Search Results

You are looking at 11 - 20 of 77 items for

  • Author or Editor: Paul A. Dirmeyer x
  • Refine by Access: All Content x
Clear All Modify Search
Hsin Hsu
and
Paul A. Dirmeyer

Abstract

The control of latent heat flux (LE) by soil moisture (SM) is a key process affecting the moisture and energy budgets at the land–atmosphere interface. SM–LE coupling relationships are conventionally examined using metrics involving temporal correlation. However, such a traditional linear approach, which fits a straight line across the full SM–LE space to evaluate the dependency, leaves out certain critical information: nonlinear SM–LE relationships and the long-recognized thresholds that lead to dramatically different behavior in different ranges of soil moisture, delineating a dry regime, a transitional regime of high sensitivity, and a wet (energy-limited) regime. Using data from climate models, reanalyses, and observationally constrained datasets, global patterns of SM–LE regimes are determined by segmented regression. Mutual information analysis is applied only for days when SM is in the transitional regime between critical points defining high sensitivity of LE to SM variations. Sensitivity is further decomposed into linear and nonlinear components. Results show discrepancies in the global patterns of existing SM regimes, but general consistencies among the linear and nonlinear components of SM–LE coupling. This implies that although models simulate differing surface hydroclimates, once SM is in the transitional regime, the locations where LE closely interacts with SM are well captured and resemble the conventional distribution of “hotspots” of land–atmosphere interactions. This indicates that only the transitional SM regime determines the strength of coupling, and attention should focused on when this regime occurs. This framework can also be applied to investigate extremes and the shifting surface hydroclimatology in a warming climate.

Significance Statement

Evaporation is sensitive to soil moisture only within a specific range that is neither too dry nor too wet. This transitional regime is examined to quantify how strongly soil moisture controls local evaporation. We identify the dry, transitional, and wet regimes across the globe, and the locations where each regime is experienced; the spatial patterns among climate models and observationally based datasets often show discrepancies. When we determine dependencies between soil moisture and evaporation only within the transitional regime, we find general consistency of locations having simple linear dependencies versus more complex nonlinear relationships. We conclude that although surface hydroclimates differ between climate models and observations, the locations where soil moisture can control evaporation are well captured. These results have potential application for improved forecasting and climate change assessment.

Full access
Paul A. Dirmeyer
and
Mei Zhao

Abstract

The potential role of the land surface state in improving predictions of seasonal climate is investigated with a coupled land–atmosphere climate model. Climate simulations for 18 boreal-summer seasons (1982–99) have been conducted with specified observed sea surface temperature (SST). The impact on prediction skill of the initial land surface state (interannually varying versus climatological soil wetness) and the effect of errors in downward surface fluxes (precipitation and longwave/shortwave radiation) over land are investigated with a number of parallel experiments. Flux errors are addressed by replacing the downward fluxes with observed values in various combinations to ascertain the separate roles of water and energy flux errors on land surface state variables, upward water and energy fluxes from the land surface, and the important climate variables of precipitation and near-surface air temperature.

Large systematic errors are found in the model, which are only mildly alleviated by the specification of realistic initial soil wetness. The model shows little skill in simulating seasonal anomalies of precipitation, but it does have skill in simulating temperature variations. Replacement of the downward surface fluxes has a clear positive impact on systematic errors, suggesting that the land–atmosphere feedback is helping to exacerbate climate drift. Improvement in the simulation of year-to-year variations in climate is even more evident. With flux replacement, the climate model simulates temperature anomalies with considerable skill over nearly all land areas, and a large fraction of the globe shows significant skill in the simulation of precipitation anomalies. This suggests that the land surface can communicate climate anomalies back to the atmosphere, given proper meteorological forcing. Flux substitution appears to have the largest benefit to improving precipitation skill over the Northern Hemisphere midlatitudes, whereas use of realistic land surface initial conditions improves skill to significant levels over regions of the Southern Hemisphere. Correlations between sets of integrations show that the model has a robust and systematic global response to SST anomalies.

Full access
David O. Benson
and
Paul A. Dirmeyer

Abstract

Increased heat-wave frequency across the United States has led to the need for improved predictability of heat-wave events. A detailed understanding of land–atmosphere interactions and the relationship between soil moisture and temperature extremes could provide useful information for prediction. This study identifies, for many locations, a threshold of soil moisture below which there is an increase in the sensitivity of atmospheric temperature to declining soil moisture. This shift to a hypersensitive regime causes the atmosphere to be more susceptible to atmospherically driven heat-wave conditions. The soil moisture breakpoint where the regime shift occurs is estimated using segmented regression applied to observations and reanalysis data. It is shown that as the soil gets drier, there is a concomitant change in the rate of decrease in latent heat flux and increase in sensible heat flux leading to a strong positive feedback of increased air temperature near the surface, which further dries out the soil. Central, southwestern, and southeastern parts of the United States seem to have regions of clear regime shifts, while the eastern part of the United States generally does not get dry enough to reveal significant breakpoints. Sensible heat flux is seen to be a primary driver of this increased temperature sensitivity aided by the drop in latent heat flux. An investigation of flux tower sites verifies the breakpoint–flux relationships found in reanalysis data. Accurate estimation of these breakpoints can contribute to improved heat-wave prediction.

Full access
David O. Benson
and
Paul A. Dirmeyer

Abstract

Thresholds of soil moisture exist below which the atmosphere becomes hypersensitive to land surface drying, inducing thermal feedbacks that can exacerbate heatwaves. Realistic representation of threshold transitions in forecast models could improve extreme heat predictability and understanding of the role of land–atmosphere coupling. This study evaluates the performance of several forecast models from the Subseasonal Experiment (SubX) and several prototype versions of the Unified Forecast System (UFS) in their representation of threshold transitions by validation against reanalysis data. A metric of skill (true skill score) is applied to soil moisture breakpoint values, which mark the transition to heatwave hypersensitivity for drying soils. Forecast models have poor skill at being initialized on the correct side of the breakpoint, but show improvement when normalized to account for deficiencies in their soil moisture climatologies. Regionally, models performed best in the U.S. Northwest and worst in the Southwest. They effectively capture the tendency of western regions to spend more summer days in the hypersensitive regime than the eastern United States. Models represent well extreme heat as a consequence of atmospheric initial state for the first week of the forecast, but struggle to represent the soil moisture feedback regime. Forecast models generally perform better at extreme heat prediction when they are already dry and in the hypersensitive regime, even when erroneously so, implying that errors or biases exist in model parameterizations. Nevertheless, composite analysis shows encouraging model performance of the “hit” category, suggesting that an improvement in soil moisture initialization could further improve extreme heat forecast skill.

Restricted access
Liang Chen
and
Paul A. Dirmeyer

ABSTRACT

Recent studies have shown the impacts of historical land-use land-cover changes (i.e., deforestation) on hot temperature extremes; contradictory temperature responses have been found between studies using observations and climate models. However, different characterizations of surface temperature are sometimes used in the assessments: land surface skin temperature T s is more commonly used in observation-based studies while near-surface air temperature T 2m is more often used in model-based studies. The inconsistent use of temperature variables is not inconsequential, and the relationship between deforestation and various temperature changes can be entangled, which complicates comparisons between observations and model simulations. In this study, the responses in the diurnal cycle of summertime T s and T 2m to deforestation are investigated using the Community Earth System Model. For the daily maximum, opposite responses are found in T s and T 2m. Due to decreased surface roughness after deforestation, the heat at the land surface cannot be efficiently dissipated into the air, leading to a warmer surface but cooler air. For the daily minimum, strong warming is found in T 2m, which exceeds daytime cooling and leads to overall warming in daily mean temperatures. After comparing several climate models, we find that the models agree in daytime land surface (T s ) warming, but different turbulent transfer characteristics produce discrepancies in T 2m. Our work highlights the need to investigate the diurnal cycles of temperature responses carefully in land-cover change studies. Furthermore, consistent consideration of temperature variables should be applied in future comparisons involving observations and climate models.

Full access
Subhadeep Halder
and
Paul A. Dirmeyer

Abstract

This observationally based study demonstrates the importance of the delayed hydrological response of snow cover and snowmelt over the Eurasian region and Tibet for variability of Indian summer monsoon rainfall during the first two months after onset. Using snow cover fraction and snow water equivalent data during 1967–2003, it is demonstrated that, although the snow-albedo effect is prevalent over western Eurasia, the delayed hydrological effect is strong and persistent over the eastern part. Long soil moisture memory and strong sensitivity of surface fluxes to soil moisture variations over eastern Asia and Tibet provide a mechanism for soil moisture anomalies generated by anomalies in winter and spring snowfall to affect rainfall during the initial months in summer. Dry soil moisture anomalies over the eastern Eurasian region associated with anomalous heating at the surface and midtroposphere help in anchoring of an anomalous upper-tropospheric “blocking” ridge around 100°E and its persistence. This not only leads to prolonged weakening of the subtropical westerly jet but also shifts its position southward of 30°N, followed by penetration of anomalous troughs in the westerlies into the Indian region. Simultaneously, intrusion of cold and dry air from the midlatitudes can reduce the convective instability and hence rainfall over India after the onset. Such a southward shift of the jet can also significantly weaken the vertical easterly wind shear over the Indian region in summer and lead to decrease in rainfall. This delayed hydrological effect also has the potential to modulate the snow–atmosphere coupling strength for temperature and precipitation in operational forecast models through soil moisture–evaporation–precipitation feedbacks.

Full access
Liang Chen
and
Paul A. Dirmeyer

Abstract

This study investigates the impacts of historical land-cover change on summer afternoon precipitation over North America using the Community Earth System Model. Using land–atmosphere coupling metrics, this study examines the sensitivity of afternoon atmospheric conditions to morning land surface states and fluxes that are altered by land-cover changes before and since 1850. The deforestation in the eastern United States prior to 1850 leads to increased latent but decreased sensible heat flux during the morning and a reduction in afternoon precipitation over the southern regions of the U.S. East Coast. The agricultural expansion over the Great Plains since preindustrial times shows similar effects on surface fluxes but results in a significant widespread increase in precipitation over the crop area. The coupling metrics exhibit a strong positive soil moisture–precipitation relationship over the Great Plains. Impacts of land-cover change on precipitation manifest through changes in rainfall frequency, rather than intensity, that are largely controlled by the distribution of CAPE as the trigger of convective precipitation. However, deforestation and later reforestation over the eastern United States, where coupling properties are different than the Great Plains, do not have as dominant an effect on afternoon precipitation. Additionally, precipitation over parts of the U.S. Southwest decreases in this model during the earlier period of East Coast deforestation, owing to changes in the large-scale circulation over North America driven by land-use changes prior to 1850.

Full access
Zhichang Guo
and
Paul A. Dirmeyer

Abstract

Recent studies in the Global Land–Atmosphere Coupling Experiment (GLACE) established a framework to estimate the extent to which anomalies in the land surface state (e.g., soil moisture) can affect rainfall generation and other atmospheric processes. Within this framework, a multiyear GLACE-type experiment is carried out with a coupled land–atmosphere general circulation model to examine the interannual variability of land–atmosphere coupling strength. Soil wetness with intermediate values are in the range at which rainfall generation, near-surface air temperature, and surface turbulent fluxes are most sensitive to soil moisture anomalies, and thus, land–atmosphere coupling strength peaks in this range. As a result, the “hot spots” with strong land–atmosphere coupling strength appear in regions with intermediate climatological soil wetness (e.g., transition zones between dry and wet climates), consistent with previous studies. Land–atmosphere coupling strength experiences significant year-to-year variation because of interannual variability of soil moisture and the local spatiotemporal evolution of hydrologic regime. Coupling strength over areas with dry (wet) climate is enhanced during wet (dry) years since the resultant soil wetness enters into the sensitive range from a relatively insensitive range, and soil moisture can have stronger potential impact on surface turbulent fluxes and convection. On the other hand, land–atmosphere coupling strength over areas with wet (dry) climate is weakened during wet (dry) years since the soil wetness moves further away from the sensitive range. This results in a positive correlation between the land–atmosphere coupling strength and soil moisture anomalies over areas with dry climate and a negative correlation over areas with wet climate.

Full access
Paul A. Dirmeyer
and
Subhadeep Halder

Abstract

Retrospective forecasts from CFSv2 are evaluated in terms of three elements of land–atmosphere coupling at subseasonal to seasonal time scales: sensitivity of the atmosphere to variations in land surface states, the magnitude of variability of land states and fluxes, and the memory or persistence of land surface anomalies. The Northern Hemisphere spring and summer seasons are considered for the period 1982–2009. Ensembles are constructed from all available pairings of initial land and atmosphere/ocean states taken from the Climate Forecast System Reanalysis at the start of April, May, and June among the 28 years, so that the effect of initial land states on the evolving forecasts can be assessed. Finally, improvement and continuance of forecast skill derived from accurate land surface initialization is related to the three coupling elements. It is found that soil moisture memory is the most broadly important element for significant improvement of realistic land initialization on forecast skill. However, coupling strength manifested through the elements of sensitivity and variability are necessary to realize the potential predictability provided by memory of initial land surface anomalies. Even though there is clear responsiveness of surface heat fluxes, near-surface temperature, humidity, and daytime boundary layer development to variations in soil moisture over much of the globe, precipitation in CFSv2 is unresponsive. Failure to realize potential predictability from land surface states could be due to unfavorable atmospheric stability or circulation states; poor quality of what is considered realistic soil moisture analyses; and errors in the land surface model, atmospheric model, or their coupled interaction.

Full access
Abedeh Abdolghafoorian
and
Paul A. Dirmeyer

Abstract

The interactions between land and atmosphere (with terrestrial and atmospheric coupling segments) play a significant role in weather and climate. A predominant segment of land–atmosphere (LA) feedbacks is the coupling between soil moisture (SM) and surface heat fluxes, the terrestrial coupling leg. The lack of high-quality, long-term, globally distributed observations, however, has hindered a robust, realistic identification of the terrestrial leg strength on a global scale. This exploratory study provides insight into how SM signals are translated into surface flux signals through the construction of a global depiction of the terrestrial leg from several recently developed global, gridded, observationally and satellite-based datasets. The feasibility of producing global gridded estimates of LA coupling metrics is explored. Five weather and climate models used for subseasonal to seasonal forecasting are confronted with the observational estimates to discern discrepancies that may affect their ability to predict phenomena related to LA feedbacks, such as drought or heat waves. The terrestrial feedback leg from observations corroborates the “hot spots” of LA coupling found in modeling studies, but the variances in daily time series of surface fluxes differ markedly. Better agreement and generally higher confidence are seen in metrics using latent heat flux than sensible heat flux. Observational metrics allow for clear stratification of model fidelity that is consistent across seasons, despite observational uncertainty. The results highlight the impact of SM on partitioning available surface energy and illustrate the potential of global observationally based datasets for the assessment of such relationships in weather and climate models.

Full access