scholarly journals Using a Simple Water Balance Framework to Quantify the Impact of Soil Moisture Initialization on Subseasonal Evapotranspiration and Air Temperature Forecasts

2020 ◽  
Vol 21 (8) ◽  
pp. 1705-1722 ◽  
Author(s):  
Randal D. Koster ◽  
Siegfried D. Schubert ◽  
Anthony M. DeAngelis ◽  
Andrea M. Molod ◽  
Sarith P. Mahanama
Keyword(s):  
Soil Moisture ◽  
Simple Model ◽  
Water Balance ◽  
Air Temperature ◽  
Surface Air Temperature ◽  
Near Surface ◽  
Forecasting System ◽  
The Impact ◽  
Soil Moisture Initialization ◽  
Eastern Half

AbstractPast studies have shown that accurate soil moisture initialization can contribute significant skill to near-surface air temperature (T2M) forecasts at subseasonal leads. The mechanisms by which soil moisture contributes such skill are examined here with a simple water balance–based model that captures the essence of soil moisture behavior in a state-of-the-art subseasonal-to-seasonal (S2S) forecasting system. The simple model successfully transforms initial soil moisture contents into average “forecast” evapotranspiration (ET) values at 16–30-day lead that agree well, during summer, with the values forecast by the full NASA GEOS S2S system, indicating that soil moisture initialization dominates over forecast meteorological conditions in determining ET fluxes at subseasonal leads. When the simple model’s ET anomalies are interpreted in terms of T2M anomalies, a similar conclusion is reached for T2M: soil moisture initialization explains much (about 50% in the eastern half of the continental United States) of the T2M anomaly values produced by the full GEOS S2S system at 16–30-day lead, and the T2M forecasts produced by the simple model capture about one-half of the skill attained by the full system. The simple model’s framework is particularly conducive to an analysis of uncertainty in forecasts. Drier soils are generally found to induce larger uncertainty in ET (and thus T2M) forecasts, a result linked to the functional form relating ET to soil moisture in the simple model and verified by an analysis of the ensemble spreads within the forecasts produced by the full GEOS S2S system.

scholarly journals Evaluation and Comparison of Noah and Pleim–Xiu Land Surface Models in MM5 Using GÖTE2001 Data: Spatial and Temporal Variations in Near-Surface Air Temperature

2007 ◽  
Vol 46 (10) ◽  
pp. 1587-1605 ◽  
Author(s):  
J-F. Miao ◽  
D. Chen ◽  
K. Borne
Keyword(s):  
Soil Moisture ◽  
Air Temperature ◽  
Land Surface ◽  
Model Performance ◽  
Surface Air Temperature ◽  
Near Surface ◽  
Surface Models ◽  
Urban Heat ◽  
Soil Moisture Initialization ◽  
Evident Difference

Abstract In this study, the performance of two advanced land surface models (LSMs; Noah LSM and Pleim–Xiu LSM) coupled with the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5), version 3.7.2, in simulating the near-surface air temperature in the greater Göteborg area in Sweden is evaluated and compared using the GÖTE2001 field campaign data. Further, the effects of different planetary boundary layer schemes [Eta and Medium-Range Forecast (MRF) PBLs] for Noah LSM and soil moisture initialization approaches for Pleim–Xiu LSM are investigated. The investigation focuses on the evaluation and comparison of diurnal cycle intensity and maximum and minimum temperatures, as well as the urban heat island during the daytime and nighttime under the clear-sky and cloudy/rainy weather conditions for different experimental schemes. The results indicate that 1) there is an evident difference between Noah LSM and Pleim–Xiu LSM in simulating the near-surface air temperature, especially in the modeled urban heat island; 2) there is no evident difference in the model performance between the Eta PBL and MRF PBL coupled with the Noah LSM; and 3) soil moisture initialization is of crucial importance for model performance in the Pleim–Xiu LSM. In addition, owing to the recent release of MM5, version 3.7.3, some experiments done with version 3.7.2 were repeated to reveal the effects of the modifications in the Noah LSM and Pleim–Xiu LSM. The modification to longwave radiation parameterizations in Noah LSM significantly improves model performance while the adjustment of emissivity, one of the vegetation properties, affects Pleim–Xiu LSM performance to a larger extent. The study suggests that improvements both in Noah LSM physics and in Pleim–Xiu LSM initialization of soil moisture and parameterization of vegetation properties are important.

scholarly journals Nature-based cooling potential: a multi-type green infrastructure evaluation in Toronto, Ontario, Canada

2021 ◽  
Author(s):  
Vidya Anderson ◽  
William A. Gough
Keyword(s):  
Urban Agriculture ◽  
Air Temperature ◽  
Green Infrastructure ◽  
Urban Climate ◽  
Surface Air Temperature ◽  
Green Roofs ◽  
Near Surface ◽  
Green Walls ◽  
The Impact ◽  
Agriculture Systems

AbstractThe application of green infrastructure presents an opportunity to mitigate rising temperatures using a multi-faceted ecosystems-based approach. A controlled field study in Toronto, Ontario, Canada, evaluates the impact of nature-based solutions on near surface air temperature regulation focusing on different applications of green infrastructure. A field campaign was undertaken over the course of two summers to measure the impact of green roofs, green walls, urban vegetation and forestry systems, and urban agriculture systems on near surface air temperature. This study demonstrates that multiple types of green infrastructure applications are beneficial in regulating near surface air temperature and are not limited to specific treatments. Widespread usage of green infrastructure could be a viable strategy to cool cities and improve urban climate.

scholarly journals Specifics of soil temperature under winter wheat canopy

2013 ◽  
Vol 43 (3) ◽  
pp. 209-223 ◽  
Author(s):  
Jana Krčmáŕová ◽  
Hana Stredová ◽  
Radovan Pokorný ◽  
Tomáš Stdŕeda
Keyword(s):  
Soil Moisture ◽  
Winter Wheat ◽  
Soil Temperature ◽  
Air Temperature ◽  
Surface Air Temperature ◽  
Soil Surface ◽  
Regression Equations ◽  
Experimental Plot ◽  
Near Surface ◽  
Soil Temperatures

Abstract The aim of this study was to evaluate the course of soil temperature under the winter wheat canopy and to determine relationships between soil temperature, air temperature and partly soil moisture. In addition, the aim was to describe the dependence by means of regression equations usable for phytopathological prediction models, crop development, and yield models. The measurement of soil temperatures was performed at the experimental field station ˇZabˇcice (Europe, the Czech Republic, South Moravia). The soil in the first experimental plot is Gleyic Fluvisol with 49-58% of the content particles measuring < 0.01 mm, in the second experimental plot, the soil is Haplic Chernozem with 31-32% of the content particles measuring < 0.01 mm. The course of soil temperature and its specifics were determined under winter wheat canopy during the main growth season in the course of three years. Automatic soil temperature sensors were positioned at three depths (0.05, 0.10 and 0.20 m under soil surface), air temperature sensor in 0.05 m above soil surface. Results of the correlation analysis showed that the best interrelationships between these two variables were achieved after a 3-hour delay for the soil temperature at 0.05 m, 5-hour delay for 0.10 m, and 8-hour delay for 0.20 m. After the time correction, the determination coefficient reached values from 0.75 to 0.89 for the depth of 0.05 m, 0.61 to 0.82 for the depth of 0.10 m, and 0.33 to 0.70 for the depth of 0.20 m. When using multiple regression with quadratic spacing (modeling hourly soil temperature based on the hourly near surface air temperature and hourly soil moisture in the 0.10-0.40 m profile), the difference between the measured and the model soil temperatures at 0.05 m was −2.16 to 2.37 ◦ C. The regression equation paired with alternative agrometeorological instruments enables relatively accurate modeling of soil temperatures (R2 = 0.93).

Influence of snowmelt on soil moisture and on near surface air temperature during winter–spring transition season

2017 ◽  
Vol 51 (4) ◽  
pp. 1295-1309 ◽  
Author(s):  
Jaison Thomas Ambadan ◽  
Aaron A. Berg ◽  
William J. Merryfield ◽  
Woo-Sung Lee
Keyword(s):  
Soil Moisture ◽  
Air Temperature ◽  
Surface Air Temperature ◽  
Near Surface ◽  
Transition Season ◽  
Spring Transition

Quantifying Spatiotemporal Variations of Soil Moisture Control on Surface Energy Balance and Near-Surface Air Temperature

2017 ◽  
Vol 30 (18) ◽  
pp. 7105-7124 ◽  
Author(s):  
Clemens Schwingshackl ◽  
Martin Hirschi ◽  
Sonia I. Seneviratne
Keyword(s):  
Soil Moisture ◽  
Air Temperature ◽  
Full Range ◽  
Surface Air Temperature ◽  
Temporal Variations ◽  
Heat Fluxes ◽  
Moisture Regime ◽  
Transitional Regime ◽  
Evaporative Fraction ◽  
Near Surface

Abstract Soil moisture plays a crucial role for the energy partitioning at Earth’s surface. Changing fractions of latent and sensible heat fluxes caused by soil moisture variations can affect both near-surface air temperature and precipitation. In this study, a simple framework for the dependence of evaporative fraction (the ratio of latent heat flux over net radiation) on soil moisture is used to analyze spatial and temporal variations of land–atmosphere coupling and its effect on near-surface air temperature. Using three different data sources (two reanalysis datasets and one combination of different datasets), three key parameters for the relation between soil moisture and evaporative fraction are estimated: 1) the frequency of occurrence of different soil moisture regimes, 2) the sensitivity of evaporative fraction to soil moisture in the transitional soil moisture regime, and 3) the critical soil moisture value that separates soil moisture- and energy-limited evapotranspiration regimes. The results show that about 30%–60% (depending on the dataset) of the global land area is in the transitional regime during at least half of the year. Based on the identification of transitional regimes, the effect of changes in soil moisture on near-surface air temperature is analyzed. Typical soil moisture variations (standard deviation) can impact air temperature by up to 1.1–1.3 K, while changing soil moisture over its full range in the transitional regime can alter air temperature by up to 6–7 K. The results emphasize the role of soil moisture for atmosphere and climate and constitute a useful benchmark for the evaluation of the respective relationships in Earth system models.

Impact of soil moisture initialization on boreal summer subseasonal forecasts: mid-latitude surface air temperature and heat wave events

2018 ◽  
Vol 52 (3-4) ◽  
pp. 1695-1709 ◽  
Author(s):  
Eunkyo Seo ◽  
Myong-In Lee ◽  
Jee-Hoon Jeong ◽  
Randal D. Koster ◽  
Siegfried D. Schubert ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Heat Wave ◽  
Air Temperature ◽  
Surface Air Temperature ◽  
Boreal Summer ◽  
Soil Moisture Initialization

scholarly journals Asymmetry in Subseasonal Surface Air Temperature Forecast Error with Respect to Soil Moisture Initialization

2021 ◽  
Author(s):  
Randal D. Koster ◽  
Anthony M. DeAngelis ◽  
Siegfried D. Schubert ◽  
Andrea M. Molod
Keyword(s):  
Soil Moisture ◽  
Air Temperature ◽  
Forecast Error ◽  
Surface Air Temperature ◽  
Forecast Bias ◽  
Temperature Forecast ◽  
Independent Observations ◽  
Moisture State ◽  
The Relationship ◽  
Soil Moisture Initialization

AbstractSoil moisture (W) helps control evapotranspiration (ET), and ET variations can in turn have a distinct impact on 2-m air temperature (T2M), given that increases in evaporative cooling encourage reduced temperatures. Soil moisture is accordingly linked to T2M, and realistic soil moisture initialization has, in previous studies, been shown to improve the skill of subseasonal T2M forecasts. The relationship between soil moisture and evapotranspiration, however, is distinctly nonlinear, with ET tending to increase with soil moisture in drier conditions and to be insensitive to soil moisture variations in wetter conditions. Here, through an extensive analysis of subseasonal forecasts produced with a state-of-the-art seasonal forecast system, this nonlinearity is shown to imprint itself on T2M forecast error in the conterminous United States in two unique ways: (i) the T2M forecast bias (relative to independent observations) induced by a negative precipitation bias tends to be larger for dry initializations, and (ii) on average, the unbiased root-mean-square error (ubRMSE) tends to be larger for dry initializations. Such findings can aid in the identification of forecasts of opportunity; taken a step further, they suggest a pathway for improving bias correction and uncertainty estimation in subseasonal T2M forecasts by conditioning each on initial soil moisture state.

scholarly journals Numerical simulations of the impact of the 20 March 2015 eclipse on UK weather

2016 ◽  
Vol 374 (2077) ◽  
pp. 20150218 ◽  
Author(s):  
P. A. Clark
Keyword(s):  
Boundary Layer ◽  
Air Temperature ◽  
Urban Areas ◽  
Weather Prediction ◽  
Sensible Heat Flux ◽  
Thermal Inertia ◽  
Surface Air Temperature ◽  
Atmospheric Effects ◽  
Near Surface ◽  
The Impact

Short lead-time forecasts using the operational United Kingdom variable-resolution (UKV) configuration of the Met Office’s numerical weather prediction model, with horizontal grid-length 1.5 km over the UK, with and without a representation of the 20 March 2015 eclipse, have been used to simulate the impact of the eclipse on UK weather. The major impact was surface-driven through changes to surface heat and moisture fluxes that changed the boundary-layer development. In cloud-free areas, the nocturnal stable boundary layer persisted or quickly re-established during the eclipse. Surface temperatures were reduced by 7–8°C, near-surface air temperature by 1–3°C, and near-surface winds were backed, typically by 20°. Impacts on wind speed were small and variable, and would have been very difficult to detect. Smaller impacts occurred beneath cloud. However, the impact was enhanced because most of the incoming radiation that reached the surface was driving surface sensible heat flux rather than moisture flux, and the near-surface air temperature impact (0.5–1° C ) agrees reasonably well with observations. The modelled impact of the eclipse was substantially reduced in urban areas due to their large thermal inertia. Experience from other assessments of the model suggests that this lack of response may be exaggerated. Surface impacts propagated upwards and downstream with time, resulting in a complex pattern of response, though generally near-surface temperature differences persisted for many hours after the eclipse. The impact on atmospheric pressure fields was insufficient to account for any significant perturbations to the wind field when compared with the direct impacts of surface stress and boundary-layer mixing. This article is part of the themed issue ‘Atmospheric effects of solar eclipses stimulated by the 2015 UK eclipse’.

scholarly journals Seasonally changing contribution of sea ice and snow cover to uncertainty in multi-decadal Eurasian surface air temperature trends based on CESM simulations

2021 ◽  
Author(s):  
Zhaomin Ding ◽  
Renguang Wu
Keyword(s):  
Sea Ice ◽  
Air Temperature ◽  
Western Siberia ◽  
Russian Far East ◽  
Far East ◽  
Surface Air Temperature ◽  
The Caspian Sea ◽  
Sea Ice Concentration ◽  
Northern Siberia ◽  
The Impact

AbstractThis study investigates the impact of sea ice and snow changes on surface air temperature (SAT) trends on the multidecadal time scale over the mid- and high-latitudes of Eurasia during boreal autumn, winter and spring based on a 30-member ensemble simulations of the Community Earth System Model (CESM). A dynamical adjustment method is used to remove the internal component of circulation-induced SAT trends. The leading mode of dynamically adjusted SAT trends is featured by same-sign anomalies extending from northern Europe to central Siberia and to the Russian Far East, respectively, during boreal spring and autumn, and confined to western Siberia during winter. The internally generated component of sea ice concentration trends over the Barents-Kara Seas contributes to the differences in the thermodynamic component of internal SAT trends across the ensemble over adjacent northern Siberia during all the three seasons. The sea ice effect is largest in autumn and smallest in winter. Eurasian snow changes contribute to the spread in dynamically adjusted SAT trends as well around the periphery of snow covered region by modulating surface heat flux changes. The snow effect is identified over northeast Europe-western Siberia in autumn, north of the Caspian Sea in winter, and over eastern Europe-northern Siberia in spring. The effects of sea ice and snow on the SAT trends are realized mainly by modulating upward shortwave and longwave radiation fluxes.

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