Land Surface Scheme Research Articles

Quantifying the impacts of land surface schemes and dynamic vegetation on the model dependency of projected changes in surface energy and water budgets

AbstractAssessing and quantifying the uncertainties in projected future changes of energy and water budgets over land surface are important steps toward improving our confidence in climate change projections. In this study, the contribution of land surface models to the inter‐GCM variation of projected future changes in land surface energy and water fluxes are assessed based on output from 19 global climate models (GCMs) and offline Community Land Model version 4 (CLM4) simulations driven by meteorological forcing from the 19 GCMs. Similar offline simulations using CLM4 with its dynamic vegetation submodel are also conducted to investigate how dynamic vegetation feedback, a process that is being added to more earth system models, may amplify or moderate the intermodel variations of projected future changes. Projected changes are quantified as the difference between the 2081–2100 period from the Representative Concentration Pathway 8.5 (RCP8.5) future experiment and the 1981–2000 period from the historical simulation. Under RCP8.5, projected changes in surface water and heat fluxes show a high degree of model dependency across the globe. Although precipitation is very likely to increase in the high latitudes of the Northern Hemisphere, a high degree of model‐related uncertainty exists for evapotranspiration, soil water content, and surface runoff, suggesting discrepancy among land surface models (LSMs) in simulating the surface hydrological processes and snow‐related processes. Large model‐related uncertainties for the surface water budget also exist in the Tropics including southeastern South America and Central Africa. These uncertainties would be reduced in the hypothetical scenario of a single near‐perfect land surface model being used across all GCMs, suggesting the potential to reduce uncertainties through the use of more consistent approaches toward land surface model development. Under such a scenario, the most significant reduction is likely to be seen in the Northern Hemisphere high latitudes. Including representation of vegetation dynamics is expected to further amplify the model‐related uncertainties in projected future changes in surface water and heat fluxes as well as soil moisture content. This is especially the case in the high latitudes of the Northern Hemisphere (e.g., northwestern North America and central North Asia) where the projected vegetation changes are uncertain and in the Tropics (e.g., the Amazon and Congo Basins) where dense vegetation exists. Findings from this study highlight the importance of improving land surface model parameterizations related to soil and snow processes, as well as the importance of improving the accuracy of dynamic vegetation models.

The sensitivity of simulated competition between different plant functional types to subgrid‐scale representation of vegetation in a land surface model

AbstractThe Canadian Land Surface Scheme coupled to the Canadian Terrestrial Ecosystem Model is used to simulate competition between the model's seven non‐crop plant functional types (PFTs) for available space. Our objective is to assess if the model is successfully able to reproduce the observed mix of PFTs and their fractional coverages and to what extent the simulated competition is affected by the manner in which the subgrid‐scale variability of vegetation is represented. The model can be run either in a composite (single tile) configuration, where structural vegetation attributes of PFTs are aggregated for use in grid‐averaged energy and water balance calculations, or a mosaic (multiple tiles) configuration, where separate energy and water balance calculations are performed for each PFT. The model realistically simulates the fractional coverages of trees, grasses, and bare ground, as well as that of individual tree and grass PFTs and their succession patterns. Our results show that the model is not overly sensitive to the manner in which subgrid‐scale variability of vegetation is represented. Of the seven sites chosen across the globe to illustrate the difference between the two configurations, the simulated fractional coverage of PFTs are generally very similar (root‐mean‐square difference, RMSD, < 5%) between the composite and mosaic configurations at locations characterized by low heterogeneity (e.g., Amazonia, Vancouver Island, and the Tibetan Plateau), whereas at locations characterized by high heterogeneity (e.g., India, South Sudan and California), the two configurations yield somewhat different results (RMSD > 5%).

Effects of Land Surface Schemes on WRF-Simulated Geopotential Heights over China in Summer 2003*

Abstract To quantify and explain effects of different land surface schemes (LSSs) on simulated geopotential height (GPH) fields, we performed simulations over China for the summer of 2003 using 12-member ensembles with the Weather Research and Forecasting (WRF) Model, version 3. The results show that while the model can generally simulate the seasonal and monthly mean GPH patterns, the effects of the LSS choice on simulated GPH fields are substantial, with the LSS-induced differences exceeding 10 gpm over a large area (especially the northwest) of China, which is very large compared with climate anomalies and forecast errors. In terms of the assessment measures for the four LSS ensembles [namely, the five-layer thermal diffusion scheme (SLAB), the Noah LSS (NOAH), the Rapid Update Cycle LSS (RUC), and the Pleim–Xiu LSS (PLEX)] in the WRF, the PLEX ensemble is the best, followed by the NOAH, RUC, and SLAB ensembles. The sensitivity of the simulated 850-hPa GPH is more significant than that of the 500-hPa GPH, with the 500-hPa GPH difference fields generally characterized by two large areas with opposite signs due to the smoothly varying nature of GPHs. LSS-induced GPH sensitivity is found to be higher than the GPH sensitivity induced by atmospheric boundary layer schemes. Moreover, theoretical analyses show that the LSS-induced GPH sensitivity is mainly caused by changes in surface fluxes (in particular, sensible heat flux), which further modify atmospheric temperature and pressure fields. The temperature and pressure fields generally have opposite contributions to changes in the GPH. This study emphasizes the importance of choosing and improving LSSs for simulating seasonal and monthly GPHs using regional climate models.

Glacial–interglacial changes in H<sub>2</sub><sup>18</sup>O, HDO and deuterium excess – results from the fully coupled ECHAM5/MPI-OM Earth system model

Abstract. In this study we present the first results of a new isotope-enabled general circulation model set-up. The model consists of the fully coupled ECHAM5/MPI-OM atmosphere–ocean model, enhanced by the JSBACH interactive land surface scheme and an explicit hydrological discharge scheme to close the global water budget. Stable water isotopes H218O and HDO have been incorporated into all relevant model components. Results of two equilibrium simulations under pre-industrial and Last Glacial Maximum conditions are analysed and compared to observational data and paleoclimate records for evaluating the model's performance in simulating spatial and temporal variations in the isotopic composition of the Earth's water cycle. For the pre-industrial climate, many aspects of the simulation results of meteoric waters are in good to very good agreement with both observations and earlier atmosphere-only simulations. The model is capable of adequately simulating the large spread in the isotopic composition of precipitation between low and high latitudes. A comparison to available ocean data also shows a good model–data agreement; however, a strong bias of overly depleted ocean surface waters is detected for the Arctic region. Simulation results under Last Glacial Maximum boundary conditions also fit to the wealth of available isotope records from polar ice cores, speleothems, as well as marine calcite data. Data–model evaluation of the isotopic composition in precipitation reveals a good match of the model results and indicates that the temporal glacial–interglacial isotope–temperature relation was substantially lower than the present spatial gradient for most mid- to high-latitudinal regions. As compared to older atmosphere-only simulations, a remarkable improvement is achieved for the modelling of the deuterium excess signal in Antarctic ice cores. Our simulation results indicate that cool sub-tropical and mid-latitudinal sea surface temperatures are key for this progress. A recently discussed revised interpretation of the deuterium excess record of Antarctic ice cores in terms of marine relative humidity changes on glacial–interglacial timescales is not supported by our model results.

Simulating the thermal regime and thaw processes of ice-rich permafrost ground with the land-surface model CryoGrid 3

Abstract. Thawing of permafrost in a warming climate is governed by a complex interplay of different processes of which only conductive heat transfer is taken into account in most model studies. However, observations in many permafrost landscapes demonstrate that lateral and vertical movement of water can have a pronounced influence on the thaw trajectories, creating distinct landforms, such as thermokarst ponds and lakes, even in areas where permafrost is otherwise thermally stable. Novel process parameterizations are required to include such phenomena in future projections of permafrost thaw and subsequent climatic-triggered feedbacks. In this study, we present a new land-surface scheme designed for permafrost applications, CryoGrid 3, which constitutes a flexible platform to explore new parameterizations for a range of permafrost processes. We document the model physics and employed parameterizations for the basis module CryoGrid 3, and compare model results with in situ observations of surface energy balance, surface temperatures, and ground thermal regime from the Samoylov permafrost observatory in NE Siberia. The comparison suggests that CryoGrid 3 can not only model the evolution of the ground thermal regime in the last decade, but also consistently reproduce the chain of energy transfer processes from the atmosphere to the ground. In addition, we demonstrate a simple 1-D parameterization for thaw processes in permafrost areas rich in ground ice, which can phenomenologically reproduce both formation of thermokarst ponds and subsidence of the ground following thawing of ice-rich subsurface layers. Long-term simulation from 1901 to 2100 driven by reanalysis data and climate model output demonstrate that the hydrological regime can both accelerate and delay permafrost thawing. If meltwater from thawed ice-rich layers can drain, the ground subsides, as well as the formation of a talik, are delayed. If the meltwater pools at the surface, a pond is formed that enhances heat transfer in the ground and leads to the formation of a talik. The model results suggest that the trajectories of future permafrost thaw are strongly influenced by the cryostratigraphy, as determined by the late Quaternary history of a site.

Retrieval of Land Surface Model State Variables through Assimilating Screen Level Humidity and Temperature Measurements

This study demonstrates successful variational retrieval of land surface states by assimilating screen level atmospheric measurements of specific humidity and air temperature. To this end, the land surface scheme is first validated against the Oklahoma Atmospheric Surface Layer Instrumentation System measurements with necessary refinements to the forward model implemented. The retrieval scheme involves a 1D land surface-atmosphere model, the corresponding adjoint codes, and a cost function that measures residuals between observed and modeled screen level atmospheric temperature and specific humidity. The retrieval scheme is robust when subjected to observational errors with magnitudes comparable to instrument accuracy and for initial guess errors larger than typical model forecast errors. Using varying assimilation window lengths centered on different periods of a day, the sampling strategy is assessed. The daytime observations are more informative compared to nocturnal observations. An assimilation window as narrow as four hours, if centered on local noon, contains comparable information to an expanded window covering the whole day. There exists an optimal assimilation window length resulting from the contest between degrading forecast accuracy and increasing information content. For an assimilation window less than two days, the “optimal” assimilation window length is inversely proportional to the data ingesting frequency.

Assessing the influence of groundwater and land surface scheme in the modelling of land surface–atmosphere feedbacks over the FIFE area in Kansas, USA

The land surface–atmosphere interaction is described differently in large-scale surface schemes of regional climate models and small-scale spatially distributed hydrological models. In particular, the hydrological models include the influence of shallow groundwater on evapotranspiration during dry periods where soils are depleted and groundwater is the only water supply. These mechanisms are analysed by combining a distributed hydrological model (MIKE SHE) and a regional climate model (HIRHAM) and comparing simulation results to the FIFE area observation data in Kansas, USA. The numerical experiments include five simulations. First MIKE SHE is forced by observed climate data in two versions (1) with groundwater at a fixed uniform depth, and (2) with a dynamical groundwater component simulating shallow groundwater conditions in river valleys. (3) In a third simulation, MIKE SHE is forced by HIRHAM-simulated precipitation. The last two simulations include (4) a standard HIRHAM simulation, and (5) a fully coupled HIRHAM-MIKE SHE simulation locally replacing the land surface scheme by MIKE SHE for the FIFE area, while HIRHAM in standard configuration is used for the remaining model area. The results show a clear correlation between depth to the groundwater and evapotranspiration with a distinct groundwater depth threshold at 0.5–3 m. During the dry summer period, the two MIKE SHE simulations using distributed groundwater reproduced evapotranspiration better than MIKE SHE with unsaturated flow alone and the HIRHAM simulations. This indicates that including dynamic groundwater in a fully coupled climate-hydrology model may improve evapotranspiration fluxes from areas with shallow groundwater tables.

Impacts of the Sahel-Sahara Interface Reforestation on West African Climate: Intraseasonal Variability and Extreme Precipitation Events

This study aims to evaluate the impacts of the Sahel-Sahara interface reforestation on spatiotemporal variability of the summer rainfall and extreme precipitation events over West Africa using the RegCM4 model. The land surface scheme of RegCM4 was modified to incorporate an East-West reforested zone (15°N and 20°N). Two runs were performed using the standard version of RegCM4 and the modified one of the same model taking into account the incorporated forest. The reforestation significantly modifies rainfall signal over West Africa by increasing it over the reforested zone and the Fouta Jallon highlands (FJH). This rainfall increase is associated with a strengthening of the atmospheric moisture over the reforested area. This atmospheric moisture content increase associated with the wind dynamic may explain the spatiotemporal change of the rainfall and extreme precipitation events. The analysis of the impacts of the reforestation on some rainfall indices shows an increase of the 90th, 95th, and 99th percentiles over the reforested zone and off the FJH. This reforestation also causes an increase of the maximum length of the consecutive wet days over and off FJH and a decrease of the maximum length of the consecutive dry days over the northern Sahel and the reforested zone.

A new framework for comprehensive, robust, and efficient global sensitivity analysis: 2. Application

AbstractBased on the theoretical framework for sensitivity analysis called “Variogram Analysis of Response Surfaces” (VARS), developed in the companion paper, we develop and implement a practical “star‐based” sampling strategy (called STAR‐VARS), for the application of VARS to real‐world problems. We also develop a bootstrap approach to provide confidence level estimates for the VARS sensitivity metrics and to evaluate the reliability of inferred factor rankings. The effectiveness, efficiency, and robustness of STAR‐VARS are demonstrated via two real‐data hydrological case studies (a 5‐parameter conceptual rainfall‐runoff model and a 45‐parameter land surface scheme hydrology model), and a comparison with the “derivative‐based” Morris and “variance‐based” Sobol approaches are provided. Our results show that STAR‐VARS provides reliable and stable assessments of “global” sensitivity across the full range of scales in the factor space, while being 1–2 orders of magnitude more efficient than the Morris or Sobol approaches.

High-resolution simulation of heatwave events in New York City

Heatwave intensity and frequency are predicted to increase in the coming years, and this will bear adverse consequences to the environmental well-being and the socio-economic fabric in urbanized areas. The hazardous combination of increased heat storage and reduced water retention capacities of the land surface make the urban areas warmer than the surrounding rural areas in what is commonly known as the urban heat island (UHI) effect. The primary motives of this study are to quantify the interaction of this city-scale UHI with synoptic-scale heatwave episodes and to analyze the factors that mediate this interaction. A modified version of the Weather Research and Forecasting model (WRF) is utilized to simulate two heatwave episodes in New York City. The land surface scheme in the default WRF model is modified to better represent the surface to atmosphere exchanges over urban areas. Our results indicate that during the heatwave episodes, the daily-averaged UHI in NYC increased by 1.5 K. Furthermore, most of this amplification occurs in the mid-afternoon period when the temperatures peak. Wind direction and urban-rural contrasts in available energy and moisture availability are found to have significant and systematic effects on the UHI, but wind speed plays a secondary role.

Evaluating the impacts of climate variability and cutting and insect defoliation on the historical carbon dynamics of a boreal black spruce forest landscape in eastern Canada

In this study, the Carbon and Nitrogen coupled Canadian Land Surface Scheme (CN-CLASS) was used to investigate the impact of climate variability, seasonal weather effects, disturbance, and CO2 fertilization effects on the historical carbon (C) dynamics of an eastern Canadian boreal forest landscape (6275ha) from 1928 to 2008. The model was parameterized with ecological, soil texture, forest inventory and historical disturbance data and driven by hourly meteorological data constructed from the historical climate records. Before performing the landscape-level simulation, model results were evaluated against site-level eddy covariance (EC) measurements. Landscape-level simulated C fluxes showed that the forest ecosystem was a small C sink in all of the years prior to cutting and insect defoliation in 1963, which resulted in the removal of 23849Mg C from the forest landscape. As a consequence, the study area was a large C source in 1963 (net biome productivity, NBP=−537gCm−2yr−1). After that, the forest landscape was mainly a net annual C sink, with total ecosystem C stocks increasing from 14.8 to 16.0kgCm−2 by 2008, during which total biomass increased from 3.1 to 4.2kgCm−2. Analysis of landscape-level, age-detrended, simulated C fluxes for the undisturbed forest landscape from 1928 to 2002 indicated that summer temperature was the dominant control on C fluxes with higher temperature causing a much faster increase in landscape-level annual Re than that of GPP (i.e. 12.3 vs. 1.3gCm−2yr−1°C−1, respectively). Scenario analysis suggested that forest disturbances had a less profound impact on landscape-level C fluxes and stocks compared to inter-annual climate variability in this landscape. Climate sensitivity analysis revealed that landscape-level simulated C fluxes and stocks were sensitive to the change of air temperature, while only dead organic matter (DOM) and soil organic matter (SOM) were sensitive to the change of precipitation. This study will help to explore the impact of future climate change scenarios and forest management on boreal forest landscapes.

Climate response to Amazon forest replacement by heterogeneous crop cover

Abstract. Previous modeling studies with atmospheric general circulation models and basic land surface schemes to balance energy and water budgets have shown that by removing the natural vegetation over the Amazon, the region's climate becomes warmer and drier. In this study we use a fully coupled Earth system model and replace tropical forests by a distribution of six common tropical crops with variable planting dates, physiological parameters and irrigation. There is still general agreement with previous studies as areal averages show a warmer (+1.4 K) and drier (−0.35 mm day−1) climate. Using an interactive crop model with a realistic crop distribution shows that regions of vegetation change experience different responses dependent upon the initial tree coverage and whether the replacement vegetation is irrigated, with seasonal changes synchronized to the cropping season. Areas with initial tree coverage greater than 80 % show an increase in coupling with the atmosphere after deforestation, suggesting land use change could heighten sensitivity to climate anomalies, while irrigation acts to dampen coupling with the atmosphere.

Evaluating stomatal models and their atmospheric drought response in a land surface scheme: A multibiome analysis

AbstractStomatal conductance (gs) is a key variable in Earth system models as it regulates the transfer of carbon and water between the terrestrial biosphere and the lower atmosphere. Various approaches have been developed that aim for a simple representation of stomatal regulation applicable at the global scale. These models differ, among others, in their response to atmospheric humidity, which induces stomatal closure in a dry atmosphere. In this study, we compared the widely used empirical Ball‐Berry and Leuning stomatal conductance models to an alternative empirical approach, an optimization‐based approach, and a semimechanistic hydraulic model. We evaluated these models using evapotranspiration (ET) and gross primary productivity (GPP) observations derived from eddy covariance measurements at 56 sites across multiple biomes and climatic conditions. The different models were embedded in the land surface model JSBACH. Differences in performance across plant functional types or climatic conditions were small, partly owing to the large variations in the observational data. The models yielded comparable results at low to moderate atmospheric drought but diverged under dry atmospheric conditions, where models with a low sensitivity to air humidity tended to overestimate gs. The Ball‐Berry model gave the best fit to the data for most biomes and climatic conditions, but all evaluated approaches have proven adequate for use in land surface models. Our findings further encourage future efforts toward a vegetation‐type‐specific parameterization of gs to improve the modeling of coupled terrestrial carbon and water dynamics.

Sensitivity of the mean and variability of Indian summer monsoon to land surface schemes in RegCM4: Understanding coupled land‐atmosphere feedbacks

AbstractA relatively simple land surface model, the Biosphere‐Atmosphere Transfer Scheme (BATS) and the more complex Community Land Model (CLM3.5) coupled to RegCM4 are used to investigate land‐atmosphere feedback processes during the Indian summer monsoon. Model simulations for 27 years show that the mean and interannual variability of rainfall and surface air temperature are affected significantly due to differences in the formulation of evapotranspiration and hydrological processes between BATS and CLM3.5, prescribed land use, land cover data and changes in net radiation. RegCM4 with CLM3.5 (RCLM) shows a reduction in surface moisture flux and precipitation but an increase in surface air temperature over most parts of India as compared to RegCM4 with BATS (RBAT). In terms of the mean and interannual variability of rainfall over central India, RBAT performs better than RCLM. Evapotranspiration over central India is found to be less (more) sensitive to soil wetness variations in RCLM (RBAT) compared to the multimodel estimate from the Global Soil Wetness Project, that is mainly attributed to the differences in ground evaporation and transpiration. Changes in evaporation efficiency between the models also lead to a reduction in the land‐atmosphere coupling strength for precipitation in RCLM. Furthermore, such changes decrease the convective instability over central and eastern India in RCLM leading to weakened convection, reduced large‐scale moisture convergence and precipitation over land. Observations of soil moisture, surface fluxes, and radiation are needed for better understanding and improvement of coupled land‐atmosphere feedbacks in models during the Indian summer monsoon.

Customization of regional climate model (RegCM4) over Indian region

The regional climate model (RegCM4) is customized for 10-year climate simulation over Indian region through sensitivity studies on cumulus convection and land surface parameterization schemes. The model is configured over 30° E–120° E and 15° S–45° N at 30-km horizontal resolution with 23 vertical levels. Six 10-year (1991–2000) simulations are conducted with the combinations of two land surface schemes (BATS, CLM3.5) and three cumulus convection schemes (Kuo, Grell, MIT). The simulated annual and seasonal climatology of surface temperature and precipitation are compared with CRU observations. The interannual variability of these two parameters is also analyzed. The results indicate that the model simulated climatology is sensitive to the convection as well as land surface parameterization. The analysis of surface temperature (precipitation) climatology indicates that the model with CLM produces warmer (dryer) climatology, particularly over India. The warmer (dryer) climatology is due to the higher sensible heat flux (lower evapotranspiration) in CLM. The model with MIT convection scheme simulated wetter and warmer climatology (higher precipitation and temperature) with smaller Bowen ratio over southern India compared to that with the Grell and Kuo schemes. This indicates that a land surface scheme produces warmer but drier climatology with sensible heating contributing to warming where as a convection scheme warmer but wetter climatology with latent heat contributing to warming. The climatology of surface temperature over India is better simulated by the model with BATS land surface model in combination with MIT convection scheme while the precipitation climatology is better simulated with BATS land surface model in combination with Grell convection scheme. Overall, the modeling system with the combination of Grell convection and BATS land surface scheme provides better climate simulation over the Indian region.

The reliability of single precision computations in the simulation of deep soil heat diffusion in a land surface model

Climate models need discretized numerical algorithms and finite precision arithmetic to solve their differential equations. Most efforts to date have focused on reducing truncation errors due to discretization effects, whereas rounding errors due to the use of floating-point arithmetic have received little attention. However, there are increasing concerns about more frequent occurrences of rounding errors in larger parallel computing platforms (due to the conflicting needs of stability and accuracy vs. performance), and while this has not been the norm in climate and forecast models using double precision, this could change with some models that are now compiled with single precision, which raises questions about the validity of using such low precision in climate applications. For example, processes occurring over large time scales such as permafrost thawing are potentially more vulnerable to this issue. In this study we analyze the theoretical and experimental effects of using single and double precision on simulated deep soil temperature from the Canadian LAnd Surface Scheme (CLASS), a state-of-the-art land surface model. We found that reliable single precision temperatures are limited to depths of less than about 20–25 m while double precision shows no loss of accuracy to depths of at least several hundred meters. We also found that, for a given precision level, model accuracy deteriorates when using smaller time steps, further reducing the usefulness of single precision. There is thus a clear danger of using single precision in some climate model applications, in particular any scientifically meaningful study of deep soil permafrost must at least use double precision. In addition, climate modelling teams might well benefit from paying more attention to numerical precision and roundoff issues to offset the potentially more frequent numerical anomalies in future large-scale parallel climate applications.

On improving cold region hydrological processes in the Canadian Land Surface Scheme

Regional and global climate model simulated streamflows for high-latitude regions show systematic biases, particularly in the timing and magnitude of spring peak flows. Though these biases could be related to the snow water equivalent and spring temperature biases in models, a good part of these biases is due to the unaccounted effects of non-uniform infiltration capacity of the frozen ground and other related processes. In this paper, the treatment of frozen water in the Canadian Land Surface Scheme (CLASS), which is used in the Canadian regional and global climate models, is modified to include fractional permeable area, supercooled liquid water and a new formulation for hydraulic conductivity. The impact of these modifications on the regional hydrology, particularly streamflow, is assessed by comparing three simulations performed with the original and two modified versions of CLASS, driven by atmospheric forcing data from the European Centre for Medium-Range Weather Forecast (ECMWF) reanalysis (ERA-Interim) for the 1990–2001 period over a northeast Canadian domain. The two modified versions of CLASS differ in the soil hydraulic conductivity and matric potential formulations, with one version being based on formulations from a previous study and the other one is newly proposed. Results suggest statistically significant decreases in infiltration and therefore soil moisture during the snowmelt season for the simulation with the new hydraulic conductivity and matric potential formulations and fractional permeable area concept compared to the original version of CLASS, which is also reflected in the increased spring surface runoff and streamflows in this simulation with modified CLASS over most of the study domain. The simulated spring peaks and their timing in this simulation are also in better agreement to those observed. This study thus demonstrates the importance of treatment of frozen water for realistic simulation of streamflows.

WRF‐simulated sensitivity to land surface schemes in short and medium ranges for a high‐temperature event in East China: A comparative study

AbstractWe designed simulations for the high‐temperature event that occurred on 23 July 2003 in East China using a series of forecast lead times, from short‐range to medium‐range, and four land surface schemes (LSSs) (i.e., SLAB, NOAH, RUC, and PX) in the Weather Research and Forecasting Model (WRF), Version 3. The sensitivities of short and medium‐range simulations to the LSSs systematically varied with the lead times. In general, the model reproduced short‐range, high‐temperature distributions. The simulated weather was sensitive to the LSSs, and the LSS‐induced sensitivity was higher in the medium range than in the short‐range. Furthermore, the LSS performances were complex, i.e., the PX errors apparently increased in the medium range (longer than 6 days), RUC produced the maximum errors, and SLAB and NOAH had approximately equivalent errors that slightly increased. Additional sensitivity simulations revealed that the WRF modeling system assigns relatively low initial soil moisture for RUC and that soil moisture initialization plays an important role that is comparable to the LSS choice in the simulations. LSS‐induced negative feedback between surface air temperature (SAT) and atmospheric circulation in the lower atmosphere was found in the medium range. These sensitivities were mainly caused by the LSS‐induced differences in surface sensible heat flux and by errors associated with the lead times. Using the SAT equation, further diagnostic analyses revealed LSS deficiencies in simulating surface fluxes and physical processes that modify the SAT and indicated the main reasons for these deficiencies. These results have implications for model improvement and application.

Impact of model developments on present and future simulations of permafrost in a global land-surface model

Abstract. There is a large amount of organic carbon stored in permafrost in the northern high latitudes, which may become vulnerable to microbial decomposition under future climate warming. In order to estimate this potential carbon–climate feedback it is necessary to correctly simulate the physical dynamics of permafrost within global Earth system models (ESMs) and to determine the rate at which it will thaw. Additional new processes within JULES, the land-surface scheme of the UK ESM (UKESM), include a representation of organic soils, moss and bedrock and a modification to the snow scheme; the sensitivity of permafrost to these new developments is investigated in this study. The impact of a higher vertical soil resolution and deeper soil column is also considered. Evaluation against a large group of sites shows the annual cycle of soil temperatures is approximately 25 % too large in the standard JULES version, but this error is corrected by the model improvements, in particular by deeper soil, organic soils, moss and the modified snow scheme. A comparison with active layer monitoring sites shows that the active layer is on average just over 1 m too deep in the standard model version, and this bias is reduced by 70 cm in the improved version. Increasing the soil vertical resolution allows the full range of active layer depths to be simulated; by contrast, with a poorly resolved soil at least 50 % of the permafrost area has a maximum thaw depth at the centre of the bottom soil layer. Thus all the model modifications are seen to improve the permafrost simulations. Historical permafrost area corresponds fairly well to observations in all simulations, covering an area between 14 and 19 million km2. Simulations under two future climate scenarios show a reduced sensitivity of permafrost degradation to temperature, with the near-surface permafrost loss per degree of warming reduced from 1.5 million km2 °C−1 in the standard version of JULES to between 1.1 and 1.2 million km2 °C−1 in the new model version. However, the near-surface permafrost area is still projected to approximately half by the end of the 21st century under the RCP8.5 scenario.

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

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.