Simulations of the 2004 North American Monsoon: NAMAP2

The second phase of the North American Monsoon Experiment (NAME) Model Assessment Project (NAMAP2) was carried out to provide a coordinated set of simulations from global and regional models of the 2004 warm season across the North American monsoon domain. This project follows an earlier assessment, called NAMAP, that preceded the 2004 field season of the North American Monsoon Experiment. Six global and four regional models are all forced with prescribed, time-varying ocean surface temperatures. Metrics for model simulation of warm season precipitation processes developed in NAMAP are examined that pertain to the seasonal progression and diurnal cycle of precipitation, monsoon onset, surface turbulent fluxes, and simulation of the low-level jet circulation over the Gulf of California. Assessment of the metrics is shown to be limited by continuing uncertainties in spatially averaged observations, demonstrating that modeling and observational analysis capabilities need to be developed concurrently. Simulations of the core subregion (CORE) of monsoonal precipitation in global models have improved since NAMAP, despite the lack of a proper low-level jet circulation in these simulations. Some regional models run at higher resolution still exhibit the tendency observed in NAMAP to overestimate precipitation in the CORE subregion; this is shown to involve both convective and resolved components of the total precipitation. The variability of precipitation in the Arizona/New Mexico (AZNM) subregion is simulated much better by the regional models compared with the global models, illustrating the importance of transient circulation anomalies (prescribed as lateral boundary conditions) for simulating precipitation in the northern part of the monsoon domain. This suggests that seasonal predictability derivable from lower boundary conditions may be limited in the AZNM subregion.open131

Daily Patterns of River Herring (\u3cem\u3eAlosa\u3c/em\u3e spp.) Spawning Migrations: Environmental Drivers and Variation among Coastal Streams in Massachusetts

The timing of life history events in many plants and animals depends on the seasonal fluctuations of specific environmental conditions. Climate change is altering environmental regimes and disrupting natural cycles and patterns across communities. Anadromous fishes that migrate between marine and freshwater habitats to spawn are particularly sensitive to shifting environmental conditions and thus are vulnerable to the effects of climate change. However, for many anadromous fish species the specific environmental mechanisms driving migration and spawning patterns are not well understood. In this study, we investigated the upstream spawning migrations of river herring Alosa spp. in 12 coastal Massachusetts streams. By analyzing long-term data sets (8–28 years) of daily fish counts, we determined the local influence of environmental factors on daily migration patterns and compared seasonal run dynamics and environmental regimes among streams. Our results suggest that water temperature was the most consistent predictor of both daily river herring presence–absence and abundance during migration. We found inconsistent effects of streamflow and lunar phase, likely due to the anthropogenic manipulation of flow and connectivity in different systems. Geographic patterns in run dynamics and thermal regimes suggest that the more northerly runs in this region are relatively vulnerable to climate change due to migration occurring later in the spring season, at warmer water temperatures that approach thermal maxima, and during a narrower temporal window compared to southern runs. The phenology of river herring and their reliance on seasonal temperature patterns indicate that populations of these species may benefit from management practices that reduce within-stream anthropogenic water temperature manipulations and maintain coolwater thermal refugia

The nocturnal water cycle in an open-canopy forest

The movement of moisture into, out-of, and within forest ecosystems is modulated by feedbacks that stem from processes which couple plants, soil, and the atmosphere. While an understanding of these processes has been gleaned from Eddy Covariance techniques, the reliability of the method suffers at night because of weak turbulence. During the summer of 2011, continuous profiles of the isotopic composition (i.e., δ¹⁸O and δD) of water vapor and periodic measurements of soil, leaf, and precipitation pools were measured in an open-canopy ponderosa pine forest in central Colorado to study within-canopy nocturnal water cycling. The isotopic composition of the nocturnal water vapor varies significantly based on the relative contributions of the three major hydrological processes acting on the forest: dewfall, exchange of moisture between leaf waters and canopy vapor, and periodic mixing between the canopy and background air. Dewfall proved to be surprisingly common (~30% of the nights) and detectable on both the surface and within the canopy through the isotopic measurements. While surface dew could be observed using leaf wetness and soil moisture sensors, dew in the foliage was only measurable through isotopic analysis of the vapor and often occurred even when no dew accumulated on the surface. Nocturnal moisture cycling plays a critical role in water availability in forest ecosystems through foliar absorption and transpiration, and assessing these dynamics, as done here, is necessary for fully characterizing the hydrological controls on terrestrial productivity.Keywords: dewfall, nocturnal boundary layer, water isotopes, forest hydrolog

A Unified Approach for Process-Based Hydrologic Modeling: 2. Model Implementation and Case Studies

This work advances a unified approach to process-based hydrologic modeling, which we term the “Structure for Unifying Multiple Modeling Alternatives (SUMMA).” The modeling framework, introduced in the companion paper, uses a general set of conservation equations with flexibility in the choice of process parameterizations (closure relationships) and spatial architecture. This second paper specifies the model equations and their spatial approximations, describes the hydrologic and biophysical process parameterizations currently supported within the framework, and illustrates how the framework can be used in conjunction with multivariate observations to identify model improvements and future research and data needs. The case studies illustrate the use of SUMMA to select among competing modeling approaches based on both observed data and theoretical considerations. Specific examples of preferable modeling approaches include the use of physiological methods to estimate stomatal resistance, careful specification of the shape of the within-canopy and below-canopy wind profile, explicitly accounting for dust concentrations within the snowpack, and explicitly representing distributed lateral flow processes. Results also demonstrate that changes in parameter values can make as much or more difference to the model predictions than changes in the process representation. This emphasizes that improvements in model fidelity require a sagacious choice of both process parameterizations and model parameters. In conclusion, we envisage that SUMMA can facilitate ongoing model development efforts, the diagnosis and correction of model structural errors, and improved characterization of model uncertainty

North American monsoon and convectively coupled equatorial waves simulated by IPCC AR4 coupled GCMs

This study evaluates the fidelity of North American monsoon and associated intraseasonal variability in the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) coupled general circulation models (CGCMs). Twenty years of monthly precipitation data from each of the 22 models' twentieth-century climate simulations, together with the available daily precipitation data from 12 of them, are analyzed and compared with Global Precipitation Climatology Project (GPCP) monthly and daily precipitation. The authors focus on the seasonal cycle and horizontal pattern of monsoon precipitation in conjunction with the two dominant convectively coupled equatorial wave modes: the eastward-propagating Madden-Julian oscillation (MJO) and the westward-propagating easterly waves. The results show that the IPCC AR4 CGCMs have significant problems and display a wide range of skill in simulating the North American monsoon and associated intraseasonal variability. Most of the models reproduce the monsoon rainbelt, extending from southeast to northwest, and its gradual northward shift in early summer, but overestimate the precipitation over the core monsoon region throughout the seasonal cycle and fail to reproduce the monsoon retreat in the fall. Additionally, most models simulate good westward propagation of the easterly waves, but relatively poor eastward propagation of the MJO and overly weak variances for both the easterly waves and the MJO. There is a tendency for models without undiluted updrafts in their deep convection scheme to produce better MJO propagation.open221

Regional climate modeling for Asia

The regional climate model (RCM) with higher resolution and sophisticated physical processes can reproduce and project fine-scale climate information, which cannot be captured by the global climate model (GCM). Therefore, we developed the Seoul National University Regional Climate Model (SNURCM) in the 1990s to simulate the intrinsic and detailed climate prevailing in Asia. In this study, we reviewed the developmental processes of the SNURCM and its application researches. In the simulation of regional climate over Asia, systematic errors can be generated because of natural characteristics such as complex land-surface conditions and topography, warm ocean conditions, and strong seasonal monsoon circulation and convection. Numerous methods and techniques have been applied to reduce these errors and improve the SNURCM. For long-term simulations without climate drift, the spectral nudging technique as well as the traditional relaxation method was employed for the boundary conditions. To represent reasonable interactions between earth systems, a simple ocean model and an advanced land-surface model were implemented into the SNURCM. Physical schemes for precipitation and vertical diffusion developed for short-term numerical weather prediction models were optimized or improved for long-term simulation. The SNURCM has been applied to future climate projection, reproduction of extreme climate, and seasonal forecasting. Furthermore, the model has served as a part of the multi-model comparison program and an ensemble of international research programs

Dynamical downscaling of historical climate over CORDEX Central America domain with a regionally coupled atmosphere–ocean model

The climate in Mexico and Central America is influenced by the Pacific and the Atlantic oceanic basins and atmospheric conditions over continental North and South America. These factors and important ocean–atmosphere coupled processes make the region’s climate a great challenge for global and regional climate modeling. We explore the benefits that coupled regional climate models may introduce in the representation of the regional climate with a set of coupled and uncoupled simulations forced by reanalysis and global model data. Uncoupled simulations tend to stay close to the large-scale patterns of the driving fields, particularly over the ocean, while over land they are modified by the regional atmospheric model physics and the improved orography representation. The regional coupled model adds to the reanalysis forcing the air–sea interaction, which is also better resolved than in the global model. Simulated fields are modified over the ocean, improving the representation of the key regional structures such as the Intertropical Convergence Zone and the Caribbean Low Level Jet. Higher resolution leads to improvements over land and in regions of intense air–sea interaction, e.g., off the coast of California. The coupled downscaling improves the representation of the Mid Summer Drought and the meridional rainfall distribution in southernmost Central America. Over the regions of humid climate, the coupling corrects the wet bias of the uncoupled runs and alleviates the dry bias of the driving model, yielding a rainfall seasonal cycle similar to that in the reanalysis-driven experiments.Universidad de Costa Rca/[805-B7-507]/UCR/Costa RicaCRYOPERU/[144-2015]//PerúUCR::Vicerrectoría de Investigación::Unidades de Investigación::Ciencias Básicas::Centro de Investigaciones Geofísicas (CIGEFI

Comparison of Cumulus Parameterizations and Entrainment Using Domain-Mean Wind Divergence in a Regional Model

Several different cumulus parameterizations are compared in a 10-day regional model simulation over the tropical Americas in northern summer. A simple bulk diagnostic test is devised, comparing the model's preferred domain-mean wind divergence profile with 'observed' drivergence. The latter is obtained by a line integral of the normal wind component at the model's outer boundary, from the ECMWF reanalysis data used as lateral boundary conditions. The former is obtained from a line integral one grid point in from the boundary, a perimeter that encloses almost exactly the same region. Even though the model fields near the boundary are strongly nudged toward the ECMWF values, the difference is distinct, and indicative of systematic errors in the model's heating field throughout the interior of the domain. Heating reflects the effects of the convection scheme, both direct and indirect (e.g., through its impact on resolved condensation). A useful axis along which to characterize schemes appears to be overactive versus underactive. Underactive convective schemes tend to produce too little low-level convergence and upper-level divergence, while overactive schemes produce too much. This categorization is also reflected in rainfall fields, as overactive schemes produce widespread light convective rain while underactive schemes produce sparse occasional storms. For example, the Kain-Fritsch scheme is overactive with its default entraining-plume radius of 1500 m, a value optimized for midlatitudes over land. A value of 750 m makes the regional divergence magnitude about right, but makes the upper-tropospheric outflow altitude too low, illustrating a classic dilemma of entraining-plume models of convection. Schemes with other conceptual structures give widely varying divergence errors. The largest errors are found with the Anthes-Kuo scheme, while the smallest errors are found with the Betts-Miller-Janjic scheme, which has no consistent divergence bias over time. Diagnosis of other North American monsoon simulations supports the general underactive/ overactive characterization, but shows that the best scheme and parameters may depend on weather regime