Cheng-Hsuan Lu

GLACE: The Global Land–Atmosphere Coupling Experiment. Part I: Overview

Abstract The Global Land–Atmosphere Coupling Experiment (GLACE) is a model intercomparison study focusing on a typically neglected yet critical element of numerical weather and climate modeling: land–atmosphere coupling strength, or the degree to which anomalies in land surface state (e.g., soil moisture) can affect rainfall generation and other atmospheric processes. The 12 AGCM groups participating in GLACE performed a series of simple numerical experiments that allow the objective quantification of this element for boreal summer. The derived coupling strengths vary widely. Some similarity, however, is found in the spatial patterns generated by the models, with enough similarity to pinpoint multimodel “hot spots” of land–atmosphere coupling. For boreal summer, such hot spots for precipitation and temperature are found over large regions of Africa, central North America, and India; a hot spot for temperature is also found over eastern China. The design of the GLACE simulations are described in full detai...

Soil Moisture Memory in AGCM Simulations: Analysis of Global Land–Atmosphere Coupling Experiment (GLACE) Data

Abstract Soil moisture memory is a key aspect of land–atmosphere interaction and has major implications for seasonal forecasting. Because of a severe lack of soil moisture observations on most continents, existing analyses of global-scale soil moisture memory have relied previously on atmospheric general circulation model (AGCM) experiments, with derived conclusions that are probably model dependent. The present study is the first survey examining and contrasting global-scale (near) monthly soil moisture memory characteristics across a broad range of AGCMs. The investigated simulations, performed with eight different AGCMs, were generated as part of the Global Land–Atmosphere Coupling Experiment. Overall, the AGCMs present relatively similar global patterns of soil moisture memory. Outliers are generally characterized by anomalous water-holding capacity or biases in radiation forcing. Water-holding capacity is highly variable among the analyzed AGCMs and is the main factor responsible for intermodel diffe...

Seasonal and diurnal variations of coherent structures over a deciduous forest

Coherent structures in turbulent flow above a midlatitude deciduous forest are identified using a wavelet analysis technique. Coupling between motions above the canopy (z/h=1.5, whereh is canopy height) and within the canopy (z/h=0.6) are studied using composite velocity and temperature fields constructed from 85 hours of data. Data are classified into winter and summer cases, for both convective and stable conditions. Vertical velocity fluctuations are in phase at both observation levels. Horizontal motions associated with the structures within the canopy lead those above the canopy, and linear analysis indicates that the horizontal motions deep in the canopy should lead the vertical motions by 90°. On average, coherent structures are responsible for only about 40% of overall turbulent heat and momentum fluxes, much less than previously reported. However, our large data set reveals that this flux fraction comes from a wide distribution that includes much higher fractions in its upper extremes. The separation distanceLs between adjacent coherent structures, 6–10h, is comparable to that obtained in previous observations over short canopies and in the laboratory. Changes in separation between the summer and winter (leafless) conditions are consistent withLs being determined by a local horizontal wind shear scale.

On the indicator‐based approach to assess ozone sensitivities and emissions features

Previous model studies suggested that ambient measurements of key chemical species and ratios of species could be used to assess the sensitivities of ozone formation to reductions in precursor emissions. Threshold values of these indicator species and ratios, delineating the transition between VOG and NOx sensitivity, were proposed. Subsequently, measurement studies have assumed the universality of these threshold criteria and have compared local observed indicators with previously established criteria to assess ozone sensitivities. In this study the concept of indicator species is extended to combinations of observable species that are consistently associated with different site characteristics (e.g., ozone sensitivities and emissions features). The results of SARMAP Air Quality Model (SAQM) simulations in the San Joaquin Valley, California, are used to investigate the applicability of indicators to assess ozone sensitivities and emissions features. The use of three indicator ratios (O3/(NOy-NOx), HCHO/NO2 and H2O2/HNO3) along with SAQM-derived threshold criteria is found to be effective for identifying VOC- or NOx-sensitive regimes. NOy and (NOy-NOx)NOy are found to be useful in describing emission features and threshold criteria are derived by SAQM prediction. SAQM-derived threshold criteria for assessing ozone sensitivities are found to differ from threshold criteria proposed by previous studies using different models and under different conditions. Such differences suggest that threshold criteria are likely to be dependent on locations and environmental conditions, including emission patterns and rates. Therefore local observed indicator species and ratios can be used to determine ozone sensitivities only if appropriate threshold criteria have been derived for the local conditions.

The Predictability of Soil Moisture and Near-Surface Temperature in Hindcasts of the NCEP Seasonal Forecast Model

Abstract Using the NCEP–DOE reanalysis (R-2) soil wetness and the NCEP Seasonal Forecast System, seasonal predictability of the soil moisture and near-surface temperature, and the role of land surface initial conditions are examined. Two sets of forecasts were made, one starting from climatological soil moisture as initial condition and the other from R-2 soil moisture analysis. Each set consisted of 10-member ensemble runs of 7-month duration. Initial conditions were taken from the first 5 days of April, 12 h apart, for the 1979–96 period. The predictive skill of soil moisture was found to be high over arid/semiarid regions. The model prediction surpassed the persisted anomaly forecast, and the soil moisture initial condition was essential for skillful predictions over these areas. Over temperate zones with more precipitation, and over tropical monsoon regions, the predictive skill of the soil moisture declined steeply in the first 3–4 months. This is due to the difficulties in predicting precipitation a...

Evaluation of Soil Moisture in the NCEP–NCAR and NCEP–DOE Global Reanalyses

Abstract This study compares soil moisture analyses from the National Centers for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR) global reanalysis (R-1) and the later NCEP– Department of Energy (DOE) Atmospheric Model Intercomparison Project (AMIP) global reanalysis (R-2). The R-1 soil moisture is strongly controlled by nudging it to a prescribed climatology, whereas the R-2 soil moisture is adjusted according to differences between model-generated and observed precipitation. While mean soil moisture fields from R-1 and R-2 show many geographic similarities, there are some major differences. This study uses in situ observations from the Global Soil Moisture Data Bank to evaluate the two global reanalysis products. In general, R-2 does a better job of simulating interannual variations, the mean seasonal cycle, and the persistence of soil moisture, when compared to observations. However, the R-2 reanalysis does not necessarily represent observed soil moisture characteristics w...

Land–Atmosphere Coupling Strength in the Global Forecast System

Abstract The operational coupled land–atmosphere forecast model from the National Centers for Environmental Prediction (NCEP) is evaluated for the strength and characteristics of its coupling in the water cycle between land and atmosphere. Following the protocols of the Global Land–Atmosphere Coupling Experiment (GLACE) it is found that the Global Forecast System (GFS) atmospheric model coupled to the Noah land surface model exhibits extraordinarily weak land–atmosphere coupling, much as its predecessor, the GFS–Oregon State University (OSU) coupled system. The coupling strength is evaluated by the ability of subsurface soil wetness to affect locally the time series of precipitation. The surface fluxes in Noah are also found to be rather insensitive to subsurface soil wetness. Comparison to another atmospheric model coupled to Noah as well as a different land surface model show that Noah is responsible for some of the lack of sensitivity, primarily because its thick (10 cm) surface layer dominates the var...

A Comparison of the Noah and OSU Land Surface Models in the ECPC Seasonal Forecast Model

Abstract The Noah land surface model (LSM) has recently been implemented into the Experimental Climate Prediction Center’s (ECPC’s) global Seasonal Forecast Model (SFM). Its performance is compared to the older ECPC SFM with the Oregon State University (OSU) LSM using two sets of 10-member 50-yr Atmospheric Model Intercomparison Project (AMIP) runs. The climatological biases of several fields tend to increase with the Noah LSM. The differences in near-surface temperature bias are traced to changes in the energy budget. In addition to climatology, the variability and skill (anomaly correlation with observations) of the two ensembles are considered. Unlike the climatology, the near-surface temperature skill of the ECPC SFM generally improves with the Noah LSM. Other climatological fields, such as precipitation, show little change in skill. While the global results are mixed, there are however significant regional improvements over Africa both in terms of climatological bias and skill. In the central African...

Variability of indicator values for ozone production sensitivity: a model study in Switzerland and San Joaquin Valley (California)

Abstract The threshold values of indicator species and ratios delineating the transition between NOx and VOC sensitivity of ozone formation are assumed to be universal by various investigators. However, our previous studies suggested that threshold values might vary according to the locations and conditions. In this study, threshold values derived from various model simulations at two different locations (the area of Switzerland by UAM Model and San Joaquin Valley of Central California by SAQM Model) are examined using a new approach for defining NOx and VOC sensitive regimes. Possible definitions for the distinction of NOx and VOC sensitive ozone production regimes are given. The dependence of the threshold values for indicators and indicator ratios such as NOy, O3/NOz, HCHO/NOy, and H2O2/HNO3 on the definition of NOx and VOC sensitivity is discussed. Then the variations of threshold values under low emission conditions and in two different days are examined in both areas to check whether the models respond consistently to changes in environmental conditions. In both cases, threshold values are shifted similarly when emissions are reduced. Changes in the wind fields and aging of the photochemical oxidants seem to cause the day-to-day variation of the threshold values. O3/NOz and HCHO/NOy indicators are predicted to be unsatisfactory to separate the NOx and VOC sensitive regimes. Although NOy and H2O2/HNO3 provide a good separation of the two regimes, threshold values are affected by changes in the environmental conditions studied in this work.