted as part of phase 1 of the Chemistry-Climate Model Initiative (CCMI). The REF-C1SD experiment, which consisted of mainly nudged general circulation models (GCMs) constrained with (re)analysis fields, was designed to examine the influence of the large-scale circulation on past trends in atmospheric composition. The REF-C1SD simulations were produced across various model frameworks and are evaluated in terms of how well they represent different measures of the dynamical and transport circulations. In the troposphere there are large (∼40 %) differences in the climatological mean distributions, seasonal cycle amplitude, and trends of the meridional and vertical winds. In the stratosphere there are similarly large (∼50 %) differences in the magnitude, trends and seasonal cycle amplitude of the transformed Eulerian mean circulation and among various chemical and idealized tracers. At the same time, interannual variations in nearly all quantities are very well represented, compared to the underlying reanalyses. We show that the differences in magnitude, trends and seasonal cycle are not related to the use of different reanalysis products; rather, we show they are associated with how the simulations were implemented, by which we refer both to how the large-scale flow was prescribed and to biases in the underlying free-running models. In most cases these differences are shown to be as large or even larger than the differences exhibited by free-running simulations produced using the exact same models, which are also shown to be more dynamically consistent. Overall, our results suggest that care must be taken when using specified-dynamics simulations to examine the influence of large-scale dynamics on composition.

Download Full-text

Impacts of Dynamical Downscaling on Circulation type Statistics: Potential added Value in the Euro-CORDEX Ensemble

10.21203/rs.3.rs-682421/v1 ◽

2021 ◽

Author(s):

Julie Røste ◽

Oskar A Landgren

Keyword(s):

Large Scale ◽

Climate Model ◽

Dynamical Downscaling ◽

Regional Climate ◽

Circulation Type ◽

Global Model ◽

Added Value ◽

Classification Methods ◽

Circulation Types ◽

Climate Model Simulations

Abstract Atmospheric circulation type classification methods were applied to an ensemble of 57 regional climate model simulations from Euro-CORDEX, their 11 boundary models from CMIP5 and the ERA5 reanalysis. We compared frequencies of the different circulation types in the simulations with ERA5 and found that the regional models add value especially in the summer season. We applied three different classification methods (the subjective Grosswettertypes and the two optimisation algorithms SANDRA and distributed k-means clustering) from the cost733class software and found that the results are not particularly sensitive to choice of circulation classification method. There are large differences between models. Simulations based on MIROC-MIROC5 and CNRM-CERFACS-CNRM-CM5 show an over-representation of easterly flow and an under-representation of westerly. The downscaled results retain the large-scale circulation from the global model most days, but especially the regional model IPSL-WRF381P changes the circulation more often, which increases the error relative to ERA5. Simulations based on ICHEC-EC-EARTH and MPI-M-MPI-ESM-LR show consistently smaller errors relative to ERA5 in all seasons. The ensemble spread is largest in the summer and smallest in the winter. Under the future RCP8.5 scenario, more than half of the ensemble shows an increase in frequency of north-easterly flow and decrease in the Central-Eastern European high and south-easterly flow. There is in general a strong agreement in the sign of the change between the regional simulations and the data from the corresponding global model.

Download Full-text

On the potential use of glacier and permafrost observations for verification of climate models

Annals of Glaciology ◽

10.1017/s026030550001435x ◽

1997 ◽

Vol 25 ◽

pp. 400-406 ◽

Cited By ~ 2

Author(s):

Martin Beniston ◽

Wilfried Haeberli ◽

Martin Hoelzle ◽

Alan Taylor

Keyword(s):

General Circulation ◽

Climate Models ◽

Climate Model ◽

Global Climate ◽

Regional Climate ◽

Model Performance ◽

Regional Climate Models ◽

General Circulation Models ◽

Model Verification ◽

Dominant Feature

While the capability of global and regional climate models in reproducing current climate has significantly improved over the past few years, the confidence in model results for remote regions, or those where complex orography is a dominant feature, is still relatively low. This is, in part, linked to the lack of observational data for model verification and intercomparison purposes.Glacier and permafrost observations are directly related to past and present energy flux patterns at the Earth-atmosphere interface and could be used as a proxy for air temperature and precipitation, particularly of value in remote mountain regions and boreal and Arctic zones where instrumental climate records are sparse or non-existent. It is particularly important to verify climate-model performance in these regions, as this is where most general circulation models (GCMs) predict the greatest changes in air temperatures in a warmer global climate.Existing datasets from glacier and permafrost monitoring sites in remote and high altitudes are described in this paper; the data could be used in model-verification studies, as a means to improving model performance in these regions.

Download Full-text

Evaluation of Historical CMIP5 GCM Simulation Results Based on Detected Atmospheric Teleconnections

Atmosphere ◽

10.3390/atmos11070723 ◽

2020 ◽

Vol 11 (7) ◽

pp. 723 ◽

Cited By ~ 1

Author(s):

Erzsébet Kristóf ◽

Zoltán Barcza ◽

Roland Hollós ◽

Judit Bartholy ◽

Rita Pongrácz

Keyword(s):

General Circulation ◽

Large Scale ◽

Evaluation Method ◽

Polynomial Regression ◽

Diversity Index ◽

Regional Climate ◽

Coupled Model ◽

General Circulation Models ◽

Teleconnection Patterns ◽

Atmospheric Teleconnections

Atmospheric teleconnections are characteristic to the climate system and exert major impacts on the global and regional climate. Accurate representation of teleconnections by general circulation models (GCMs) is indispensable given their fundamental role in the large scale circulation patterns. In this study a statistical method is introduced to evaluate historical GCM outputs of the fifth phase of the Coupled Model Intercomparison Project (CMIP5) with respect to teleconnection patterns. The introduced method is based on the calculation of correlations between gridded time series of the 500 hPa geopotential height fields in the Northern Hemisphere. GCMs are quantified by a simple diversity index. Additionally, potential action centers of the teleconnection patterns are identified on which the local polynomial regression model is fitted. Diversity fields and regression curves obtained from the GCMs are compared against the NCEP/NCAR Reanalysis 1 and the ERA-20C reanalysis datasets. The introduced method is objective, reproducible, and reduces the number of arbitrary decisions during the analysis. We conclude that major teleconnection patterns are positioned in the GCMs and in the reanalysis datasets similarly, however, spatial differences in their intensities can be severe in some cases that could hamper the applicability of the GCM results for some regions. Based on the evaluation method, best-performing GCMs can be clearly distinguished. Evaluation of the GCMs based on the introduced method might help the modeling community to choose GCMs that are the most applicable for impact studies and for regional downscaling exercises.

Download Full-text

Climate Change Implications for Tropical Islands: Interpolating and Interpreting Statistically Downscaled GCM Projections for Management and Planning

Journal of Applied Meteorology and Climatology ◽

10.1175/jamc-d-15-0182.1 ◽

2016 ◽

Vol 55 (2) ◽

pp. 265-282 ◽

Cited By ~ 44

Author(s):

Azad Henareh Khalyani ◽

William A. Gould ◽

Eric Harmsen ◽

Adam Terando ◽

Maya Quinones ◽

...

Keyword(s):

Climate Change ◽

Energy Demand ◽

General Circulation ◽

Large Scale ◽

Climate Model ◽

Model Averaging ◽

General Circulation Models ◽

Economic Effects ◽

Drought Indices ◽

Tropical Islands

AbstractThe potential ecological and economic effects of climate change for tropical islands were studied using output from 12 statistically downscaled general circulation models (GCMs) taking Puerto Rico as a test case. Two model selection/model averaging strategies were used: the average of all available GCMs and the average of the models that are able to reproduce the observed large-scale dynamics that control precipitation over the Caribbean. Five island-wide and multidecadal averages of daily precipitation and temperature were estimated by way of a climatology-informed interpolation of the site-specific downscaled climate model output. Annual cooling degree-days (CDD) were calculated as a proxy index for air-conditioning energy demand, and two measures of annual no-rainfall days were used as drought indices. Holdridge life zone classification was used to map the possible ecological effects of climate change. Precipitation is predicted to decline in both model ensembles, but the decrease was more severe in the “regionally consistent” models. The precipitation declines cause gradual and linear increases in drought intensity and extremes. The warming from the 1960–90 period to the 2071–99 period was 4.6°–9°C depending on the global emission scenarios and location. This warming may cause increases in CDD, and consequently increasing energy demands. Life zones may shift from wetter to drier zones with the possibility of losing most, if not all, of the subtropical rain forests and extinction risks to rain forest specialists or obligates.

Download Full-text

Robust Late 21st Century Shift in the Regional Monsoons in RegCM-CORDEX Simulations

10.5194/egusphere-egu2020-12102 ◽

2020 ◽

Author(s):

Moetasim Ashfaq ◽

Tereza Cavazos ◽

Michelle Reboita ◽

José Abraham Torres-Alavez ◽

Eun-Soon Im ◽

...

Keyword(s):

Radiative Forcing ◽

General Circulation ◽

Climate Model ◽

Regional Climate ◽

Lower Boundary ◽

Coupled Model ◽

General Circulation Models ◽

Monsoon Onset ◽

Historical Period ◽

Monsoon Period

<p>We use an unprecedented ensemble of regional climate model (RCM) projections over seven regional CORDEX domains to provide, for the first time, an RCM-based global view of monsoon changes at various levels of increased greenhouse gas (GHG) forcing. All regional simulations are conducted using RegCM4 at a 25km horizontal grid spacing using lateral and lower boundary forcing from three General Circulation Models (GCMs), which are part of the fifth phase of the Coupled Model Inter-comparison Project (CMIP5). Each simulation covers the period from 1970 through 2100 under two Representative Concentration Pathways (RCP2.6 and RCP8.5). Regional climate simulations exhibit high fidelity in capturing key characteristics of precipitation and atmospheric dynamics across monsoon regions in the historical period. In the future period, regional monsoons exhibit a spatially robust delay in the monsoon onset, an increase in seasonality, and a reduction in the rainy season length at higher levels of radiative forcing. All regions with substantial delays in the monsoon onset exhibit a decrease in pre-monsoon precipitation, indicating a strong connection between pre-monsoon drying and a shift in the monsoon onset. The weakening of latent heat driven atmospheric warming during the pre-monsoon period delays the overturning of atmospheric subsidence in the monsoon regions, which defers their transitioning into deep convective states. Monsoon changes under the RCP2.6 scenario are mostly within the baseline variability.&#160;</p>

Download Full-text

A climate model intercomparison for the Antarctic region: present and past

Climate of the Past ◽

10.5194/cp-8-803-2012 ◽

2012 ◽

Vol 8 (2) ◽

pp. 803-814 ◽

Cited By ~ 7

Author(s):

M. N. A. Maris ◽

B. de Boer ◽

J. Oerlemans

Keyword(s):

General Circulation ◽

Climate Model ◽

Reference Data ◽

Regional Climate ◽

Ice Core ◽

Ice Sheet ◽

General Circulation Models ◽

Antarctic Region ◽

The Past ◽

The Antarctic

Abstract. Eighteen General Circulation Models (GCMs) are compared to reference data for the present, the Mid-Holocene (MH) and the Last Glacial Maximum (LGM) for the Antarctic region. The climatology produced by a regional climate model is taken as a reference climate for the present. GCM results for the past are compared to ice-core data. The goal of this study is to find the best GCM that can be used to drive an ice sheet model that simulates the evolution of the Antarctic Ice Sheet. Because temperature and precipitation are the most important climate variables when modelling the evolution of an ice sheet, these two variables are considered in this paper. This is done by ranking the models according to how well their output corresponds with the references. In general, present-day temperature is simulated well, but precipitation is overestimated compared to the reference data. Another finding is that model biases play an important role in simulating the past, as they are often larger than the change in temperature or precipitation between the past and the present. Considering the results for the present-day as well as for the MH and the LGM, the best performing models are HadCM3 and MIROC 3.2.2.

Download Full-text

Characterizing Sierra Nevada Snowpack Using Variable-Resolution CESM

Journal of Applied Meteorology and Climatology ◽

10.1175/jamc-d-15-0156.1 ◽

2016 ◽

Vol 55 (1) ◽

pp. 173-196 ◽

Cited By ~ 33

Author(s):

Alan M. Rhoades ◽

Xingying Huang ◽

Paul A. Ullrich ◽

Colin M. Zarzycki

Keyword(s):

Sierra Nevada ◽

General Circulation ◽

Water Resource Management ◽

Large Scale ◽

Climate Model ◽

Global Climate ◽

Global Climate Model ◽

Winter Season ◽

General Circulation Models ◽

Variable Resolution

AbstractThe location, timing, and intermittency of precipitation in California make the state integrally reliant on winter-season snowpack accumulation to maintain its economic and agricultural livelihood. Of particular concern is that winter-season snowpack has shown a net decline across the western United States over the past 50 years, resulting in major uncertainty in water-resource management heading into the next century. Cutting-edge tools are available to help navigate and preemptively plan for these uncertainties. This paper uses a next-generation modeling technique—variable-resolution global climate modeling within the Community Earth System Model (VR-CESM)—at horizontal resolutions of 0.125° (14 km) and 0.25° (28 km). VR-CESM provides the means to include dynamically large-scale atmosphere–ocean drivers, to limit model bias, and to provide more accurate representations of regional topography while doing so in a more computationally efficient manner than can be achieved with conventional general circulation models. This paper validates VR-CESM at climatological and seasonal time scales for Sierra Nevada snowpack metrics by comparing them with the “Daymet,” “Cal-Adapt,” NARR, NCEP, and North American Land Data Assimilation System (NLDAS) reanalysis datasets, the MODIS remote sensing dataset, the SNOTEL observational dataset, a standard-practice global climate model (CESM), and a regional climate model (WRF Model) dataset. Overall, given California’s complex terrain and intermittent precipitation and that both of the VR-CESM simulations were only constrained by prescribed sea surface temperatures and data on sea ice extent, a 0.68 centered Pearson product-moment correlation, a negative mean SWE bias of <7 mm, an interquartile range well within the values exhibited in the reanalysis datasets, and a mean December–February extent of snow cover that is within 7% of the expected MODIS value together make apparent the efficacy of the VR-CESM framework.

Download Full-text