Geology topics

Dennis P. Lettenmaier

Publications and source records attributed to Dennis P. Lettenmaier.

7 recordsLinked to original sources

USGS2017

Terrestrial ecosystem model performance in simulating productivity and its vulnerability to climate change in the northern permafrost region

Realistic projection of future climate-carbon (C) cycle feedbacks requires better understanding and an improved representation of the C cycle in permafrost regions in the current generation of Earth system models. Here we evaluated 10 terrestrial ecosystem models for their estimates of net primary productivity (NPP) and responses to historical climate change in permafrost regions in the Northern Hemisphere. In comparison with the satellite estimate from the Moderate Resolution Imaging Spectroradiometer (MODIS; 246 ± 6 g C m −2 yr −1 ), most models produced higher NPP (309 ± 12 g C m −2 yr −1 ) over the permafrost region during 2000–2009. By comparing the simulated gross primary productivity (GPP) with a flux tower-based database, we found that although mean GPP among the models was only overestimated by 10% over 1982–2009, there was a twofold discrepancy among models (380 to 800 g C m −2 yr −1 ), which mainly resulted from differences in simulated maximum monthly GPP (GPP max ). Most models overestimated C use efficiency (CUE) as compared to observations at both regional and site levels. Further analysis shows that model variability of GPP and CUE are nonlinearly correlated to variability in specific leaf area and the maximum rate of carboxylation by the enzyme Rubisco at 25°C ( V c max_25 ), respectively. The models also varied in their sensitivities of NPP, GPP, and CUE to historical changes in climate and atmospheric CO 2 concentration. These results indicate that model predictive ability of the C cycle in permafrost regions can be improved by better representation of the processes controlling CUE and GPP max as well as their sensitivity to climate change.

Journal of Geophysical Research: Biogeosciences↗

USGS2016

Variability in the sensitivity among model simulations of permafrost and carbon dynamics in the permafrost region between 1960 and 2009

A significant portion of the large amount of carbon (C) currently stored in soils of the permafrost region in the Northern Hemisphere has the potential to be emitted as the greenhouse gases CO 2 and CH 4 under a warmer climate. In this study we evaluated the variability in the sensitivity of permafrost and C in recent decades among land surface model simulations over the permafrost region between 1960 and 2009. The 15 model simulations all predict a loss of near-surface permafrost (within 3 m) area over the region, but there are large differences in the magnitude of the simulated rates of loss among the models (0.2 to 58.8 × 10 3 km 2 yr −1 ). Sensitivity simulations indicated that changes in air temperature largely explained changes in permafrost area, although interactions among changes in other environmental variables also played a role. All of the models indicate that both vegetation and soil C storage together have increased by 156 to 954 Tg C yr −1 between 1960 and 2009 over the permafrost region even though model analyses indicate that warming alone would decrease soil C storage. Increases in gross primary production (GPP) largely explain the simulated increases in vegetation and soil C. The sensitivity of GPP to increases in atmospheric CO 2 was the dominant cause of increases in GPP across the models, but comparison of simulated GPP trends across the 1982–2009 period with that of a global GPP data set indicates that all of the models overestimate the trend in GPP. Disturbance also appears to be an important factor affecting C storage, as models that consider disturbance had lower increases in C storage than models that did not consider disturbance. To improve the modeling of C in the permafrost region, there is the need for the modeling community to standardize structural representation of permafrost and carbon dynamics among models that are used to evaluate the permafrost C feedback and for the modeling and observational communities to jointly develop data sets and methodologies to more effectively benchmark models.

Global Biogeochemical Cycles↗

USGS2016

Evaluation of air-soil temperature relationships simulated by land surface models during winter across the permafrost region

A realistic simulation of snow cover and its thermal properties are important for accurate modelling of permafrost. We analyze simulated relationships between air and near-surface (20 cm) soil temperatures in the Northern Hemisphere permafrost region during winter, with a particular focus on snow insulation effects in nine land surface models and compare them with observations from 268 Russian stations. There are large across-model differences as expressed by simulated differences between near-surface soil and air temperatures, (Δ T ), of 3 to 14 K, in the gradients between soil and air temperatures (0.13 to 0.96°C/°C), and in the relationship between Δ T and snow depth. The observed relationship between Δ T and snow depth can be used as a metric to evaluate the effects of each model's representation of snow insulation, and hence guide improvements to the model’s conceptual structure and process parameterizations. Models with better performance apply multi-layer snow schemes and consider complex snow processes. Some models show poor performance in representing snow insulation due to underestimation of snow depth and/or overestimation of snow conductivity. Generally, models identified as most acceptable with respect to snow insulation simulate reasonable areas of near-surface permafrost (12–16 million km 2 ). However, there is not a simple relationship between the quality of the snow insulation in the acceptable models and the simulated area of Northern Hemisphere near-surface permafrost, likely because several other factors such as differences in the treatment of soil organic matter, soil hydrology, surface energy calculations, and vegetation also provide important controls on simulated permafrost distribution.

The Cryosphere↗

USGS2015

On critiques of “Stationarity is dead: Whither water management?”

We review and comment upon some themes in the recent stream of critical commentary on the assertion that “stationarity is dead,” attempting to clear up some misunderstandings; to note points of agreement; to elaborate on matters in dispute; and to share further relevant thoughts.

Water Resources Research↗

USGS2015

Hydroclimatic conditions preceding the March 2014 Oso landslide

The 22 March 2014 Oso landslide was one of the deadliest in U.S. history, resulting in 43 fatalities and the destruction of more than 40 structures. We examine synoptic conditions, precipitation records and soil moisture reconstructions in the days, months, and years preceding the landslide. Atmospheric reanalysis shows a period of enhanced moisture transport to the Pacific Northwest beginning on 11 February 2014. The 21- to 42-day periods prior to the landslide had anomalously high precipitation; we estimate that 300-400 mm of precipitation fell at Oso in the 21 days prior to the landslide. Relative only to historical periods ending on 22 March, the return periods of these precipitation accumulations are large (25-88 years). However, relative to the largest accumulations from any time of the year (annual maxima), return periods are more modest (2-6 years). In addition to the 21-42 days prior to the landslide, there is a secondary maximum in the precipitation return periods for the 4 years preceding the landslide. Reconstructed soil moisture was anomalously high prior to the landslide, with a return period that exceeded 40 years about a week before the event.

Washington↗

USGS2014

Understanding uncertainties in future Colorado River streamflow

The Colorado River is the primary water source for more than 30 million people in the United States and Mexico. Recent studies that project streamf low changes in the Colorado River all project annual declines, but the magnitude of the projected decreases range from less than 10% to 45% by the mid-twenty-first century. To understand these differences, we address the questions the management community has raised: Why is there such a wide range of projections of impacts of future climate change on Colorado River streamflow, and how should this uncertainty be interpreted? We identify four major sources of disparities among studies that arise from both methodological and model differences. In order of importance, these are differences in 1) the global climate models (GCMs) and emission scenarios used; 2) the ability of land surface and atmospheric models to simulate properly the high-elevation runoff source areas; 3) the sensitivities of land surface hydrology models to precipitation and temperature changes; and 4) the methods used to statistically downscale GCM scenarios. In accounting for these differences, there is substantial evidence across studies that future Colorado River streamflow will be reduced under the current trajectories of anthropogenic greenhouse gas emissions because of a combination of strong temperature-induced runoff curtailment and reduced annual precipitation. Reconstructions of preinstrumental streamflows provide additional insights; the greatest risk to Colorado River streamf lows is a multidecadal drought, like that observed in paleoreconstructions, exacerbated by a steady reduction in flows due to climate change. This could result in decades of sustained streamflows much lower than have been observed in the ~100 years of instrumental record.

Colorado River↗

USGS2013

Monitoring and understanding changes in heat waves, cold waves, floods, and droughts in the United States: State of knowledge

Weather and climate extremes have been varying and changing on many different time scales. In recent decades, heat waves have generally become more frequent across the United States, while cold waves have been decreasing. While this is in keeping with expectations in a warming climate, it turns out that decadal variations in the number of U.S. heat and cold waves do not correlate well with the observed U.S. warming during the last century. Annual peak flow data reveal that river flooding trends on the century scale do not show uniform changes across the country. While flood magnitudes in the Southwest have been decreasing, flood magnitudes in the Northeast and north-central United States have been increasing. Confounding the analysis of trends in river flooding is multiyear and even multidecadal variability likely caused by both large-scale atmospheric circulation changes and basin-scale “memory” in the form of soil moisture. Droughts also have long-term trends as well as multiyear and decadal variability. Instrumental data indicate that the Dust Bowl of the 1930s and the drought in the 1950s were the most significant twentieth-century droughts in the United States, while tree ring data indicate that the megadroughts over the twelfth century exceeded anything in the twentieth century in both spatial extent and duration. The state of knowledge of the factors that cause heat waves, cold waves, floods, and drought to change is fairly good with heat waves being the best understood.

Bulletin of the American Meteorological Society↗