The impact of soil moisture variability on seasonal convective precipitation simulations. Part I: validation, feedbacks, and realistic initialisation

2013 ◽  
Vol 22 (4) ◽  
pp. 489-505 ◽  
Author(s):  
Samiro Khodayar ◽  
Norbert Kalthoff ◽  
Gerd Schädler
2005 ◽  
Vol 6 (5) ◽  
pp. 670-680 ◽  
Author(s):  
David M. Lawrence ◽  
Julia M. Slingo

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.


Hydrology ◽  
2018 ◽  
Vol 5 (3) ◽  
pp. 36 ◽  
Author(s):  
Paul Dirmeyer ◽  
Holly Norton

Variability and covariability of land properties (soil, vegetation and subsurface geology) and remotely sensed soil moisture over the southeast and south-central U.S. are assessed. The goal is to determine whether satellite soil moisture memory contains information regarding land properties, especially the distribution karst formations below the active soil column that have a bearing on land-atmosphere feedbacks. Local (within a few tens of km) statistics of land states and soil moisture are considered to minimize the impact of climatic variations, and the local statistics are then correlated across the domain to illuminate significant relationships. There is a clear correspondence between soil moisture memory and many land properties including karst distribution. This has implications for distributed land surface modeling, which has not considered preferential water flows through geologic formations. All correspondences are found to be strongest during spring and fall, and weak during summer, when atmospheric moisture demand appears to dominate soil moisture variability. While there are significant relationships between remotely-sensed soil moisture variability and land properties, it will be a challenge to use satellite data for terrestrial parameter estimation as there is often a great deal of correlation among soil, vegetation and karst property distributions.


1998 ◽  
Vol 21 (5) ◽  
pp. 375-384 ◽  
Author(s):  
Chulsang Yoo ◽  
Juan B. Valdés ◽  
Gerald R. North

2011 ◽  
Vol 137 (S1) ◽  
pp. 42-56 ◽  
Author(s):  
Christian Hauck ◽  
Christian Barthlott ◽  
Liane Krauss ◽  
Norbert Kalthoff

2020 ◽  
Vol 33 (15) ◽  
pp. 6511-6529
Author(s):  
Sanjiv Kumar ◽  
Matthew Newman ◽  
David M. Lawrence ◽  
Min-Hui Lo ◽  
Sathish Akula ◽  
...  

AbstractThe impact of land–atmosphere anomaly coupling on land variability is investigated using a new two-stage climate model experimental design called the “GLACE-Hydrology” experiment. First, as in the GLACE-CMIP5 experiment, twin sets of coupled land–atmosphere climate model (CAM5-CLM4.5) ensembles are performed, with each simulation using the same prescribed observed sea surface temperatures and radiative forcing for the years 1971–2014. In one set, land–atmosphere anomaly coupling is removed by prescribing soil moisture to follow the control model’s seasonally evolving soil moisture climatology (“land–atmosphere uncoupled”), enabling a contrast with the original control set (“land–atmosphere coupled”). Then, the atmospheric outputs from both sets of simulations are used to force land-only ensemble simulations, allowing investigation of the resulting soil moisture variability and memory under both the coupled and uncoupled scenarios. This study finds that in midlatitudes during boreal summer, land–atmosphere anomaly coupling significantly strengthens the relationship between soil moisture and evapotranspiration anomalies, both in amplitude and phase. This allows for decreased moisture exchange between the land surface and atmosphere, increasing soil moisture memory and often its variability as well. Additionally, land–atmosphere anomaly coupling impacts runoff variability, especially in wet and transition regions, and precipitation variability, although the latter has surprisingly localized impacts on soil moisture variability. As a result of these changes, there is an increase in the signal-to-noise ratio, and thereby the potential seasonal predictability, of SST-forced hydroclimate anomalies in many areas of the globe, especially in the midlatitudes. This predictability increase is greater for soil moisture than precipitation and has important implications for the prediction of drought.


PLoS ONE ◽  
2019 ◽  
Vol 14 (8) ◽  
pp. e0220457 ◽  
Author(s):  
Andrew Gillreath-Brown ◽  
Lisa Nagaoka ◽  
Steve Wolverton

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