Large-scale rain-fed to paddy farmland conversion modified land-surface thermal properties in Cold China

Abstract. Bryophyte and lichen cover on the forest floor at high latitudes exerts an insulating effect on the ground. In this way, the cover decreases mean annual soil temperature and can protect permafrost soil. Climate change, however, may change bryophyte and lichen cover, with effects on the permafrost state and related carbon balance. It is, therefore, crucial to predict how the bryophyte and lichen cover will react to environmental change at the global scale. To date, current global land surface models contain only empirical representations of the bryophyte and lichen cover, which makes it impractical to predict the future state and function of bryophytes and lichens. For this reason, we integrate a process-based model of bryophyte and lichen growth into the global land surface model JSBACH (Jena Scheme for Biosphere–Atmosphere Coupling in Hamburg). The model simulates bryophyte and lichen cover on upland sites. Wetlands are not included. We take into account the dynamic nature of the thermal properties of the bryophyte and lichen cover and their relation to environmental factors. Subsequently, we compare simulations with and without bryophyte and lichen cover to quantify the insulating effect of the organisms on the soil. We find an average cooling effect of the bryophyte and lichen cover of 2.7 K on temperature in the topsoil for the region north of 50° N under the current climate. Locally, a cooling of up to 5.7 K may be reached. Moreover, we show that using a simple, empirical representation of the bryophyte and lichen cover without dynamic properties only results in an average cooling of around 0.5 K. This suggests that (a) bryophytes and lichens have a significant impact on soil temperature in high-latitude ecosystems and (b) a process-based description of their thermal properties is necessary for a realistic representation of the cooling effect. The advanced land surface scheme, including a dynamic bryophyte and lichen model, will be the basis for an improved future projection of land–atmosphere heat and carbon exchange.

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Testing a Gypsum Composite Based on Raw Gypsum with a Direct Admixture of Paraffin and Polymer to Improve Thermal Properties

Materials ◽

10.3390/ma14123241 ◽

2021 ◽

Vol 14 (12) ◽

pp. 3241

Author(s):

Krzysztof Powała ◽

Andrzej Obraniak ◽

Dariusz Heim

Keyword(s):

Thermal Conductivity ◽

Heat Capacity ◽

Thermal Properties ◽

Phase Change ◽

Large Scale ◽

Building Materials ◽

Residential Buildings ◽

Energy Performance ◽

Polymer Content ◽

Volumetric Heat Capacity

The implemented new legal regulations regarding thermal comfort, the energy performance of residential buildings, and proecological requirements require the design of new building materials, the use of which will improve the thermal efficiency of newly built and renovated buildings. Therefore, many companies producing building materials strive to improve the properties of their products by reducing the weight of the materials, increasing their mechanical properties, and improving their insulating properties. Currently, there are solutions in phase-change materials (PCM) production technology, such as microencapsulation, but its application on a large scale is extremely costly. This paper presents a solution to the abovementioned problem through the creation and testing of a composite, i.e., a new mixture of gypsum, paraffin, and polymer, which can be used in the production of plasterboard. The presented solution uses a material (PCM) which improves the thermal properties of the composite by taking advantage of the phase-change phenomenon. The study analyzes the influence of polymer content in the total mass of a composite in relation to its thermal conductivity, volumetric heat capacity, and diffusivity. Based on the results contained in this article, the best solution appears to be a mixture with 0.1% polymer content. It is definitely visible in the tests which use drying, hardening time, and paraffin absorption. It differs slightly from the best result in the thermal conductivity test, while it is comparable in terms of volumetric heat capacity and differs slightly from the best result in the thermal diffusivity test.

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Reservoir-Induced Land Deformation: Case Study from the Grand Ethiopian Renaissance Dam

Remote Sensing ◽

10.3390/rs13050874 ◽

2021 ◽

Vol 13 (5) ◽

pp. 874

Author(s):

Yu Chen ◽

Mohamed Ahmed ◽

Natthachet Tangdamrongsub ◽

Dorina Murgulet

Keyword(s):

Land Surface ◽

Large Scale ◽

Surface Deformation ◽

Vertical Displacement ◽

Nile River ◽

Reservoir Volume ◽

Novel Approach ◽

Land Deformation ◽

Large Scale Land ◽

The Impact

The Nile River stretches from south to north throughout the Nile River Basin (NRB) in Northeast Africa. Ethiopia, where the Blue Nile originates, has begun the construction of the Grand Ethiopian Renaissance Dam (GERD), which will be used to generate electricity. However, the impact of the GERD on land deformation caused by significant water relocation has not been rigorously considered in the scientific research. In this study, we develop a novel approach for predicting large-scale land deformation induced by the construction of the GERD reservoir. We also investigate the limitations of using the Gravity Recovery and Climate Experiment Follow On (GRACE-FO) mission to detect GERD-induced land deformation. We simulated three land deformation scenarios related to filling the expected reservoir volume, 70 km3, using 5-, 10-, and 15-year filling scenarios. The results indicated: (i) trends in downward vertical displacement estimated at −17.79 ± 0.02, −8.90 ± 0.09, and −5.94 ± 0.05 mm/year, for the 5-, 10-, and 15-year filling scenarios, respectively; (ii) the western (eastern) parts of the GERD reservoir are estimated to move toward the reservoir’s center by +0.98 ± 0.01 (−0.98 ± 0.01), +0.48 ± 0.00 (−0.48 ± 0.00), and +0.33 ± 0.00 (−0.33 ± 0.00) mm/year, under the 5-, 10- and 15-year filling strategies, respectively; (iii) the northern part of the GERD reservoir is moving southward by +1.28 ± 0.02, +0.64 ± 0.01, and +0.43 ± 0.00 mm/year, while the southern part is moving northward by −3.75 ± 0.04, −1.87 ± 0.02, and −1.25 ± 0.01 mm/year, during the three examined scenarios, respectively; and (iv) the GRACE-FO mission can only detect 15% of the large-scale land deformation produced by the GERD reservoir. Methods and results demonstrated in this study provide insights into possible impacts of reservoir impoundment on land surface deformation, which can be adopted into the GERD project or similar future dam construction plans.

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Cities Exacerbate Climate Warming

Urban Science ◽

10.3390/urbansci5010027 ◽

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.

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Hydrological evaluation of high-resolution precipitation estimates from the WRF model in the Third Pole river basins

Journal of Hydrometeorology ◽

10.1175/jhm-d-20-0272.1 ◽

2021 ◽

Author(s):

He Sun ◽

Fengge Su ◽

Zhihua He ◽

Tinghai Ou ◽

Deliang Chen ◽

...

Keyword(s):

Land Surface ◽

Large Scale ◽

Hydrological Modeling ◽

Climate Model ◽

Regional Climate ◽

Wrf Model ◽

Infiltration Capacity ◽

Flood Prediction ◽

Daily Streamflow ◽

Precipitation Estimates

AbstractIn this study, two sets of precipitation estimates based on the regional Weather Research and Forecasting model (WRF) –the high Asia refined analysis (HAR) and outputs with a 9 km resolution from WRF (WRF-9km) are evaluated at both basin and point scales, and their potential hydrological utilities are investigated by driving the Variable Infiltration Capacity (VIC) large-scale land surface hydrological model in seven Third Pole (TP) basins. The regional climate model (RCM) tends to overestimate the gauge-based estimates by 20–95% in annual means among the selected basins. Relative to the gauge observations, the RCM precipitation estimates can accurately detect daily precipitation events of varying intensities (with absolute bias < 3 mm). The WRF-9km exhibits a high potential for hydrological application in the monsoon-dominated basins in the southeastern TP (with NSE of 0.7–0.9 and bias of -11% to 3%), while the HAR performs well in the upper Indus (UI) and upper Brahmaputra (UB) basins (with NSE of 0.6 and bias of -15% to -9%). Both the RCM precipitation estimates can accurately capture the magnitudes of low and moderate daily streamflow, but show limited capabilities in flood prediction in most of the TP basins. This study provides a comprehensive evaluation of the strength and limitation of RCMs precipitation in hydrological modeling in the TP with complex terrains and sparse gauge observations.

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Continuous high-resolution midlatitude-belt simulations for July–August 2013 with WRF

Geoscientific Model Development ◽

10.5194/gmd-10-2031-2017 ◽

2017 ◽

Vol 10 (5) ◽

pp. 2031-2055 ◽

Cited By ~ 14

Author(s):

Thomas Schwitalla ◽

Hans-Stefan Bauer ◽

Volker Wulfmeyer ◽

Kirsten Warrach-Sagi

Keyword(s):

High Resolution ◽

Land Surface ◽

Large Scale ◽

Temperature Fields ◽

Surface Model ◽

Limited Area ◽

Data Set ◽

Latitude Belt ◽

Simulated Precipitation ◽

The Impact

Abstract. Increasing computational resources and the demands of impact modelers, stake holders, and society envision seasonal and climate simulations with the convection-permitting resolution. So far such a resolution is only achieved with a limited-area model whose results are impacted by zonal and meridional boundaries. Here, we present the setup of a latitude-belt domain that reduces disturbances originating from the western and eastern boundaries and therefore allows for studying the impact of model resolution and physical parameterization. The Weather Research and Forecasting (WRF) model coupled to the NOAH land–surface model was operated during July and August 2013 at two different horizontal resolutions, namely 0.03 (HIRES) and 0.12° (LOWRES). Both simulations were forced by the European Centre for Medium-Range Weather Forecasts (ECMWF) operational analysis data at the northern and southern domain boundaries, and the high-resolution Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA) data at the sea surface.The simulations are compared to the operational ECMWF analysis for the representation of large-scale features. To analyze the simulated precipitation, the operational ECMWF forecast, the CPC MORPHing (CMORPH), and the ENSEMBLES gridded observation precipitation data set (E-OBS) were used as references.Analyzing pressure, geopotential height, wind, and temperature fields as well as precipitation revealed (1) a benefit from the higher resolution concerning the reduction of monthly biases, root mean square error, and an improved Pearson skill score, and (2) deficiencies in the physical parameterizations leading to notable biases in distinct regions like the polar Atlantic for the LOWRES simulation, the North Pacific, and Inner Mongolia for both resolutions.In summary, the application of a latitude belt on a convection-permitting resolution shows promising results that are beneficial for future seasonal forecasting.

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Spatial variability and its scale dependency of observed and modeled soil moisture over different climate regions

Hydrology and Earth System Sciences ◽

10.5194/hess-17-1177-2013 ◽

2013 ◽

Vol 17 (3) ◽

pp. 1177-1188 ◽

Cited By ~ 45

Author(s):

B. Li ◽

M. Rodell

Keyword(s):

Soil Moisture ◽

Spatial Variability ◽

Land Surface ◽

Large Scale ◽

Warm Season ◽

Scale Dependency ◽

Convex Shape ◽

Spatial Moments ◽

Environmental Controls

Abstract. Past studies on soil moisture spatial variability have been mainly conducted at catchment scales where soil moisture is often sampled over a short time period; as a result, the observed soil moisture often exhibited smaller dynamic ranges, which prevented the complete revelation of soil moisture spatial variability as a function of mean soil moisture. In this study, spatial statistics (mean, spatial variability and skewness) of in situ soil moisture, modeled and satellite-retrieved soil moisture obtained in a warm season (198 days) were examined over three large climate regions in the US. The study found that spatial moments of in situ measurements strongly depend on climates, with distinct mean, spatial variability and skewness observed in each climate zone. In addition, an upward convex shape, which was revealed in several smaller scale studies, was observed for the relationship between spatial variability of in situ soil moisture and its spatial mean when statistics from dry, intermediate, and wet climates were combined. This upward convex shape was vaguely or partially observable in modeled and satellite-retrieved soil moisture estimates due to their smaller dynamic ranges. Despite different environmental controls on large-scale soil moisture spatial variability, the correlation between spatial variability and mean soil moisture remained similar to that observed at small scales, which is attributed to the boundedness of soil moisture. From the smaller support (effective area or volume represented by a measurement or estimate) to larger ones, soil moisture spatial variability decreased in each climate region. The scale dependency of spatial variability all followed the power law, but data with large supports showed stronger scale dependency than those with smaller supports. The scale dependency of soil moisture variability also varied with climates, which may be linked to the scale dependency of precipitation spatial variability. Influences of environmental controls on soil moisture spatial variability at large scales are discussed. The results of this study should be useful for diagnosing large scale soil moisture estimates and for improving the estimation of land surface processes.

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Climate Drivers Linked to Changing Seasonality of Alaska Coastal Tundra Vegetation Productivity

Earth Interactions ◽

10.1175/ei-d-15-0013.1 ◽

2015 ◽

Vol 19 (19) ◽

pp. 1-29 ◽

Cited By ~ 25

Author(s):

Peter A. Bieniek ◽

Uma S. Bhatt ◽

Donald A. Walker ◽

Martha K. Raynolds ◽

Josefino C. Comiso ◽

...

Keyword(s):

Land Surface ◽

Large Scale ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Sea Breeze ◽

Tundra Vegetation ◽

Land Surface Temperatures ◽

Alaskan Tundra ◽

Northern Alaska

Abstract The mechanisms driving trends and variability of the normalized difference vegetation index (NDVI) for tundra in Alaska along the Beaufort, east Chukchi, and east Bering Seas for 1982–2013 are evaluated in the context of remote sensing, reanalysis, and meteorological station data as well as regional modeling. Over the entire season the tundra vegetation continues to green; however, biweekly NDVI has declined during the early part of the growing season in all of the Alaskan tundra domains. These springtime declines coincide with increased snow depth in spring documented in northern Alaska. The tundra region generally has warmed over the summer but intraseasonal analysis shows a decline in midsummer land surface temperatures. The midsummer cooling is consistent with recent large-scale circulation changes characterized by lower sea level pressures, which favor increased cloud cover. In northern Alaska, the sea-breeze circulation is strengthened with an increase in atmospheric moisture/cloudiness inland when the land surface is warmed in a regional model, suggesting the potential for increased vegetation to feedback onto the atmospheric circulation that could reduce midsummer temperatures. This study shows that both large- and local-scale climate drivers likely play a role in the observed seasonality of NDVI trends.

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Drought Relief and Reversal over North America from 1500 to 2016

Earth Interactions ◽

10.1175/ei-d-20-0020.1 ◽

2021 ◽

Vol 25 (1) ◽

pp. 94-107

Author(s):

M. C. A. Torbenson ◽

D. W. Stahle ◽

I. M. Howard ◽

D. J. Burnette ◽

D. Griffin ◽

...

Keyword(s):

Soil Moisture ◽

North America ◽

Land Surface ◽

Large Scale ◽

Temporal Stability ◽

Warm Season ◽

Cool Season ◽

Continental Scale ◽

The North ◽

Drought Relief

Abstract Season-to-season persistence of soil moisture drought varies across North America. Such interseasonal autocorrelation can have modest skill in forecasting future conditions several months in advance. Because robust instrumental observations of precipitation span less than 100 years, the temporal stability of the relationship between seasonal moisture anomalies is uncertain. The North American Seasonal Precipitation Atlas (NASPA) is a gridded network of separately reconstructed cool-season (December–April) and warm-season (May–July) precipitation series and offers new insights on the intra-annual changes in drought for up to 2000 years. Here, the NASPA precipitation reconstructions are rescaled to represent the long-term soil moisture balance during the cool season and 3-month-long atmospheric moisture during the warm season. These rescaled seasonal reconstructions are then used to quantify the frequency, magnitude, and spatial extent of cool-season drought that was relieved or reversed during the following summer months. The adjusted seasonal reconstructions reproduce the general patterns of large-scale drought amelioration and termination in the instrumental record during the twentieth century and are used to estimate relief and reversals for the most skillfully reconstructed past 500 years. Subcontinental-to-continental-scale reversals of cool-season drought in the following warm season have been rare, but the reconstructions display periods prior to the instrumental data of increased reversal probabilities for the mid-Atlantic region and the U.S. Southwest. Drought relief at the continental scale may arise in part from macroscale ocean–atmosphere processes, whereas the smaller-scale regional reversals may reflect land surface feedbacks and stochastic variability.

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Large-scale groundwater modeling using global datasets: a test case for the Rhine-Meuse basin

Hydrology and Earth System Sciences Discussions ◽

10.5194/hessd-8-2555-2011 ◽

2011 ◽

Vol 8 (2) ◽

pp. 2555-2608 ◽

Cited By ~ 2

Author(s):

E. H. Sutanudjaja ◽

L. P. H. van Beek ◽

S. M. de Jong ◽

F. C. van Geer ◽

M. F. P. Bierkens

Keyword(s):

Sensitivity Analysis ◽

Land Surface ◽

Large Scale ◽

Groundwater Modeling ◽

Land Surface Model ◽

Water Levels ◽

Surface Model ◽

Groundwater Model ◽

Model Output ◽

Global Datasets

Abstract. Large-scale groundwater models involving aquifers and basins of multiple countries are still rare due to a lack of hydrogeological data which are usually only available in developed countries. In this study, we propose a novel approach to construct large-scale groundwater models by using global datasets that are readily available. As the test-bed, we use the combined Rhine-Meuse basin that contains groundwater head data used to verify the model output. We start by building a distributed land surface model (30 arc-second resolution) to estimate groundwater recharge and river discharge. Subsequently, a MODFLOW transient groundwater model is built and forced by the recharge and surface water levels calculated by the land surface model. Although the method that we used to couple the land surface and MODFLOW groundwater model is considered as an offline-coupling procedure (i.e. the simulations of both models were performed separately), results are promising. The simulated river discharges compare well to the observations. Moreover, based on our sensitivity analysis, in which we run several groundwater model scenarios with various hydrogeological parameter settings, we observe that the model can reproduce the observed groundwater head time series reasonably well. However, we note that there are still some limitations in the current approach, specifically because the current offline-coupling technique simplifies dynamic feedbacks between surface water levels and groundwater heads, and between soil moisture states and groundwater heads. Also the current sensitivity analysis ignores the uncertainty of the land surface model output. Despite these limitations, we argue that the results of the current model show a promise for large-scale groundwater modeling practices, including for data-poor environments and at the global scale.

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