Development of a 50-Year High-Resolution Global Dataset of Meteorological Forcings for Land Surface Modeling

2006 ◽  
Vol 19 (13) ◽  
pp. 3088-3111 ◽  
Author(s):  
Justin Sheffield ◽  
Gopi Goteti ◽  
Eric F. Wood
Keyword(s):  
Land Surface ◽  
Large Scale ◽  
Hydrologic Cycle ◽  
Surface Fluxes ◽  
Specific Humidity ◽  
Meteorological Variables ◽  
Coupled Models ◽  
Near Surface ◽  
Solid Precipitation

Abstract Understanding the variability of the terrestrial hydrologic cycle is central to determining the potential for extreme events and susceptibility to future change. In the absence of long-term, large-scale observations of the components of the hydrologic cycle, modeling can provide consistent fields of land surface fluxes and states. This paper describes the creation of a global, 50-yr, 3-hourly, 1.0° dataset of meteorological forcings that can be used to drive models of land surface hydrology. The dataset is constructed by combining a suite of global observation-based datasets with the National Centers for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR) reanalysis. Known biases in the reanalysis precipitation and near-surface meteorology have been shown to exert an erroneous effect on modeled land surface water and energy budgets and are thus corrected using observation-based datasets of precipitation, air temperature, and radiation. Corrections are also made to the rain day statistics of the reanalysis precipitation, which have been found to exhibit a spurious wavelike pattern in high-latitude wintertime. Wind-induced undercatch of solid precipitation is removed using the results from the World Meteorological Organization (WMO) Solid Precipitation Measurement Intercomparison. Precipitation is disaggregated in space to 1.0° by statistical downscaling using relationships developed with the Global Precipitation Climatology Project (GPCP) daily product. Disaggregation in time from daily to 3 hourly is accomplished similarly, using the Tropical Rainfall Measuring Mission (TRMM) 3-hourly real-time dataset. Other meteorological variables (downward short- and longwave radiation, specific humidity, surface air pressure, and wind speed) are downscaled in space while accounting for changes in elevation. The dataset is evaluated against the bias-corrected forcing dataset of the second Global Soil Wetness Project (GSWP2). The final product provides a long-term, globally consistent dataset of near-surface meteorological variables that can be used to drive models of the terrestrial hydrologic and ecological processes for the study of seasonal and interannual variability and for the evaluation of coupled models and other land surface prediction schemes.

Which hydro-meteorological variables control large-scale photosynthesis?

2020 ◽  
Author(s):  
Wantong Li ◽  
Mirco Migliavacca ◽  
Yunpeng Luo ◽  
René Orth
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Vegetation Dynamics ◽  
Large Scale ◽  
Global Analysis ◽  
Spatial Scales ◽  
Meteorological Variables ◽  
Climate Projections ◽  
Net Radiation ◽  
Near Surface

<p>Vegetation dynamics are determined by a multitude of hydro-meteorological variables, and this interplay changes in space and time. Due to its complexity, it is still not fully understood at large spatial scales. This knowledge gap contributes to increased uncertainties in future climate projections because large-scale photosynthesis is influencing the exchange of energy and water between the land surface and the atmosphere, thereby potentially impacting near-surface weather. In this study, we explore the relative importance of several hydro-meteorological variables for vegetation dynamics. For this purpose, we infer the correlations of anomalies in temperature, precipitation, soil moisture, VPD, surface net radiation and surface downward solar radiation with respective anomalies of photosynthetic activity as inferred from Sun-Induced chlorophyll Fluorescence (SIF). To detect changing hydro-meteorological controls across different climate conditions, this global analysis distinguishes between climate regimes as determined by long-term mean aridity and temperature. The results show that soil moisture was the most critical driver with SIF in the simultaneous correlation with dry and warm conditions, while temperature and VPD was both influential on cold and wet regimes during the study period 2007-2018. We repeat our analysis by replacing the SIF data with NDVI, as a proxy for vegetation greenness, and find overall similar results, except for surface net radiation expanding controlled regions on cold and wet regimes. As the considered hydro-meteorological variables are inter-related, spurious correlations can occur. We test different approaches to investigate and account for this phenomenon. The results can provide new insight into mechanisms of vegetation-water-energy interactions and contribute to improve dynamic global vegetation models.</p>

scholarly journals Sensitivity of the regional European boreal climate to changes in surface properties resulting from structural vegetation perturbations

2015 ◽  
Vol 12 (10) ◽  
pp. 3071-3087 ◽  
Author(s):  
J. H. Rydsaa ◽  
F. Stordal ◽  
L. M. Tallaksen
Keyword(s):  
Land Surface ◽  
Large Scale ◽  
Structural Changes ◽  
Mixed Forest ◽  
Surface Fluxes ◽  
Heat Fluxes ◽  
Energy Partitioning ◽  
The Arctic ◽  
Surface Model ◽  
Near Surface

Abstract. Amplified warming at high latitudes over the past few decades has led to changes in the boreal and Arctic climate system such as structural changes in high-latitude ecosystems and soil moisture properties. These changes trigger land–atmosphere feedbacks through altered energy partitioning in response to changes in albedo and surface water fluxes. Local-scale changes in the Arctic and boreal zones may propagate to affect large-scale climatic features. In this study, MODIS land surface data are used with the Weather Research and Forecasting model (WRF V3.5.1) and Noah land surface model (LSM), in a series of experiments to investigate the sensitivity of the overlying atmosphere to perturbations in the structural vegetation in the northern European boreal ecosystem. Emphasis is placed on surface energy partitioning and near-surface atmospheric variables, and their response to observed and anticipated land cover changes. We find that perturbations simulating northward migration of evergreen needleleaf forest into tundra regions cause an increase in latent rather than sensible heat fluxes during the summer season. Shrub expansion in tundra areas has only small effects on surface fluxes. Perturbations simulating the northward migration of mixed forest across the present southern border of the boreal forest, have largely opposite effects on the summer latent heat flux, i.e., they lead to a decrease and act to moderate the overall mean regional effects of structural vegetation changes on the near-surface atmosphere.

scholarly journals Cities Exacerbate Climate Warming

Urban Science ◽  
2021 ◽  
Vol 5 (1) ◽  
pp. 27
Author(s):  
Lahouari Bounoua ◽  
Kurtis Thome ◽  
Joseph Nigro
Keyword(s):  
Surface Temperature ◽  
Land Surface ◽  
Large Scale ◽  
Climate Models ◽  
Warming Trend ◽  
Climate Mitigation ◽  
Temperature Changes ◽  
Surface Warming ◽  
The Us

Urbanization is a complex land transformation not explicitly resolved within large-scale climate models. Long-term timeseries of high-resolution satellite data are essential to characterize urbanization within land surface models and to assess its contribution to surface temperature changes. The potential for additional surface warming from urbanization-induced land use change is investigated and decoupled from that due to change in climate over the continental US using a decadal timescale. We show that, aggregated over the US, the summer mean urban-induced surface temperature increased by 0.15 °C, with a warming of 0.24 °C in cities built in vegetated areas and a cooling of 0.25 °C in cities built in non-vegetated arid areas. This temperature change is comparable in magnitude to the 0.13 °C/decade global warming trend observed over the last 50 years caused by increased CO2. We also show that the effect of urban-induced change on surface temperature is felt above and beyond that of the CO2 effect. Our results suggest that climate mitigation policies must consider urbanization feedback to put a limit on the worldwide mean temperature increase.

scholarly journals Assessing the Impact of Changes in Land Surface Conditions on WRF Predictions in Arid Regions

2020 ◽  
Vol 21 (12) ◽  
pp. 2829-2853 ◽  
Author(s):  
Marouane Temimi ◽  
Ricardo Fonseca ◽  
Narendra Nelli ◽  
Michael Weston ◽  
Mohan Thota ◽  
...  
Keyword(s):  
Eddy Covariance ◽  
Soil Texture ◽  
Land Surface ◽  
Surface Wind ◽  
Surface Fluxes ◽  
Abu Dhabi ◽  
Horizontal Wind ◽  
Cold Bias ◽  
Near Surface ◽  
The Impact

AbstractA thorough evaluation of the Weather Research and Forecasting (WRF) Model is conducted over the United Arab Emirates, for the period September 2017–August 2018. Two simulations are performed: one with the default model settings (control run), and another one (experiment) with an improved representation of soil texture and land use land cover (LULC). The model predictions are evaluated against observations at 35 weather stations, radiosonde profiles at the coastal Abu Dhabi International Airport, and surface fluxes from eddy-covariance measurements at the inland city of Al Ain. It is found that WRF’s cold temperature bias, also present in the forcing data and seen almost exclusively at night, is reduced when the surface and soil properties are updated, by as much as 3.5 K. This arises from the expansion of the urban areas, and the replacement of loamy regions with sand, which has a higher thermal inertia. However, the model continues to overestimate the strength of the near-surface wind at all stations and seasons, typically by 0.5–1.5 m s−1. It is concluded that the albedo of barren/sparsely vegetated regions in WRF (0.380) is higher than that inferred from eddy-covariance observations (0.340), which can also explain the referred cold bias. At the Abu Dhabi site, even though soil texture and LULC are not changed, there is a small but positive effect on the predicted vertical profiles of temperature, humidity, and horizontal wind speed, mostly between 950 and 750 hPa, possibly because of differences in vertical mixing.

scholarly journals Simulating carbon exchange using a regional atmospheric model coupled to an advanced land-surface model

2008 ◽  
Vol 5 (5) ◽  
pp. 4161-4207 ◽  
Author(s):  
H. W. Ter Maat ◽  
R. W. A. Hutjes
Keyword(s):  
Carbon Dioxide ◽  
Land Surface ◽  
Large Scale ◽  
Regional Scale ◽  
Atmospheric Model ◽  
Surface Fluxes ◽  
Heat Fluxes ◽  
Surface Model ◽  
Carbon Exchange ◽  
Regional Atmospheric Modelling System

Abstract. A large scale mismatch exists between our understanding and quantification of ecosystem atmosphere exchange of carbon dioxide at local scale and continental scales. This paper will focus on the carbon exchange on the regional scale to address the following question: What are the main controlling factors determining atmospheric carbon dioxide content at a regional scale? We use the Regional Atmospheric Modelling System (RAMS), coupled with a land surface scheme simulating carbon, heat and momentum fluxes (SWAPS-C), and including also sub models for urban and marine fluxes, which in principle include the main controlling mechanisms and capture the relevant dynamics of the system. To validate the model, observations are used which were taken during an intensive observational campaign in the central Netherlands in summer 2002. These included flux-site observations, vertical profiles at tall towers and spatial fluxes of various variables taken by aircraft. The coupled regional model (RAMS-SWAPS-C) generally does a good job in simulating results close to reality. The validation of the model demonstrates that surface fluxes of heat, water and CO2 are reasonably well simulated. The comparison against aircraft data shows that the regional meteorology is captured by the model. Comparing spatially explicit simulated and observed fluxes we conclude that in general simulated latent heat fluxes are underestimated by the model to the observations which exhibit large standard deviation for all flights. Sensitivity experiments demonstrated the relevance of the urban emissions of carbon dioxide for the carbon balance in this particular region. The same test also show the relation between uncertainties in surface fluxes and those in atmospheric concentrations.

scholarly journals A high-resolution global dataset of topographic index values for use in large-scale hydrological modelling

2014 ◽  
Vol 11 (6) ◽  
pp. 6139-6166 ◽  
Author(s):  
T. R. Marthews ◽  
S. J. Dadson ◽  
B. Lehner ◽  
S. Abele ◽  
N. Gedney
Keyword(s):  
High Resolution ◽  
Land Surface ◽  
Large Scale ◽  
Global Scale ◽  
Surface Fluxes ◽  
Data Sets ◽  
Topographic Index ◽  
Surface Water Flow ◽  
Land Surface Water ◽  
Compound Topographic Index

Abstract. Modelling land surface water flow is of critical importance for simulating land-surface fluxes, predicting runoff and water table dynamics and for many other applications of Land Surface Models. Many approaches are based on the popular hydrology model TOPMODEL, and the most important parameter of this model is the well-knowntopographic index. Here we present new, high-resolution parameter maps of the topographic index for all ice-free land pixels calculated from hydrologically-conditioned HydroSHEDS data sets using the GA2 algorithm. At 15 arcsec resolution, these layers are 4× finer than the resolution of the previously best-available topographic index layers, the Compound Topographic Index of HYDRO1k (CTI). In terms of the largest river catchments occurring on each continent, we found that in comparison to our revised values, CTI values were up to 20% higher in e.g. the Amazon. We found the highest catchment means were for the Murray-Darling and Nelson-Saskatchewan rather than for the Amazon and St. Lawrence as found from the CTI. We believe these new index layers represent the most robust existing global-scale topographic index values and hope that they will be widely used in land surface modelling applications in the future.

scholarly journals Atmospheric Dynamics Feedback: Concept, Simulations, and Climate Implications

2018 ◽  
Vol 31 (8) ◽  
pp. 3249-3264 ◽  
Author(s):  
Michael P. Byrne ◽  
Tapio Schneider
Keyword(s):  
Climate Change ◽  
Atmospheric Circulation ◽  
Radiative Forcing ◽  
Large Scale ◽  
Climate Models ◽  
Atmospheric Dynamics ◽  
Future Climate Change ◽  
Coupled Models ◽  
Near Surface ◽  
Circulation Changes

AbstractThe regional climate response to radiative forcing is largely controlled by changes in the atmospheric circulation. It has been suggested that global climate sensitivity also depends on the circulation response, an effect called the “atmospheric dynamics feedback.” Using a technique to isolate the influence of changes in atmospheric circulation on top-of-the-atmosphere radiation, the authors calculate the atmospheric dynamics feedback in coupled climate models. Large-scale circulation changes contribute substantially to all-sky and cloud feedbacks in the tropics but are relatively less important at higher latitudes. Globally averaged, the atmospheric dynamics feedback is positive and amplifies the near-surface temperature response to climate change by an average of 8% in simulations with coupled models. A constraint related to the atmospheric mass budget results in the dynamics feedback being small on large scales relative to feedbacks associated with thermodynamic processes. Idealized-forcing simulations suggest that circulation changes at high latitudes are potentially more effective at influencing global temperature than circulation changes at low latitudes, and the implications for past and future climate change are discussed.

Advanced Structural Integrity Assessment Tools for Safe Long Term Operation: ATLAS+ Project — Status of the Activities of the WP3 on Modelling

2019 ◽  
Author(s):  
Stéphane Marie ◽  
Arnaud Blouin ◽  
Tomas Nicak ◽  
Dominique Moinereau ◽  
Anna Dahl ◽  
...  
Keyword(s):  
Large Scale ◽  
Structural Integrity ◽  
Assessment Tools ◽  
Local Approach ◽  
Coupled Models ◽  
Large Defect ◽  
Ductile Tearing ◽  
Term Operation ◽  
Integrity Assessment

Abstract The main objective and mission of the ATLAS+ project is to develop advanced structural assessment tools to address the remaining technology gaps for the safe and long term operation of nuclear reactor pressure coolant boundary systems. ATLAS+ WP3 focuses mainly on ductile tearing prediction for large defect in components: Several approaches have been developed to accurately model the ductile tearing process and to take into account phenomena such as the triaxiality effect, or the ability to predict large tearing in industrial components. These advanced models include local approach coupled models or advanced energetic approaches. Unfortunately, the application of these tools is today rather limited to R&D expertise. However, because of the continuous progress in the performance of the calculation tools and accumulated knowledge, in particular by members of ATLAS+, these models can now be considered as relevant for application in the context of engineering assessments. WP3 will therefore: • Illustrate the implementation of these models for industrial applications through the interpretation of large scale mock-ups (with cracks in weld joints for some of them), • Make recommendations for the implementation of the advanced models in engineering assessments, • Correct data from the conventional engineering approach by developing a methodology to produce J-Δa curve suitable case by case, based on local approach models, • Improve the tools, guidance and procedures for undertaking leak-before-break (LBB) assessments of piping components, particularly in relation to representing structural representative fracture toughness J-Resistance curves and the influence of weld residual stresses. To achieve these goals, WP3 is divided into 4 sub-WPs and this paper presents the progress of the work performed in each sub-WP after 24 months of activities.

scholarly journals Modeling the Effect of Desert Urbanization on Local Climate and Natural Dust Generation: A Case Study for Erbil, Iraq

Urban Science ◽  
2020 ◽  
Vol 4 (4) ◽  
pp. 46
Author(s):  
Sherzad T. Tahir ◽  
Huei-Ping Huang
Keyword(s):  
Land Surface ◽  
Numerical Models ◽  
Surface Wind ◽  
Surface Fluxes ◽  
Slight Reduction ◽  
Rapid Urbanization ◽  
Near Surface ◽  
Local Climate ◽  
Surface Dust ◽  
Dust Generation

This study uses a suite of meteorological and land-surface models to quantify the changes in local climate and surface dust fluxes associated with desert urbanization. Formulas connecting friction velocity and soil moisture to dust generation are used to quantify surface fluxes for natural wind-blown dust. The models are used to conduct a series of simulations for the desert city of Erbil across a period of rapid urbanization. The results show significant nighttime warming and weak but robust daytime cooling associated with desert urbanization. A slight reduction in near-surface wind speed is also found in the areas undergoing urbanization. These findings are consistent with previous empirical and modeling studies on other desert cities. Numerical models and empirical formulas are used to produce climatological maps of surface dust fluxes as a function of season, and for the pre- and post-urbanization eras. This framework can potentially be used to bridge the gap in observation on the trends in local dust generation associated with land-use changes and urban expansions.

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