scholarly journals Evaluation of convective parameters derived from pressure level and native ERA5 data and different resolution WRF climate simulations over Central Europe

2021 ◽  
Author(s):  
Ákos János Varga ◽  
Hajnalka Breuer
Keyword(s):  
Large Scale ◽  
Climate Model ◽  
Regional Climate ◽  
Wrf Model ◽  
Environmental Parameters ◽  
Pressure Level ◽  
Lapse Rate ◽  
Strong Suppression ◽  
Climate Simulations ◽  
Multiple Variables

AbstractThe mean climatological distribution of convective environmental parameters from the ERA5 reanalysis and WRF regional climate simulations is evaluated using radiosonde observations. The investigation area covers parts of Central and Eastern Europe. Severe weather proxies are calculated from daily 1200 UTC sounding measurements and collocated ERA5 and WRF pseudo-profiles in the 1985–2010 period. The pressure level and the native ERA5 reanalysis, and two WRF runs with grid spacings of 50 and 10 km are verified. ERA5 represents convective parameters remarkably well with correlation coefficients higher than 0.9 for multiple variables and mean errors close to zero for precipitable water and mid-tropospheric lapse rate. Monthly mean mixed-layer CAPE biases are reduced in the full hybrid-sigma ERA5 dataset by 20–30 J/kg compared to its pressure level version. The WRF model can reproduce the annual cycle of thunderstorm predictors but with considerably lower correlations and higher errors than ERA5. Surface elevation differences between the stations and the corresponding grid points in the 50-km WRF run lead to biases and false error compensations in the convective indices. The 10-km grid spacing is sufficient to avoid such discrepancies. The evaluation of convection-related parameters contributes to a better understanding of regional climate model behavior. For example, a strong suppression of convective activity might explain precipitation underestimation in summer. A decreasing correlation of WRF-derived wind shear away from the western domain boundaries indicates a deterioration of the large-scale circulation as the constraining effect of the driving reanalysis weakens.

scholarly journals Causes of future Mediterranean precipitation decline depend on the season

2020 ◽  
Author(s):  
Roman Brogli ◽  
Silje Lund Sørland ◽  
Nico Kröner ◽  
Christoph Schär
Keyword(s):  
Climate Change ◽  
Large Scale ◽  
Climate Model ◽  
Regional Climate ◽  
Lapse Rate ◽  
Environmental Research ◽  
Economic Sectors ◽  
Climate Simulations ◽  
The Mediterranean ◽  
Circulation Changes

<p>The Mediterranean is among the global 'hot-spots' of climate change, where severe consequences of climate change are expected. Changes in the atmospheric water cycle are among the leading causes of the vulnerability of the Mediterranean to greenhouse gas-driven warming. Specifically, precipitation is projected to decrease year-round, which is expected to have major impacts on hydrology, biodiversity, agriculture, hydropower, and further economic sectors that rely on sufficient water supply.</p><p>We investigate possible causes of the Mediterranean drying in regional climate simulations. To isolate the influence of multiple large-scale drivers on the drying, we sequentially add the respective drivers from global models to regional climate model simulations. We show that the causes of the Mediterranean drying depend on the season. We will present in detail how the summer drying is driven by the land-ocean warming contrast, lapse-rate and other thermodynamic changes, while it only weakly depends on circulation changes. In contrast, changes in the circulation are the primary driver for the projected winter precipitation decline. Since land-ocean contrast, thermodynamic and lapse-rate changes are more robust in climate simulations than circulation changes, the uncertainty associated with the projected drying should be considered smaller in summer than in winter.</p><p>Reference: Brogli, R., S. L. Sørland, N. Kröner, and C. Schär, 2019: Causes of future Mediterranean precipitation decline depend on the season. Environmental Research Letters, 14, 114017, doi:10.1088/1748-9326/ab4438.</p>

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.

Large-scale drivers of the Mediterranean climate change hot-spot

2021 ◽  
Author(s):  
Roman Brogli ◽  
Silje Lund Sørland ◽  
Nico Kröner ◽  
Christoph Schär
Keyword(s):  
Climate Change ◽  
Large Scale ◽  
Hot Spot ◽  
Regional Climate ◽  
Lapse Rate ◽  
Summer Climate ◽  
Climate Simulations ◽  
Summer Warming ◽  
The Mediterranean ◽  
Circulation Changes

&lt;div&gt; &lt;p&gt;&lt;span&gt;It has long been recognized that the Mediterranean is a &amp;#8216;hot-spot&amp;#8217; of climate change. The model-projected year-round precipitation decline and amplified summer warming are among the leading causes of the vulnerability of the Mediterranean to greenhouse gas-driven warming. We investigate large-scale drivers influencing both the Mediterranean drying and summer warming in regional climate simulations. To isolate the influence of multiple large-scale drivers, we sequentially add the respective drivers from global models to regional climate model simulations. Additionally, we confirm the robustness of our results across multiple ensembles of global and regional climate simulations.&lt;/span&gt;&lt;/p&gt; &lt;/div&gt;&lt;div&gt; &lt;p&gt;&lt;span&gt;We will present in detail how changes in the atmospheric stratification are key in causing the amplified Mediterranean summer warming. Together with the land-ocean warming contrast, stratification changes also drive the summer precipitation decline. Summer circulation changes generally have a surprisingly small influence on the changing Mediterranean summer climate. In contrast, changes in the circulation are the primary driver for the projected winter precipitation decline. Since land-ocean contrast and stratification changes are more robust in global climate simulations than circulation changes, we argue that the uncertainty associated with the projected climate change patterns should be considered smaller in summer than in winter.&lt;/span&gt;&lt;/p&gt; &lt;/div&gt;&lt;div&gt; &lt;p&gt;&lt;span&gt;References:&lt;/span&gt;&lt;/p&gt; &lt;/div&gt;&lt;div&gt; &lt;p&gt;&lt;span&gt;Brogli, R., S. L. S&amp;#248;rland, N. Kr&amp;#246;ner, and C. Sch&amp;#228;r, 2019: Causes of future Mediterranean precipitation decline depend on the season. Environmental Research Letters, 14, 114017, doi:10.1088/1748-9326/ab4438.&lt;/span&gt;&lt;/p&gt; &lt;/div&gt;&lt;div&gt; &lt;p&gt;&lt;span&gt;Brogli, R., N. Kr&amp;#246;ner, S. L. S&amp;#248;rland, D. L&amp;#252;thi and C. Sch&amp;#228;r, 2019: The Role of Hadley Circulation and Lapse-Rate Changes for the Future European Summer Climate. Journal of Climate, 32, 385-404, doi:10.1175/JCLI-D-18-0431.1&lt;/span&gt;&lt;/p&gt; &lt;/div&gt;

Verification of climatological ERA5 and WRF convective environments using radiosonde data

2021 ◽  
Author(s):  
Ákos János Varga ◽  
Hajnalka Breuer
Keyword(s):  
Climate Model ◽  
Pannonian Basin ◽  
Regional Climate ◽  
Environmental Parameters ◽  
Lapse Rate ◽  
Radiosonde Data ◽  
Monthly Basis ◽  
Environmental Indices ◽  
Level Data ◽  
Thermodynamic Variables

&lt;p&gt;Atmospheric convection is a major source of hazardous weather in many parts of the world, including the Pannonian Basin in Central Europe. It is therefore indispensable to explore the climatological distribution of convective environments and related phenomena, for which model data provide a spatially and temporally consistent alternative.&lt;/p&gt;&lt;p&gt;Several studies compared convective parameters derived from reanalysis datasets to radiosonde observations, but such evaluation of climate model output is less frequent.&lt;/p&gt;&lt;p&gt;This study uses sounding station measurements to verify convective environmental parameters derived from the ERA5 reanalysis and relatively coarse resolution WRF regional climate simulations for the 1985&amp;#8211;2010 period over the wider Pannonian Basin region. Common parcel thermodynamic variables and environmental indices are calculated, such as CAPE, CIN, LI, TPW, lapse rate and wind shear. We carry out pointwise comparison between observed and modeled convective parameters in terms of basic statistical metrics and climatological means on a daily and monthly basis. Both pressure and model level data from ERA5 are included in the analysis.&lt;/p&gt;&lt;p&gt;In line with previous research, the ERA5 model level dataset reasonably represents the climatological distribution of convection-related variables. Preliminary results suggest that the WRF regional climate model is also quite skillful in reproducing convective environments, but large biases exist compared to the observations and reanalysis.&lt;/p&gt;&lt;p&gt;The research was supported by the Hungarian National Research, Development and Innovation Office, Grant No. FK132014.&lt;/p&gt;

scholarly journals Multivariate bias adjustment of high-dimensional climate simulations: the Rank Resampling for Distributions and Dependences (R<sup>2</sup>D<sup>2</sup>) bias correction

2018 ◽  
Vol 22 (6) ◽  
pp. 3175-3196 ◽  
Author(s):  
Mathieu Vrac
Keyword(s):  
Bias Correction ◽  
Climate Model ◽  
Regional Climate ◽  
Grid Cell ◽  
Dependence Structure ◽  
Historical Period ◽  
Temporal Properties ◽  
Temperature And Precipitation ◽  
Climate Simulations ◽  
Site Dependence

Abstract. Climate simulations often suffer from statistical biases with respect to observations or reanalyses. It is therefore common to correct (or adjust) those simulations before using them as inputs into impact models. However, most bias correction (BC) methods are univariate and so do not account for the statistical dependences linking the different locations and/or physical variables of interest. In addition, they are often deterministic, and stochasticity is frequently needed to investigate climate uncertainty and to add constrained randomness to climate simulations that do not possess a realistic variability. This study presents a multivariate method of rank resampling for distributions and dependences (R2D2) bias correction allowing one to adjust not only the univariate distributions but also their inter-variable and inter-site dependence structures. Moreover, the proposed R2D2 method provides some stochasticity since it can generate as many multivariate corrected outputs as the number of statistical dimensions (i.e., number of grid cell  ×  number of climate variables) of the simulations to be corrected. It is based on an assumption of stability in time of the dependence structure – making it possible to deal with a high number of statistical dimensions – that lets the climate model drive the temporal properties and their changes in time. R2D2 is applied on temperature and precipitation reanalysis time series with respect to high-resolution reference data over the southeast of France (1506 grid cell). Bivariate, 1506-dimensional and 3012-dimensional versions of R2D2 are tested over a historical period and compared to a univariate BC. How the different BC methods behave in a climate change context is also illustrated with an application to regional climate simulations over the 2071–2100 period. The results indicate that the 1d-BC basically reproduces the climate model multivariate properties, 2d-R2D2 is only satisfying in the inter-variable context, 1506d-R2D2 strongly improves inter-site properties and 3012d-R2D2 is able to account for both. Applications of the proposed R2D2 method to various climate datasets are relevant for many impact studies. The perspectives of improvements are numerous, such as introducing stochasticity in the dependence itself, questioning its stability assumption, and accounting for temporal properties adjustment while including more physics in the adjustment procedures.

scholarly journals Dependence of Eemian Greenland temperature reconstructions on the ice sheet topography

2013 ◽  
Vol 9 (6) ◽  
pp. 6683-6732
Author(s):  
N. Merz ◽  
A. Born ◽  
C. C. Raible ◽  
H. Fischer ◽  
T. F. Stocker
Keyword(s):  
Energy Balance ◽  
Surface Energy ◽  
Large Scale ◽  
Surface Energy Balance ◽  
Climate Model ◽  
Surface Wind ◽  
Sensible Heat Flux ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Lapse Rate

Abstract. The influence of a reduced Greenland ice sheet (GrIS) on Greenland's surface climate during the Eemian interglacial is studied using a comprehensive climate model. We find a distinct impact of changes in the GrIS topography on Greenland's surface air temperatures (SAT) even when correcting for changes in surface elevation which influences SAT through the lapse rate effect. The resulting lapse rate corrected SAT anomalies are thermodynamically driven by changes in the local surface energy balance rather than dynamically caused through anomalous advection of warm/cold air masses. The large-scale circulation is indeed very stable among all sensitivity experiments and the NH flow pattern does not depend on Greenland's topography in the Eemian. In contrast, Greenland's surface energy balance is clearly influenced by changes in the GrIS topography and this impact is seasonally diverse. In winter, the variable reacting strongest to changes in the topography is the sensible heat flux (SHFLX). The reason is its dependence on surface winds, which themselves are controlled to a large extent by the shape of the GrIS. Hence, regions where a receding GrIS causes higher surface wind velocities also experience anomalous warming through SHFLX. Vice-versa, regions that become flat and ice-free are characterized by low wind speeds, low SHFLX and anomalous cold winter temperatures. In summer, we find surface warming induced by a decrease in surface albedo in deglaciated areas and regions which experience surface melting. The Eemian temperature records derived from Greenland proxies, thus, likely include a temperature signal arising from changes in the GrIS topography. For the NEEM ice core site, our model suggests that up to 3.2 °C of the annual mean Eemian warming can be attributed to these topography-related processes and hence is not necessarily linked to large-scale climate variations.

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.

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