scholarly journals A Revised Framework for Analyzing Soil Moisture Memory in Climate Data: Derivation and Interpretation

2012 ◽  
Vol 13 (1) ◽  
pp. 404-412 ◽  
Author(s):  
Sonia I. Seneviratne ◽  
Randal D. Koster
Keyword(s):  
Soil Moisture ◽  
General Circulation ◽  
Climate Models ◽  
Circulation Model ◽  
Climate Data ◽  
Time Step ◽  
Initial Soil Moisture ◽  
Initial Soil ◽  
Soil Moisture Variability ◽  
Moisture Variability

Abstract A revised framework for the analysis of soil moisture memory characteristics of climate models and observational data is derived from the approach proposed by Koster and Suarez. The resulting equation allows the expression of the month-to-month soil moisture autocorrelation as a function of 1) the initial soil moisture variability, 2) the (atmospheric) forcing variability over the considered time period, 3) the correlation between initial soil moisture and subsequent forcing, 4) the sensitivity of evaporation to soil moisture, and 5) the sensitivity of runoff to soil moisture. A specific new feature is the disentangling of the roles of initial soil moisture variability and forcing variability, which were both (for the latter indirectly) contributing to the seasonality term of the original formulation. In addition, a version of the framework entirely based on explicit equations for the underlying relationships (i.e., independent of soil moisture statistics at the following time step) is proposed. The validity of the derived equation is exemplified with atmospheric general circulation model (AGCM) simulations from the Global Land–Atmosphere Coupling Experiment (GLACE).

scholarly journals Weak Land–Atmosphere Coupling Strength in HadAM3: The Role of Soil Moisture Variability

2005 ◽  
Vol 6 (5) ◽  
pp. 670-680 ◽  
Author(s):  
David M. Lawrence ◽  
Julia M. Slingo
Keyword(s):  
Boundary Layer ◽  
Soil Moisture ◽  
Coupling Strength ◽  
General Circulation ◽  
General Circulation Models ◽  
Soil Conditions ◽  
Wide Range ◽  
The Impact ◽  
Soil Moisture Variability ◽  
Moisture Variability

Abstract A recent model intercomparison, the Global Land–Atmosphere Coupling Experiment (GLACE), showed that there is a wide range of land–atmosphere coupling strengths, or the degree that soil moisture affects the generation of precipitation, amongst current atmospheric general circulation models (AGCMs). Coupling strength in the Hadley Centre atmosphere model (HadAM3) is among the weakest of all AGCMs considered in GLACE. Reasons for the weak HadAM3 coupling strength are sought here. In particular, the impact of pervasive saturated soil conditions and low soil moisture variability on coupling strength is assessed. It is found that when the soil model is modified to reduce the occurrence of soil moisture saturation and to encourage soil moisture variability, the soil moisture–precipitation feedback remains weak, even though the relationship between soil moisture and evaporation is strengthened. Composites of the diurnal cycle, constructed relative to soil moisture, indicate that the model can simulate key differences in boundary layer development over wet versus dry soils. In particular, the influence of wet or dry soil on the diurnal cycles of Bowen ratio, boundary layer height, and total heat flux are largely consistent with the observed influence of soil moisture on these properties. However, despite what appears to be successful simulation of these key aspects of the indirect soil moisture–precipitation feedback, the model does not capture observed differences for wet and dry soils in the daily accumulation of boundary layer moist static energy, a crucial feature of the feedback mechanism.

scholarly journals Assessment of soil moisture fields from imperfect climate models with uncertain satellite observations

2009 ◽  
Vol 6 (2) ◽  
pp. 2733-2750 ◽  
Author(s):  
G. Schumann ◽  
D. J. Lunt ◽  
P. J. Valdes ◽  
R. A. M. de Jeu ◽  
K. Scipal ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
General Circulation ◽  
Climate Models ◽  
Climate Model ◽  
Hydrological Cycle ◽  
Circulation Model ◽  
Data Uncertainty ◽  
Limited Area

Abstract. We demonstrate that global satellite products can be used to evaluate climate model soil moisture predictions but conclusions should be drawn with care. The quality of a limited area climate model (LAM) was compared to a general circulation model (GCM) using soil moisture data from two different Earth observing satellites within a model validation scheme that copes with the presence of uncertain data. Results showed that in the face of imperfect models and data, it is difficult to investigate the quality of current land surface schemes in simulating hydrology accurately. Nevertheless, a LAM provides, in general, a better representation of spatial patterns and dynamics of soil moisture. However, in months when data uncertainty is higher, particularly in colder months and in periods when vegetation cover and soil moisture are out of phase (e.g. August in the case of Western Europe), it is not possible to draw firm conclusions about model acceptability. Our work indicates that a higher resolution LAM has more benefits to soil moisture prediction than are due to the resolution alone and can be attributed to an overall intensification of the hydrological cycle relative to the GCM.

scholarly journals Mineral dust modelling with MADE3 in EMAC v2.54

2020 ◽  
Author(s):  
Christof G. Beer ◽  
Johannes Hendricks ◽  
Mattia Righi ◽  
Bernd Heinold ◽  
Ina Tegen ◽  
...  
Keyword(s):  
Atmospheric Chemistry ◽  
General Circulation ◽  
Climate Models ◽  
Mineral Dust ◽  
Dust Emission ◽  
Circulation Model ◽  
Dust Particles ◽  
Model Resolution ◽  
Time Step ◽  
Dust Emissions

Abstract. Mineral dust particles play an important role in the climate system, by e.g. interacting with solar and terrestrial radiation or facilitating the formation of cloud droplets. Additionally, dust particles can act as very efficient ice nuclei in cirrus clouds. Many Global Chemistry Climate Models (GCCMs) use prescribed monthly mean mineral dust emissions representative of a specific year, based on a climatology. It was hypothesized that using dust emission climatologies may lead to misrepresentations of strong dust burst episodes, resulting in a negative bias of model dust concentrations compared to observations for these episodes. Here, we apply the aerosol microphysics submodel MADE3 (Modal Aerosol Dynamics model for Europe, adapted for global applications, third generation) as part of the ECHAM/MESSy Atmospheric Chemistry (EMAC) general circulation model. We employ two different representations of mineral dust for our model simulations: i) a prescribed monthly-mean climatology of dust emissions representative of the year 2000; ii) an online dust parametrization which calculates wind-driven mineral dust emissions at every model time-step. We evaluate model results for these two dust representations by comparison with observations of aerosol optical depth from ground-based station data. The model results show a better agreement with the observations for strong dust burst events when using the online dust representation compared to the prescribed dust emissions setup. Furthermore, we analyse the effect of increasing the vertical and horizontal model resolution on mineral dust properties in our model. The model is evaluated against airborne in situ measurements performed during the SALTRACE mineral dust campaign (Saharan Aerosol Long-range Transport and Aerosol-Cloud Interaction Experiment, June/July 2013), i.e. observations of dust transported from the Sahara to the Caribbean. Results show that an increased horizontal and vertical model resolution is able to better represent the spatial distribution of airborne mineral dust, especially in the upper troposphere (above 400 hPa). Additionally, we analyse the effect of varying assumptions for the size distribution of emitted dust. The results of this study will help to identify the model setup best suited for future studies and to further improve the representation of mineral dust particles in EMAC-MADE3.

Predictability of Seasonal Streamflow and Soil Moisture in National Water Model and a Humid Alabama–Coosa–Tallapoosa River Basin

2020 ◽  
Vol 21 (7) ◽  
pp. 1447-1467 ◽  
Author(s):  
Yanan Duan ◽  
Sanjiv Kumar
Keyword(s):  
Soil Moisture ◽  
Water Model ◽  
Moisture Condition ◽  
Soil Moisture Condition ◽  
Streamflow Forecast ◽  
Initial Soil Moisture ◽  
Initial Soil ◽  
Seasonal Streamflow ◽  
Soil Moisture Variability ◽  
National Water

AbstractThis study investigates the potential predictability of streamflow and soil moisture in the Alabama–Coosa–Tallapoosa (ACT) river basin in the southeastern United States. The study employs the state-of-the-art National Water Model (NWM) and compares the effects of initial soil moisture condition with those of seasonal climate anomalies on streamflow and soil moisture forecast skills. We have designed and implemented seasonal streamflow forecast ensemble experiments following the methodology suggested by Dirmeyer et al. The study also compares the soil moisture variability in the NWM with in situ measurements and remote sensing data from the Soil Moisture Active and Passive (SMAP) satellite. The NWM skillfully simulates the observed streamflow in the ACT basin. The soil moisture variability is 46% smaller in the NWM compared with the SMAP data, mainly due to a weaker amplitude of the seasonal cycle. This study finds that initial soil moisture condition is a major source of predictability for the seasonal streamflow forecast. The contribution of the initial soil moisture condition is comparable or even higher than that of seasonal climate anomaly effects in dry seasons. In the boreal summer season, the initial soil moisture condition contributes to 65% and 48% improvements in the seasonal streamflow and soil moisture forecast skills, respectively. This study attributes a greater improvement in the streamflow forecast skill to the lag effects between the soil moisture and streamflow anomalies. The results of this study can inform the development and improvement of the operational streamflow forecasting system.

scholarly journals Modelling mineral dust emissions and atmospheric dispersion with MADE3 in EMAC v2.54

2020 ◽  
Vol 13 (9) ◽  
pp. 4287-4303
Author(s):  
Christof G. Beer ◽  
Johannes Hendricks ◽  
Mattia Righi ◽  
Bernd Heinold ◽  
Ina Tegen ◽  
...  
Keyword(s):  
Atmospheric Chemistry ◽  
General Circulation ◽  
Climate Models ◽  
Mineral Dust ◽  
Dust Emission ◽  
Circulation Model ◽  
Dust Particles ◽  
Model Resolution ◽  
Time Step ◽  
Dust Emissions

Abstract. It was hypothesized that using mineral dust emission climatologies in global chemistry climate models (GCCMs), i.e. prescribed monthly-mean dust emissions representative of a specific year, may lead to misrepresentations of strong dust burst events. This could result in a negative bias of model dust concentrations compared to observations for these episodes. Here, we apply the aerosol microphysics submodel MADE3 (Modal Aerosol Dynamics model for Europe, adapted for global applications, third generation) as part of the ECHAM/MESSy Atmospheric Chemistry (EMAC) general circulation model. We employ two different representations of mineral dust emissions for our model simulations: (i) a prescribed monthly-mean climatology of dust emissions representative of the year 2000 and (ii) an online dust parametrization which calculates wind-driven mineral dust emissions at every model time step. We evaluate model results for these two dust representations by comparison with observations of aerosol optical depth from ground-based station data. The model results show a better agreement with the observations for strong dust burst events when using the online dust representation compared to the prescribed dust emissions setup. Furthermore, we analyse the effect of increasing the vertical and horizontal model resolution on the mineral dust properties in our model. We compare results from simulations with T42L31 and T63L31 model resolution (2.8∘×2.8∘ and 1.9∘×1.9∘ in latitude and longitude, respectively; 31 vertical levels) with the reference setup (T42L19). The different model versions are evaluated against airborne in situ measurements performed during the SALTRACE mineral dust campaign (Saharan Aerosol Long-range Transport and Aerosol-Cloud Interaction Experiment, June–July 2013), i.e. observations of dust transported from the Sahara to the Caribbean. Results show that an increased horizontal and vertical model resolution is able to better represent the spatial distribution of airborne mineral dust, especially in the upper troposphere (above 400 hPa). Additionally, we analyse the effect of varying assumptions for the size distribution of emitted dust but find only a weak sensitivity concerning these changes. The results of this study will help to identify the model setup best suited for future studies and to further improve the representation of mineral dust particles in EMAC-MADE3.

scholarly journals A geospatial method for estimating soil moisture variability in prehistoric agricultural landscapes

PLoS ONE ◽  
2019 ◽  
Vol 14 (8) ◽  
pp. e0220457 ◽  
Author(s):  
Andrew Gillreath-Brown ◽  
Lisa Nagaoka ◽  
Steve Wolverton
Keyword(s):  
Soil Moisture ◽  
Agricultural Landscapes ◽  
Soil Moisture Variability ◽  
Moisture Variability

Tropical Atmospheric Variability Forced by Oceanic Internal Variability

2007 ◽  
Vol 20 (4) ◽  
pp. 765-771 ◽  
Author(s):  
Markus Jochum ◽  
Clara Deser ◽  
Adam Phillips
Keyword(s):  
General Circulation ◽  
Climate Models ◽  
Rainfall Variability ◽  
Circulation Model ◽  
Internal Variability ◽  
Tropical Pacific ◽  
Atmospheric Variability ◽  
Instability Waves ◽  
Tropical Instability Waves ◽  
The Tropical Pacific

Abstract Atmospheric general circulation model experiments are conducted to quantify the contribution of internal oceanic variability in the form of tropical instability waves (TIWs) to interannual wind and rainfall variability in the tropical Pacific. It is found that in the tropical Pacific, along the equator, and near 25°N and 25°S, TIWs force a significant increase in wind and rainfall variability from interseasonal to interannual time scales. Because of the stochastic nature of TIWs, this means that climate models that do not take them into account will underestimate the strength and number of extreme events and may overestimate forecast capability.

Initial soil moisture retrievals from the METOP-A Advanced Scatterometer (ASCAT)

2007 ◽  
Vol 34 (20) ◽  
Author(s):  
Zoltan Bartalis ◽  
Wolfgang Wagner ◽  
Vahid Naeimi ◽  
Stefan Hasenauer ◽  
Klaus Scipal ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Initial Soil Moisture ◽  
Initial Soil

Exploring the potential of soil moisture reanalysis data for improving the identification of regional landslide triggering thresholds

2021 ◽  
Author(s):  
Nunziarita Palazzolo ◽  
David J. Peres ◽  
Enrico Creaco ◽  
Antonino Cancelliere
Keyword(s):  
Soil Moisture ◽  
Rainfall Event ◽  
Rainfall Thresholds ◽  
Rainfall Duration ◽  
Soil Moisture Data ◽  
Initial Soil Moisture ◽  
Initial Soil ◽  
Different Depths ◽  
Moisture Conditions ◽  
Landslide Triggering

<p>Landslide triggering thresholds provide the rainfall conditions that are likely to trigger landslides, therefore their derivation is key for prediction purposes. Different variables can be considered for the identification of thresholds, which commonly are in the form of a power-law relationship linking rainfall event duration and intensity or cumulated event rainfall. The assessment of such rainfall thresholds generally neglects initial soil moisture conditions at each rainfall event, which are indeed a predisposing factor that can be crucial for the proper definition of the triggering scenario. Thus, more studies are needed to understand whether and the extent to which the integration of the initial soil moisture conditions with rainfall thresholds could improve the conventional precipitation-based approach. Although soil moisture data availability has hindered such type of studies, yet now this information is increasingly becoming available at the large scale, for instance as an output of meteorological reanalysis initiatives. In particular, in this study, we focus on the use of the ERA5-Land reanalysis soil moisture dataset. Climate reanalysis combines past observations with models in order to generate consistent time series and the ERA5-Land data actually provides the volume of water in soil layer at different depths and at global scale. Era5-Land project is, indeed, a global dataset at 9 km horizontal resolution in which atmospheric data are at an hourly scale from 1981 to present. Volumetric soil water data are available at four depths ranging from the surface level to 289 cm, namely 0-7 cm, 7-28 cm, 28-100 cm, and 100-289 cm. After collecting the rainfall and soil moisture data at the desired spatio-temporal resolution, together with the target data discriminating landslide and no-landslide events, we develop automatic triggering/non-triggering classifiers and test their performances via confusion matrix statistics. In particular, we compare the performances associated with the following set of precursors: a) event rainfall duration and depth (traditional approach), b) initial soil moisture at several soil depths, and c) event rainfall duration and depth and initial soil moisture at different depths. The approach is applied to the Oltrepò Pavese region (northern Italy), for which the historical observed landslides have been provided by the IFFI project (Italian landslides inventory). Results show that soil moisture may allow an improvement in the performances of the classifier, but that the quality of the landslide inventory is crucial.</p>

scholarly journals Changes of Variability in Response to Increasing Greenhouse Gases. Part II: Hydrology

2009 ◽  
Vol 22 (22) ◽  
pp. 6089-6103 ◽  
Author(s):  
Richard T. Wetherald
Keyword(s):  
Soil Moisture ◽  
Greenhouse Gases ◽  
General Circulation ◽  
Circulation Model ◽  
Early Spring ◽  
Precipitation Rate ◽  
Late Winter ◽  
Annual Data ◽  
Geophysical Fluid Dynamics Laboratory ◽  
The Mean

Abstract This paper examines hydrological variability and its changes in two different versions of a coupled ocean–atmosphere general circulation model developed at the National Oceanic and Atmospheric Administration/Geophysical Fluid Dynamics Laboratory and forced with estimates of future increases of greenhouse gas and aerosol concentrations. This paper is the second part, documenting potential changes in variability as greenhouse gases increase. The variance changes are examined using an ensemble of 8 transient integrations for an older model version and 10 transient integrations for a newer model. Monthly and annual data are used to compute the mean and variance changes. Emphasis is placed on computing and analyzing the variance changes for the middle of the twenty-first century and compared with those found in the respective control integrations. The hydrologic cycle intensifies because of the increase of greenhouse gases. In general, precipitation variance increases in most places. This is the case virtually everywhere the mean precipitation rate increases and many places where the precipitation decreases. The precipitation rate variance decreases in the subtropics, where the mean precipitation rate also decreases. The increased precipitation rate and variance, in middle to higher latitudes during late fall, winter, and early spring leads to increased runoff and its variance during that period. On the other hand, the variance changes of soil moisture are more complicated, because soil moisture has both a lower and upper bound that tends to reduce its fluctuations. This is particularly true in middle to higher latitudes during winter and spring, when the soil moisture is close to its saturation value at many locations. Therefore, changes in its variance are limited. Soil moisture variance change is positive during the summer, when the mean soil moisture decreases and is close to the middle of its allowable range. In middle to high northern latitudes, an increase in runoff and its variance during late winter and spring plus the decrease in soil moisture and its variance during summer lend support to the hypothesis stated in other publications that a warmer climate can cause an increasing frequency of both excessive discharge and drier events, depending on season and latitude.

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