scholarly journals A Statistical–Dynamical Methodology to Downscale Regional Climate Projections to Urban Scale

2020 ◽  
Vol 59 (6) ◽  
pp. 1109-1123 ◽  
Author(s):  
François DuchÊne ◽  
Bert Van Schaeybroeck ◽  
Steven Caluwaerts ◽  
Rozemien De Troch ◽  
Rafiq Hamdi ◽  
...  
Keyword(s):  
Land Surface ◽  
Climate Models ◽  
Dynamical Downscaling ◽  
Heat Waves ◽  
Regional Climate ◽  
Wave Number ◽  
Surface Model ◽  
Climate Projections ◽  
Short Period ◽  
The Impact

AbstractThe demand of city planners for quantitative information on the impact of climate change on the urban environment is increasing. However, such information is usually extracted from decadelong climate projections generated with global or regional climate models (RCMs). Because of their coarse resolution and unsuitable physical parameterization, however, their model output is not adequate to be used at city scale. A full dynamical downscaling to city level, on the other hand, is computationally too expensive for climatological time scales. A statistical–dynamical computationally inexpensive method is therefore proposed that approximates well the behavior of the full dynamical downscaling approach. The approach downscales RCM simulations using the combination of an RCM at high resolution (H-RES) and a land surface model (LSM). The method involves the setup of a database of urban signatures by running an H-RES RCM with and without urban parameterization for a relatively short period. Using an analog approach, these signatures are first selectively added to the long-term RCM data, which are then used as forcing for an LSM using an urban parameterization in a stand-alone mode. A comparison with a full dynamical downscaling approach is presented for the city of Brussels, Belgium, for 30 summers with the combined ALADIN–AROME model (ALARO-0) coupled to the Surface Externalisée model (SURFEX) as H-RES RCM and SURFEX as LSM. The average bias of the nocturnal urban heat island during heat waves is vanishingly small, and the RMSE is strongly reduced. Not only is the statistical–dynamical approach able to correct the heat-wave number and intensities, it can also improve intervariable correlations and multivariate and temporally correlated indices, such as Humidex.

scholarly journals An observation-constrained multi-physics WRF ensemble for simulating European mega heat waves

2015 ◽  
Vol 8 (7) ◽  
pp. 2285-2298 ◽  
Author(s):  
A. I. Stegehuis ◽  
R. Vautard ◽  
P. Ciais ◽  
A. J. Teuling ◽  
D. G. Miralles ◽  
...  
Keyword(s):  
Heat Wave ◽  
Land Surface ◽  
Western Europe ◽  
Climate Models ◽  
Climate Model ◽  
Heat Waves ◽  
Regional Climate ◽  
Shortwave Radiation ◽  
Cold Bias ◽  
The Impact

Abstract. Many climate models have difficulties in properly reproducing climate extremes, such as heat wave conditions. Here we use the Weather Research and Forecasting (WRF) regional climate model with a large combination of different atmospheric physics schemes, in combination with the NOAH land-surface scheme, with the goal of detecting the most sensitive physics and identifying those that appear most suitable for simulating the heat wave events of 2003 in western Europe and 2010 in Russia. In total, 55 out of 216 simulations combining different atmospheric physical schemes have a temperature bias smaller than 1 °C during the heat wave episodes, the majority of simulations showing a cold bias of on average 2–3 °C. Conversely, precipitation is mostly overestimated prior to heat waves, and shortwave radiation is slightly overestimated. Convection is found to be the most sensitive atmospheric physical process impacting simulated heat wave temperature across four different convection schemes in the simulation ensemble. Based on these comparisons, we design a reduced ensemble of five well performing and diverse scheme configurations, which may be used in the future to perform heat wave analysis and to investigate the impact of climate change during summer in Europe.

scholarly journals Exploring how groundwater buffers the influence of heatwaves on vegetation function during multi-year droughts

2021 ◽  
Vol 12 (3) ◽  
pp. 919-938
Author(s):  
Mengyuan Mu ◽  
Martin G. De Kauwe ◽  
Anna M. Ukkola ◽  
Andy J. Pitman ◽  
Weidong Guo ◽  
...  
Keyword(s):  
Land Surface ◽  
Forest Canopy ◽  
Climate Models ◽  
Root Zone ◽  
Stomatal Closure ◽  
Capillary Rise ◽  
Vapour Pressure Deficit ◽  
Global Climate Models ◽  
Surface Model ◽  
The Impact

Abstract. The co-occurrence of droughts and heatwaves can have significant impacts on many socioeconomic and environmental systems. Groundwater has the potential to moderate the impact of droughts and heatwaves by moistening the soil and enabling vegetation to maintain higher evaporation, thereby cooling the canopy. We use the Community Atmosphere Biosphere Land Exchange (CABLE) land surface model, coupled to a groundwater scheme, to examine how groundwater influences ecosystems under conditions of co-occurring droughts and heatwaves. We focus specifically on south-east Australia for the period 2000–2019, when two significant droughts and multiple extreme heatwave events occurred. We found groundwater plays an important role in helping vegetation maintain transpiration, particularly in the first 1–2 years of a multi-year drought. Groundwater impedes gravity-driven drainage and moistens the root zone via capillary rise. These mechanisms reduced forest canopy temperatures by up to 5 ∘C during individual heatwaves, particularly where the water table depth is shallow. The role of groundwater diminishes as the drought lengthens beyond 2 years and soil water reserves are depleted. Further, the lack of deep roots or stomatal closure caused by high vapour pressure deficit or high temperatures can reduce the additional transpiration induced by groundwater. The capacity of groundwater to moderate both water and heat stress on ecosystems during simultaneous droughts and heatwaves is not represented in most global climate models, suggesting that model projections may overestimate the risk of these events in the future.

scholarly journals Impact of humidity biases on light precipitation occurrence: observations versus simulations

2018 ◽  
Author(s):  
Sophie Bastin ◽  
Philippe Drobinski ◽  
Marjolaine Chiriaco ◽  
Olivier Bock ◽  
Romain Roehrig ◽  
...  
Keyword(s):  
Land Surface ◽  
Climate Models ◽  
Regional Climate ◽  
Strong Dependence ◽  
Mediterranean Area ◽  
Critical Value ◽  
Critical Values ◽  
Frequency Of Occurrence ◽  
The Impact ◽  
Light Precipitation

Abstract. This work uses a network of GPS stations over Europe from which a homogenised integrated water vapor (IWV) dataset has been retrieved, completed with colocated temperature and precipitation measurements over specific stations to i) estimate the biases of six regional climate models over Europe in terms of humidity; ii) understand their origins; iii) and finally assess the impact of these biases on the frequency of occurrence of precipitation. The evaluated simulations have been performed in the framework of HYMEX/Med-CORDEX programs and cover the Mediterranean area and part of Europe at horizontal resolutions of 50 to 12 km. The analysis shows that models tend to overestimate the low values of IWV and the use of the nudging technique reduces the differences between GPS and simulated IWV. Results suggest that physics of models mostly explain the mean biases, while dynamics affects the variability. The land surface/atmosphere exchanges affect the estimation of IWV over most part of Europe, especially in summer. The limitations of the models to represent these processes explain part of their baises in IWV. However, models correctly simulate the dependance between IWV and temperature, and specifically the deviation that this relationship experiences regarding the Clausius-Clapeyron law after a critical value of temperature (Tbreak). The high spatial variability of Tbreak indicates that it has a strong dependence on local processes which drive the local humidity sources. This explains why the maximum values of IWV are not necessarely observed over warmer area, that are often dry area. Finally, it is shown over SIRTA observatory (near Paris) that the frequency of occurrence of light precipitation is strongly conditioned by the biases in IWV and by the precision of the models to reproduce the distribution of IWV as a function of the temperature. The results of the models indicate that a similar dependence occurs in other areas of Europe, especially where precipitation has a predominantly convective character. According to the observations, for each range of temperature, there is a critical value of IWV from which precipitation picks up. The critical values and the probability to exceed them are simulated with a bias that depends on the model. Those models which present too often light precipitation generally show lower critical values and higher probability to exceed them.

scholarly journals 2-way coupling the hydrological land surface model PROMET with the regional climate model MM5

2013 ◽  
Vol 17 (5) ◽  
pp. 1705-1714 ◽  
Author(s):  
F. Zabel ◽  
W. Mauser
Keyword(s):  
Heat Flux ◽  
Land Surface ◽  
Regional Climate ◽  
Surface Processes ◽  
Surface Model ◽  
Land Surface Processes ◽  
Near Surface ◽  
Danube Catchment ◽  
Simulated Precipitation ◽  
The Impact

Abstract. Most land surface hydrological models (LSHMs) consider land surface processes (e.g. soil–plant–atmosphere interactions, lateral water flows, snow and ice) in a spatially detailed manner. The atmosphere is considered as exogenous driver, neglecting feedbacks between the land surface and the atmosphere. On the other hand, regional climate models (RCMs) generally simulate land surface processes through coarse descriptions and spatial scales but include land–atmosphere interactions. What is the impact of the differently applied model physics and spatial resolution of LSHMs on the performance of RCMs? What feedback effects are induced by different land surface models? This study analyses the impact of replacing the land surface module (LSM) within an RCM with a high resolution LSHM. A 2-way coupling approach was applied using the LSHM PROMET (1 × 1 km2) and the atmospheric part of the RCM MM5 (45 × 45 km2). The scaling interface SCALMET is used for down- and upscaling the linear and non-linear fluxes between the model scales. The change in the atmospheric response by MM5 using the LSHM is analysed, and its quality is compared to observations of temperature and precipitation for a 4 yr period from 1996 to 1999 for the Upper Danube catchment. By substituting the Noah-LSM with PROMET, simulated non-bias-corrected near-surface air temperature improves for annual, monthly and daily courses when compared to measurements from 277 meteorological weather stations within the Upper Danube catchment. The mean annual bias was improved from −0.85 to −0.13 K. In particular, the improved afternoon heating from May to September is caused by increased sensible heat flux and decreased latent heat flux as well as more incoming solar radiation in the fully coupled PROMET/MM5 in comparison to the NOAH/MM5 simulation. Triggered by the LSM replacement, precipitation overall is reduced; however simulated precipitation amounts are still of high uncertainty, both spatially and temporally. The distribution of precipitation follows the coarse topography representation in MM5, resulting in a spatial shift of maximum precipitation northwards of the Alps. Consequently, simulation of river runoff inherits precipitation biases from MM5. However, by comparing the water balance, the bias of annual average runoff was improved from 21.2% (NOAH/MM5) to 4.4% (PROMET/MM5) when compared to measurements at the outlet gauge of the Upper Danube watershed in Achleiten.

Intercomparison of terrestrial water budgets in EURO-CORDEX and TSMP evaluation runs

2020 ◽  
Author(s):  
Mohamed Eltahan ◽  
Klaus Goergen ◽  
Carina Furusho-Percot ◽  
Stefan Kollet
Keyword(s):  
Land Surface ◽  
Water Budget ◽  
Climate Models ◽  
Water Cycle ◽  
Weather Prediction ◽  
Regional Climate ◽  
Shallow Groundwater ◽  
Surface Model ◽  
Frequency Distributions ◽  
Terrestrial Water

<p>Water is one of Earth’s most important geo-ecosystem components. Here we present an evaluation of water cycle components using 12 EURO-CORDEX Regional Climate Models (RCMs) and the Terrestrial Systems Modeling Platform (TSMP) from ERA-Interim driven evaluation runs. Unlike the other RCMs, TSMP provides an <span>integrated</span> representation of the terrestrial water cycle by coupling the numerical weather prediction model COSMO, the land surface model CLM and the surface-subsurface hydrological model ParFlow, which simulates shallow groundwater states and fluxes. The study analyses precipitation (P), evapotranspiration (E), runoff (R), and terrestrial water storage (TWS=P-E-R) at a 0.11degree spatial resolution (about 12km) on EUR-11 CORDEX grid from 1996 to 2008. As reference datasets, we use ERA5 reanalysis to <span>represent</span> the complete terrestrial water budget, <span>as well as </span>the E-OBS, GLEAM and E-Run datasets for precipitation, evapotranspiration and runoff, respectively. The terrestrial water budget is investigated for twenty catchments over Europe (Guadalquivir, Guadiana, Tagus, Douro, Ebro, Garonne, Rhone, Po, Seine, Rhine, Loire, Maas, Weser, Elbe, Oder, Vistuala, Danube, Dniester, Dnieper, and Neman). Annual cycles, seasonal variations, empirical frequency distributions, spatial distributions for the water cycle components and budgets over the catchments are assessed. The analysis <span>demonstrates</span> the capability of the RCMs and TSMP to reproduce the overall <span>characteristics of the</span> water cycle over the EURO-CORDEX domain<span>, which is a prerequisite if, e.g., climate change projections with the CORDEX RCMs or TSMP are to be used for vulnerability, impacts, and adaptation studies.</span></p>

scholarly journals Assessment of the impacts of climate change on maize production in the Wami Ruvu basin of Tanzania

2016 ◽  
Vol 8 (1) ◽  
pp. 142-164 ◽  
Author(s):  
Philbert Luhunga ◽  
Ladslaus Chang'a ◽  
George Djolov
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Regional Climate ◽  
Climate Projections ◽  
Intergovernmental Panel ◽  
Lower Altitude ◽  
Rcp 8.5 ◽  
Maize Yields ◽  
The Impact ◽  
Impacts Of Climate Change

The IPCC (Intergovernmental Panel on Climate Change) assessment reports confirm that climate change will hit developing countries the hardest. Adaption is on the agenda of many countries around the world. However, before devising adaption strategies, it is crucial to assess and understand the impacts of climate change at regional and local scales. In this study, the impact of climate change on rain-fed maize (Zea mays) production in the Wami-Ruvu basin of Tanzania was evaluated using the Decision Support System for Agro-technological Transfer. The model was fed with daily minimum and maximum temperatures, rainfall and solar radiation for current climate conditions (1971–2000) as well as future climate projections (2010–2099) for two Representative Concentration Pathways: RCP 4.5 and RCP 8.5. These data were derived from three high-resolution regional climate models, used in the Coordinated Regional Climate Downscaling Experiment program. Results showed that due to climate change future maize yields over the Wami-Ruvu basin will slightly increase relative to the baseline during the current century under RCP 4.5 and RCP 8.5. However, maize yields will decline in the mid and end centuries. The spatial distribution showed that high decline in maize yields are projected over lower altitude regions due to projected increase in temperatures in those areas.

scholarly journals Evaluation of the impacts of climate variability on rainfed maize production over the Wami-Ruvu basin of Tanzania

2017 ◽  
Vol 9 (1) ◽  
pp. 207-222 ◽  
Author(s):  
Philbert Luhunga
Keyword(s):  
Climate Variability ◽  
Climate Models ◽  
Pearson Correlation ◽  
Regional Climate ◽  
Maximum Temperature ◽  
Climate Projections ◽  
Historical Climate ◽  
Climate Simulations ◽  
Maize Yields ◽  
The Impact

AbstractIn this study, the impact of inter-seasonal climate variability on rainfed maize (Zea mays) production over the Wami-Ruvu basin of Tanzania is evaluated. Daily high-resolution climate simulations from the Coordinated Regional Climate Downscaling Experiment_Regional Climate Models (CORDEX_RCMs) are used to drive the Decision Support System for Agro-technological Transfer (DSSAT) to simulate maize yields. Climate simulations for the base period of 35 years (1971–2005) are used to drive DSSAT to simulate maize yields during the historical climate. On the other hand, climate projections for the period 2010–2039 (current), 2040–2069 (mid), and 2070–2099 centuries for two Representative Concentration Pathway (RCP45 and 85) emission scenarios are used to drive DSSAT to simulate maize yields in respective centuries. Statistical approaches based on Pearson correlation coefficient and the coefficients of determination are used in the analysis. Results show that rainfall, maximum temperature, and solar radiation are the most important climate variables that determine variation in rainfed maize yields over the Wami-Ruvu basin of Tanzania. They explain the variability in maize yields in historical climate condition (1971–2005), present century under RCP 4.5, and mid and end centuries under both RCP 4.5 and RCP 8.5.

scholarly journals Streamflow data assimilation for soil moisture analysis

2010 ◽  
Vol 3 (1) ◽  
pp. 1-12 ◽  
Author(s):  
K. Warrach-Sagi ◽  
V. Wulfmeyer
Keyword(s):  
Soil Moisture ◽  
Data Assimilation ◽  
Land Surface ◽  
Climate Models ◽  
Root Zone ◽  
Weather Forecast ◽  
Surface Model ◽  
River Catchment ◽  
Streamflow Data ◽  
The Impact

Abstract. Streamflow depends on the soil moisture of a river catchment and can be measured with relatively high accuracy. The soil moisture in the root zone influences the latent heat flux and, hence, the quantity and spatial distribution of atmospheric water vapour and precipitation. As numerical weather forecast and climate models require a proper soil moisture initialization for their land surface models, we enhanced an Ensemble Kalman Filter to assimilate streamflow time series into the multi-layer land surface model TERRA-ML of the regional weather forecast model COSMO. The impact of streamflow assimilation was studied by an observing system simulation experiment in the Enz River catchment (located at the downwind side of the northern Black Forest in Germany). The results demonstrate a clear improvement of the soil moisture field in the catchment. We illustrate the potential of streamflow data assimilation for weather forecasting and discuss its spatial and temporal requirements for a corresponding, automated river gauging network.

Parametrizating Soil Surface Fluxes in the JULES Land Surface Model

2021 ◽  
Author(s):  
John Edwards
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Heat Waves ◽  
Numerical Models ◽  
Weather Prediction ◽  
Land Surface Model ◽  
Soil Surface ◽  
Current Status ◽  
Surface Model ◽  
The Impact

<p>The parametrization of land-atmosphere interactions in numerical weather prediction and climate models is a topic of active and growing interest, especially in connection with extreme events such as heat waves and droughts. Semiarid regions are sensitive to drought and are currently expanding, but they are often poorly represented in numerical models. On forecasting timescales, comparisons of simulated land surface temperature against retrievals from satellites often show significant cold biases around noon, whilst, on climate timescales, land surface models often fail to represent droughts realistically. Inadequate treatment of the land surface, and particularly of soil properties and soil moisture, is likely to contribute to such errors.</p> <p>Efforts to develop improved parametrizations of soil processes in the JULES land surface model for application in weather prediction and climate simulations are underway. Whilst processes at the soil surface are a central part of this, to obtain acceptable performance it is also important to consider the surface flux budget as a whole, including the treatment of the plant canopy. Here, we shall describe the current status of developments aimed at improving the representation of evapotranspiration and ground heat fluxes in the model, noting the major issues encountered. The importance of accurately representing the impact of soil moisture on thermal properties will be stressed. Results from initial studies will be presented and we shall offer a perspective on future developments.<br /><br /></p>

Increasing the depth of a Land Surface Model. Part II: Temperature sensitivity to improved subsurface thermodynamics and associated permafrost response

2021 ◽  
Author(s):  
N. J. Steinert ◽  
J. F. González-Rouco ◽  
P. de Vrese ◽  
E. García-Bustamante ◽  
S. Hagemann ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Root Zone ◽  
Land Surface Model ◽  
Phase Changes ◽  
Surface Model ◽  
Climate Projections ◽  
Stable States ◽  
Soil Parameter ◽  
The Impact

AbstractThe impact of various modifications of the JSBACH Land Surface Model to represent soil temperature and cold-region hydro-thermodynamic processes in climate projections of the 21st century is examined. We explore the sensitivity of JSBACH to changes in the soil thermodynamics, energy balance and storage, and the effect of including freezing and thawing processes. The changes involve 1) the net effect of an improved soil physical representation and 2) the sensitivity of our results to changed soil parameter values and their contribution to the simulation of soil temperatures and soil moisture, both aspects being presented in the frame of an increased bottom boundary depth from 9.83 m to 1418.84 m. The implementation of water phase changes and supercooled water in the ground creates a coupling between the soil thermal and hydrological regimes through latent heat exchange. Momentous effects on subsurface temperature of up to ±3 K, together with soil drying in the high northern latitudes, can be found at regional scales when applying improved hydro-thermodynamic soil physics. The sensitivity of the model to different soil parameter datasets occurs to be low but shows important implications for the root zone soil moisture content. The evolution of permafrost under pre-industrial forcing conditions emerges in simulated trajectories of stable states that differ by 4 – 6 • 106 km2 and shows large differences in the spatial extent of 105 –106 km2 by 2100, depending on the model configuration.

Sign in / Sign up

Export Citation Format

Share Document