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A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Atmospheric Techniques, Instruments, and Modeling".

Deadline for manuscript submissions: closed (10 December 2021) | Viewed by 38251

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Special Issue Editor

Dr. Souhail Boussetta

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Guest Editor

European Centre for Medium-Range Weather Forecasts (ECMWF), Reading RG2 9AX, UK
Interests: land surface processes; land–atmosphere interaction; seamless land surface modelling; kilometric-scale land surface modelling

Special Issue Information

Dear Colleagues,

Land surface processes aim to describe the behaviour of global energy, water and carbon cycle from the surface components to enhance our capacity to monitor and predict the natural resources and their evolution in time. These processes are essential parts of numerical weather prediction and climate models. More realistic descriptions of processes and their interactions with the atmosphere is at the heart of research efforts to improve weather and climate forecasts. This Special Issue will include, but is not limited to, the following topics:

Process understanding and interaction of the surface conditions (soil moisture, land surface temperature, snow, phenology etc.) with the atmosphere
Representing anthropogenic effects (irrigation, crop modelling, land-use change etc.) in land surface models
High-resolution land surface modelling for improved global application (extreme events, CO2 monitoring etc.)
Evaluation and benchmarking of land surface model components

Dr. Souhail Boussetta
Guest Editor

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Keywords

Land surface modelling
Land–atmosphere interaction
Anthropogenic impact
Land surface benchmarking
Kilometric-scale modelling

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Published Papers (9 papers)

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Research

24 pages, 3759 KiB

Open AccessArticle

Hydrological Impact of the New ECMWF Multi-Layer Snow Scheme

by Ervin Zsoter, Gabriele Arduini, Christel Prudhomme, Elisabeth Stephens and Hannah Cloke

Atmosphere 2022, 13(5), 727; https://doi.org/10.3390/atmos13050727 - 2 May 2022

Cited by 7 | Viewed by 2339

Abstract

The representation of snow is a crucial aspect of land-surface modelling, as it has a strong influence on energy and water balances. Snow schemes with multiple layers have been shown to better describe the snowpack evolution and bring improvements to soil freezing and some hydrological processes. In this paper, the wider hydrological impact of the multi-layer snow scheme, implemented in the ECLand model, was analyzed globally on hundreds of catchments. ERA5-forced reanalysis simulations of ECLand were coupled to CaMa-Flood, as the hydrodynamic model to produce river discharge. Different sensitivity experiments were conducted to evaluate the impact of the ECLand snow and soil freezing scheme changes on the terrestrial hydrological processes, with particular focus on permafrost. It was found that the default multi-layer snow scheme can generally improve the river discharge simulation, with the exception of permafrost catchments, where snowmelt-driven floods are largely underestimated, due to the lack of surface runoff. It was also found that appropriate changes in the snow vertical discretization, destructive metamorphism, snow-soil thermal conductivity and soil freeze temperature could lead to large river discharge improvements in permafrost by adjusting the evolution of soil temperature, infiltration and the partitioning between surface and subsurface runoff. Full article

(This article belongs to the Special Issue Representation of Land Surface Processes in Weather and Climate Models)

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17 pages, 5871 KiB

Open AccessArticle

Projections of Future Drought by CMIP5 Multimodel Ensembles in Central Asia

by Zhijie Ta, Kaiyu Li, Yang Yu and Meilin Yang

Atmosphere 2022, 13(2), 232; https://doi.org/10.3390/atmos13020232 - 29 Jan 2022

Cited by 5 | Viewed by 2591

Abstract

Future changes in drought characteristics in Central Asia are projected at the regional scale using 21 climate models from phase 5 of the Coupled Model Intercomparison Project (CMIP5). Based on the standardized precipitation index (SPI) and standardized precipitation evapotranspiration index (SPEI), drought characteristics were characterized by drought frequency at 1-, 3-, and 12-month timescales. The drought duration was analyzed based on SPI1 and SPEI1. Drought indices were calculated by the multimodel ensemble (MME) from 21 CMIP5 models. The varimax rotation method was used to identify drought conditions for the entire area and seven drought subregions. In general, the projection results of future drought in Central Asia are related to the choice of drought index, and SPI and SPEI show different results. The drought frequency based on SPEI1, SPEI3, and SPEI12 showed an increasing trend in the future periods, that is, the drought frequency based on monthly, seasonal, and annual timescales will show an increase trend in the future periods. However, for SPI1, SPI3, and SPI12, the drought frequency will decrease in the future. SPI projected that the duration of drought will decrease in the future, while SPEI mainly showed an increasing trend. The results of the study should be of sufficient concern to policymakers to avoid land degradation, crop loss, water resource deficit, and economic loss. Full article

(This article belongs to the Special Issue Representation of Land Surface Processes in Weather and Climate Models)

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35 pages, 34413 KiB

Open AccessArticle

Influence of Planetary Boundary Layer (PBL) Parameterizations in the Weather Research and Forecasting (WRF) Model on the Retrieval of Surface Meteorological Variables over the Kenyan Highlands

by Sammy M. Njuki, Chris M. Mannaerts and Zhongbo Su

Atmosphere 2022, 13(2), 169; https://doi.org/10.3390/atmos13020169 - 20 Jan 2022

Cited by 11 | Viewed by 4391

Abstract

Regional climate models (RCMs) are crucial for climate studies and may be an alternative source of meteorological data in data-scarce regions. However, the effectiveness of the numerical weather prediction (NWP) models applied in RCMs is hampered by the parameterization of unresolved physical processes in the model. A major source of uncertainties in NWP models is the parameterization of the planetary boundary layer (PBL). This study evaluates the influence of seven PBL parameterization schemes in the Weather Research and Forecasting (WRF) model on the retrieval of four meteorological variables over the Kenyan highlands. The seven PBL schemes consist of four local schemes: the Mellor-Yamada-Janjic (MYJ), Mellor-Yamada-Nakanishi-Niino (MYNN), Bougeault-Lacarrere (BouLac), quasinormal scale elimination (QNSE), and three nonlocal schemes: asymmetrical convective model version 2 (ACM2), Shin and Hong (SHIN) and Yonsei University (YSU). The forcing data for the WRF model was obtained from the fifth generation of the European ReAnalysis (ERA5) dataset. The results were validated against observational data from the Trans-African Hydro-Meteorological Observatory (TAHMO). WRF was found to simulate surface meteorological variables with spatial details coherent with the complex topography within the Kenyan highlands, irrespective of the PBL scheme. A comparison between 2-meter temperature (T2) derived from the YSU scheme and T2 from the land component of ERA5 (ERA5-Land) indicates that surface meteorological variables derived from WRF are better suited for applications over the Kenyan highlands. The choice of the PBL scheme was found to primarily influence the simulation of the 10-meter wind speed (WS10) and rainfall as opposed to T2 and the 2-meter relative humidity (RH2). The insensitivity of the 2-meter variables to the choice of the PBL scheme is attributed to the influence of the surface layer parameterization near the surface. Results from the rainfall simulation indicate that the YSU scheme provides a more realistic depiction of PBL dynamics within the study area. Hence, the YSU scheme is best suited for simulating surface meteorological variables over the Kenyan highlands. Full article

(This article belongs to the Special Issue Representation of Land Surface Processes in Weather and Climate Models)

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38 pages, 21415 KiB

Open AccessEditor’s ChoiceArticle

ECLand: The ECMWF Land Surface Modelling System

by Souhail Boussetta, Gianpaolo Balsamo, Gabriele Arduini, Emanuel Dutra, Joe McNorton, Margarita Choulga, Anna Agustí-Panareda, Anton Beljaars, Nils Wedi, Joaquín Munõz-Sabater, Patricia de Rosnay, Irina Sandu, Ioan Hadade, Glenn Carver, Cinzia Mazzetti, Christel Prudhomme, Dai Yamazaki and Ervin Zsoter

Atmosphere 2021, 12(6), 723; https://doi.org/10.3390/atmos12060723 - 5 Jun 2021

Cited by 32 | Viewed by 9949

Abstract

The land-surface developments of the European Centre for Medium-range Weather Forecasts (ECMWF) are based on the Carbon-Hydrology Tiled Scheme for Surface Exchanges over Land (CHTESSEL) and form an integral part of the Integrated Forecasting System (IFS), supporting a wide range of global weather, climate and environmental applications. In order to structure, coordinate and focus future developments and benefit from international collaboration in new areas, a flexible system named ECLand, which would facilitate modular extensions to support numerical weather prediction (NWP) and society-relevant operational services, for example, Copernicus, is presented. This paper introduces recent examples of novel ECLand developments on (i) vegetation; (ii) snow; (iii) soil; (iv) open water/lake; (v) river/inundation; and (vi) urban areas. The developments are evaluated separately with long-range, atmosphere-forced surface offline simulations and coupled land-atmosphere-ocean experiments. This illustrates the benchmark criteria for assessing both process fidelity with regards to land surface fluxes and reservoirs of the water-energy-carbon exchange on the one hand, and on the other hand the requirements of ECMWF’s NWP, climate and atmospheric composition monitoring services using an Earth system assimilation and prediction framework. Full article

(This article belongs to the Special Issue Representation of Land Surface Processes in Weather and Climate Models)

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21 pages, 5665 KiB

Open AccessEditor’s ChoiceArticle

High-Resolution Numerical Modelling of Near-Surface Atmospheric Fields in the Complex Terrain of James Ross Island, Antarctic Peninsula

by Michael Matějka, Kamil Láska, Klára Jeklová and Jiří Hošek

Atmosphere 2021, 12(3), 360; https://doi.org/10.3390/atmos12030360 - 9 Mar 2021

Cited by 2 | Viewed by 2955

Abstract

The Antarctic Peninsula belongs to the regions of the Earth that have seen the highest increase in air temperature in the past few decades. The warming is reflected in degradation of the cryospheric system. The impact of climate variability and interactions between the atmosphere and the cryosphere can be studied using numerical atmospheric models. In this study, the standard version of the Weather Research and Forecasting (WRF) model was validated on James Ross Island in the northern part of the Antarctic Peninsula. The aim of this study was to verify the WRF model output at 700 m horizontal resolution using air temperature, wind speed and wind direction observations from automatic weather stations on the Ulu Peninsula, the northernmost part of James Ross Island. Validation was carried out for two contrasting periods (summer and winter) in 2019/2020 to assess possible seasonal effects on model accuracy. Simulated air temperatures were in very good agreement with measurements (mean bias −1.7 °C to 1.4 °C). The exception was a strong air temperature inversion during two of the winter days when a significant positive bias occurred at the coastal and lower-altitude locations on the Ulu Peninsula. Further analysis of the WRF estimates showed a good skill in simulating near-surface wind speed with higher correlation coefficients in winter (0.81–0.93) than in summer (0.41–0.59). However, bias and RMSE for wind speed tended to be better in summer. The performance of three WRF boundary layer schemes (MYJ, MYNN, QNSE) was further evaluated. The QNSE scheme was generally more accurate than MYNN and MYJ, but the differences were quite small and varied with time and place. The MYNN and QNSE schemes tended to achieve better wind speed simulation quality than the MYJ scheme. The model successfully captured wind direction, showing only slight differences to the observed values. It was shown that at lower altitudes the performance of the model can vary greatly with time. The model results were more accurate during high wind speed southwestern flow, while the accuracy decreased under weak synoptic-scale forcing, accompanied by an occurrence of mesoscale atmospheric processes. Full article

(This article belongs to the Special Issue Representation of Land Surface Processes in Weather and Climate Models)

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19 pages, 1983 KiB

Open AccessArticle

Impact of Environmental Conditions on Grass Phenology in the Regional Climate Model COSMO-CLM

by Eva Hartmann, Jan-Peter Schulz, Ruben Seibert, Marius Schmidt, Mingyue Zhang, Jürg Luterbacher and Merja H. Tölle

Atmosphere 2020, 11(12), 1364; https://doi.org/10.3390/atmos11121364 - 16 Dec 2020

Cited by 3 | Viewed by 3137

Abstract

Feedbacks of plant phenology to the regional climate system affect fluxes of energy, water, CO2, biogenic volatile organic compounds as well as canopy conductance, surface roughness length, and are influencing the seasonality of albedo. We performed simulations with the regional climate model COSMO-CLM (CCLM) at three locations in Germany covering the period 1999 to 2015 in order to study the sensitivity of grass phenology to different environmental conditions by implementing a new phenology module. We provide new evidence that the annually-recurring standard phenology of CCLM is improved by the new calculation of leaf area index (LAI) dependent upon surface temperature, day length, and water availability. Results with the new phenology implemented in the model show a significantly higher correlation with observations than simulations with the standard phenology. The interannual variability of LAI improves the representation of vegetation in years with extremely warm winter/spring (e.g., 2007) or extremely dry summer (e.g., 2003) and shows a more realistic growth period. The effect of the newly implemented phenology on atmospheric variables is small but tends to be positive. It should be used in future applications with an extension on more plant functional types. Full article

(This article belongs to the Special Issue Representation of Land Surface Processes in Weather and Climate Models)

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19 pages, 591 KiB

Open AccessArticle

Sensitivity of Surface Fluxes in the ECMWF Land Surface Model to the Remotely Sensed Leaf Area Index and Root Distribution: Evaluation with Tower Flux Data

by David Stevens, Pedro M. A. Miranda, René Orth, Souhail Boussetta, Gianpaolo Balsamo and Emanuel Dutra

Atmosphere 2020, 11(12), 1362; https://doi.org/10.3390/atmos11121362 - 16 Dec 2020

Cited by 10 | Viewed by 3830

Abstract

The surface-atmosphere turbulent exchanges couple the water, energy and carbon budgets in the Earth system. The biosphere plays an important role in the evaporation process, and vegetation related parameters such as the leaf area index (LAI), vertical root distribution and stomatal resistance are poorly constrained due to sparse observations at the spatio-temporal scales at which land surface models (LSMs) operate. In this study, we use the Carbon Hydrology Tiled European Center for Medium-Range Weather Forecasts (ECMWF) Scheme for Surface Exchanges over Land (CHTESSEL) model and investigate the sensitivity of the simulated turbulent fluxes to these vegetation related parameters. Observed data from 17 FLUXNET towers were used to force and evaluate model simulations with different vegetation parameter configurations. The replacement of the current LAI climatology used by CHTESSEL, by a new high-resolution climatology, representative of the station’s location, has a small impact on the simulated fluxes. Instead, a revision of the root profile considering a uniform root distribution reduces the underestimation of evaporation during water stress conditions. Despite the limitations of using only one model and a limited number of stations, our results highlight the relevance of root distribution in controlling soil moisture stress, which is likely to be applicable to other LSMs. Full article

(This article belongs to the Special Issue Representation of Land Surface Processes in Weather and Climate Models)

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20 pages, 8305 KiB

Open AccessArticle

Assessing the Impact of Land Use and Land Cover Data Representation on Weather Forecast Quality: A Case Study in Central Mexico

by Erika Danaé López-Espinoza, Jorge Zavala-Hidalgo, Rezaul Mahmood and Octavio Gómez-Ramos

Atmosphere 2020, 11(11), 1242; https://doi.org/10.3390/atmos11111242 - 18 Nov 2020

Cited by 19 | Viewed by 3496

Abstract

In atmospheric modeling, an accurate representation of land cover is required because such information impacts water and energy budgets and, consequently, the performance of models in simulating regional climate. This study analyzes the impact of the land cover data on an operational weather forecasting system using the Weather Research and Forecasting (WRF) model for central Mexico, with the aim of improving the quality of the operative forecast. Two experiments were conducted using different land cover datasets: a United States Geological Survey (USGS) map and an updated North American Land Change Monitoring System (NALCMS) map. The experiments were conducted as a daily 120 h forecast for each day of January, April, July, and September of 2012, and the near-surface temperature, wind speed, and hourly precipitation were analyzed. Both experiments were compared with observations from meteorological stations. The statistical analysis of this study showed that wind speed and near-surface temperature prediction may be further improved with the updated and more accurate NALCMS dataset, particularly in the forecast covering 48 to 72 h. The Root Mean Square Error (RMSE) of the average wind speed reached a maximum reduction of up to 1.2 m s⁻¹, whereas for the near-surface temperature there was a reduction of up to 0.6 °C. The RMSE of the average hourly precipitation was very similar between both experiments, however the location of precipitation was modified. Full article

(This article belongs to the Special Issue Representation of Land Surface Processes in Weather and Climate Models)

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15 pages, 3811 KiB

Open AccessArticle

Numerical Study of the Impact of Complex Terrain and Soil Moisture on Convective Initiation

by Beilei Zan, Ye Yu, Longxiang Dong, Jianglin Li, Guo Zhao and Tong Zhang

Atmosphere 2020, 11(8), 871; https://doi.org/10.3390/atmos11080871 - 17 Aug 2020

Cited by 6 | Viewed by 3279

Abstract

The relative importance of topography and soil moisture on the initiation of an afternoon deep convection under weak synoptic-scale forcing was investigated using the weather research and forecasting (WRF) model with high resolution (1.33 km). The convection occurred on 29 June 2017, over the Liupan Mountains, west of the Loess Plateau. The timing and location of the convective initiation (CI) simulated by the WRF model compared well with the radar observations. It showed that the warm and humid southerly airflow under 700 hPa was divided into east and west flows due to the blockage of the Liupan Mountains. The warm and humid air on the west side was forced to climb along the slope and enhanced the humidity near the ridge. The accumulation of unstable energy in the middle and north of the ridge led to a strong vertical convergence and triggered the convection. Sensitivity experiments showed that terrain played a dominant role in triggering the convection, while the spatial heterogeneity of soil moisture played an indirect role by affecting the local circulation and the partition of surface energy. Full article

(This article belongs to the Special Issue Representation of Land Surface Processes in Weather and Climate Models)

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