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

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.

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The Second Phase of the Global Land–Atmosphere Coupling Experiment: Soil Moisture Contributions to Subseasonal Forecast Skill

Journal of Hydrometeorology ◽

10.1175/2011jhm1365.1 ◽

2011 ◽

Vol 12 (5) ◽

pp. 805-822 ◽

Cited By ~ 215

Author(s):

R. D. Koster ◽

S. P. P. Mahanama ◽

T. J. Yamada ◽

Gianpaolo Balsamo ◽

A. A. Berg ◽

...

Keyword(s):

Soil Moisture ◽

Air Temperature ◽

Rain Gauge ◽

Forecast Skill ◽

Precipitation Forecast ◽

Boreal Summer ◽

Second Phase ◽

Global Land ◽

Soil Moisture Initialization ◽

Coupling Experiment

Abstract The second phase of the Global Land–Atmosphere Coupling Experiment (GLACE-2) is a multi-institutional numerical modeling experiment focused on quantifying, for boreal summer, the subseasonal (out to two months) forecast skill for precipitation and air temperature that can be derived from the realistic initialization of land surface states, notably soil moisture. An overview of the experiment and model behavior at the global scale is described here, along with a determination and characterization of multimodel “consensus” skill. The models show modest but significant skill in predicting air temperatures, especially where the rain gauge network is dense. Given that precipitation is the chief driver of soil moisture, and thereby assuming that rain gauge density is a reasonable proxy for the adequacy of the observational network contributing to soil moisture initialization, this result indeed highlights the potential contribution of enhanced observations to prediction. Land-derived precipitation forecast skill is much weaker than that for air temperature. The skill for predicting air temperature, and to some extent precipitation, increases with the magnitude of the initial soil moisture anomaly. GLACE-2 results are examined further to provide insight into the asymmetric impacts of wet and dry soil moisture initialization on skill.

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

Journal of Hydrometeorology ◽

10.1175/jhm-d-21-0022.1 ◽

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.

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

Journal of Hydrometeorology ◽

10.1175/jhm-d-20-0007.1 ◽

2020 ◽

Vol 21 (8) ◽

pp. 1705-1722 ◽

Cited By ~ 1

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.

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Impact of Subsurface Temperature Variability on Surface Air Temperature Variability: An AGCM Study

Journal of Hydrometeorology ◽

10.1175/2008jhm949.1 ◽

2008 ◽

Vol 9 (4) ◽

pp. 804-815 ◽

Cited By ~ 20

Author(s):

Sarith P. P. Mahanama ◽

Randal D. Koster ◽

Rolf H. Reichle ◽

Max J. Suarez

Keyword(s):

Surface Temperature ◽

Soil Temperature ◽

Air Temperature ◽

Seasonal Cycle ◽

Surface Air Temperature ◽

Temperature Variability ◽

Climate System ◽

Boreal Summer ◽

Temperature Anomalies ◽

Subsurface Soil

Abstract Anomalous atmospheric conditions can lead to surface temperature anomalies, which in turn can lead to temperature anomalies in the subsurface soil. The subsurface soil temperature (and the associated ground heat content) has significant memory—the dissipation of a temperature anomaly may take weeks to months—and thus subsurface soil temperature may contribute to the low-frequency variability of energy and water variables elsewhere in the system. The memory may even provide some skill to subseasonal and seasonal forecasts. This study uses three long-term AGCM experiments to isolate the contribution of subsurface soil temperature variability to variability elsewhere in the climate system. The first experiment consists of a standard ensemble of Atmospheric Model Intercomparison Project (AMIP)-type simulations in which the subsurface soil temperature variable is allowed to interact with the rest of the system. In the second experiment, the coupling of the subsurface soil temperature to the rest of the climate system is disabled; that is, at each grid cell, the local climatological seasonal cycle of subsurface soil temperature (as determined from the first experiment) is prescribed. Finally, a climatological seasonal cycle of sea surface temperature (SST) is prescribed in the third experiment. Together, the three experiments allow the isolation of the contributions of variable SSTs, interactive subsurface soil temperature, and chaotic atmospheric dynamics to meteorological variability. The results show that allowing an interactive subsurface soil temperature does, indeed, significantly increase surface air temperature variability and memory in most regions. In many regions, however, the impact is negligible, particularly during boreal summer.

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Numerical Simulations of Effects of Soil Moisture and Modification by Mountains over New Zealand in Summer

Monthly Weather Review ◽

10.1175/2010mwr3324.1 ◽

2011 ◽

Vol 139 (2) ◽

pp. 494-510 ◽

Cited By ~ 11

Author(s):

Yang Yang ◽

Michael Uddstrom ◽

Mike Revell ◽

Phil Andrews ◽

Hilary Oliver ◽

...

Keyword(s):

Soil Moisture ◽

New Zealand ◽

Moisture Content ◽

Air Temperature ◽

Land Surface ◽

Soil Moisture Content ◽

Surface Air Temperature ◽

Shortwave Radiation ◽

Lower Sensitivity ◽

The South

Abstract Historically most soil moisture–land surface impact studies have focused on continents because of the important forecasting and climate implications involved. For a relatively small isolated mountainous landmass in the ocean such as New Zealand, these impacts have received less attention. This paper addresses some of these issues for New Zealand through numerical experiments with a regional configuration of the Met Office Unified Model atmospheric model. Two pairs of idealized simulations with only contrasting dry or wet initial soil moisture over a 6-day period in January 2004 were conducted, with one pair using realistic terrain and the other pair flat terrain. For the mean of the 6 days, the differences in the simulated surface air temperature between the dry and moist cases were 3–5 K on the leeside slopes and 1–2 K on the windward slopes and the central leeside coastal region of the South Island in the afternoon. This quite nonuniform response in surface air temperature to a uniformly distributed soil moisture content and soil type is mainly attributed to modification of the effects of soil moisture by mountains through two different processes: 1) spatial variation in cloud coverage across the mountains ranges leading to more shortwave radiation at ground surface on the leeside slope than the windward slope, and 2) the presence of a dynamically and thermally induced onshore flow on the leeside coast bringing in air with a lower sensitivity to soil moisture. The response of local winds to soil moisture content is through direct or indirect effects. The direct effect is due to the thermal contrast between land and sea/land shown for the leeside solenoidal circulations, and the indirect effect is through the weakening of the upstream blocking of the South Island for dryer soils shown by the weakening and onshore shift of the upstream deceleration and forced ascent of incoming airflow.

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Soil Moisture Variability in India: Relationship of Land Surface–Atmosphere Fields Using Maximum Covariance Analysis

Remote Sensing ◽

10.3390/rs11030335 ◽

2019 ◽

Vol 11 (3) ◽

pp. 335 ◽

Cited By ~ 9

Author(s):

Kishore Pangaluru ◽

Isabella Velicogna ◽

Geruo A ◽

Yara Mohajerani ◽

Enrico Ciracì ◽

...

Keyword(s):

Soil Moisture ◽

Air Temperature ◽

Land Surface ◽

Water Storage ◽

Surface Air Temperature ◽

Covariance Analysis ◽

Positive Trend ◽

Total Water ◽

Maximum Covariance Analysis ◽

Surface Atmosphere

This study investigates the spatial and temporal variability of the soil moisture in India using Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) gridded datasets from June 2002 to April 2017. Significant relationships between soil moisture and different land surface–atmosphere fields (Precipitation, surface air temperature, total cloud cover, and total water storage) were studied, using maximum covariance analysis (MCA) to extract dominant interactions that maximize the covariance between two fields. The first leading mode of MCA explained 56%, 87%, 81%, and 79% of the squared covariance function (SCF) between soil moisture with precipitation (PR), surface air temperature (TEM), total cloud count (TCC), and total water storage (TWS), respectively, with correlation coefficients of 0.65, −0.72, 0.71, and 0.62. Furthermore, the covariance analysis of total water storage showed contrasting patterns with soil moisture, especially over northwest, northeast, and west coast regions. In addition, the spatial distribution of seasonal and annual trends of soil moisture in India was estimated using a robust regression technique for the very first time. For most regions in India, significant positive trends were noticed in all seasons. Meanwhile, a small negative trend was observed over southern India. The monthly mean value of AMSR soil moisture trend revealed a significant positive trend, at about 0.0158 cm3/cm3 per decade during the period ranging from 2002 to 2017.

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Projected Changes in Daily Variability and Seasonal Cycle of Near-Surface Air Temperature over the Globe during the Twenty-First Century

Journal of Climate ◽

10.1175/jcli-d-19-0438.1 ◽

2019 ◽

Vol 32 (24) ◽

pp. 8537-8561 ◽

Cited By ~ 6

Author(s):

Jiao Chen ◽

Aiguo Dai ◽

Yaocun Zhang

Keyword(s):

Sea Ice ◽

Air Temperature ◽

Seasonal Cycle ◽

Surface Air Temperature ◽

First Century ◽

The Arctic ◽

Boreal Summer ◽

High Latitudes ◽

Low Latitudes ◽

Twenty First Century

Abstract Increases in atmospheric greenhouse gases will not only raise Earth’s temperature but may also change its variability and seasonal cycle. Here CMIP5 model data are analyzed to quantify these changes in surface air temperature (Tas) and investigate the underlying processes. The models capture well the mean Tas seasonal cycle and variability and their changes in reanalysis, which shows decreasing Tas seasonal amplitudes and variability over the Arctic and Southern Ocean from 1979 to 2017. Daily Tas variability and seasonal amplitude are projected to decrease in the twenty-first century at high latitudes (except for boreal summer when Tas variability increases) but increase at low latitudes. The day of the maximum or minimum Tas shows large delays over high-latitude oceans, while it changes little at low latitudes. These Tas changes at high latitudes are linked to the polar amplification of warming and sea ice loss, which cause larger warming in winter than summer due to extra heating from the ocean during the cold season. Reduced sea ice cover also decreases its ability to cause Tas variations, contributing to the decreased Tas variability at high latitudes. Over low–midlatitude oceans, larger increases in surface evaporation in winter than summer (due to strong winter winds, strengthened winter winds in the Southern Hemisphere, and increased winter surface humidity gradients over the Northern Hemisphere low latitudes), coupled with strong ocean mixing in winter, lead to smaller surface warming in winter than summer and thus increased seasonal amplitudes there. These changes result in narrower (wider) Tas distributions over the high (low) latitudes, which may have important implications for other related fields.

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