Michael J. Fennessy

The Simulated Indian Monsoon: A GCM Sensitivity Study

Abstract A series of sensitivity experiments are conducted in an attempt to understand and correct deficiencies in the simulation of the seasonal mean Indian monsoon with a global atmospheric general circulation model. The seasonal mean precipitation is less than half that observed. This poor simulation in seasonal integrations is independent of the choice of initial conditions and global sea surface temperature data used. Experiments are performed to test the sensitivity of the Indian monsoon simulation to changes in orography, vegetation, soil wetness, and cloudiness. The authors find that the deficiency of the model precipitation simulation may be attributed to the use of an enhanced orography in the integrations. Replacement of this orography with a mean orography results in a much more realistic simulation of Indian monsoon circulation and rainfall. Experiments with a linear primitive equation model on the sphere suggest that this striking improvement is due to modulations of the orographically force...

Low-Level Jets and Their Effects on the South American Summer Climate as Simulated by the NCEP Eta Model*

Abstract The National Centers for Environmental Prediction (NCEP) Eta Model (80 km, 38L) is used to simulate the tropical South American summer (January–March) climate for 1983, 1985, 1987, 1989, and 1991 using lateral boundary conditions from the NCEP–National Center for Atmospheric Research (NCAR) reanalysis. Simulations of the lower tropospheric circulation and precipitation are analyzed to study the variability on diurnal, intraseasonal, and interannual timescales. The results are compared with observations and previous studies. The Eta Model produces better regional circulation details, such as low-level jets (LLJs), than does the reanalysis because of its higher resolution, more realistic topography and coastal geometry, and because of its ability to realistically simulate the effects of mesoscale circulation on the time-mean flow. The model detects not only the LLJ east of the Andes Mountains and the LLJ west of northern Cordillera Occidental, which have been reported in previous studies, but it al...

A statistical-dynamical estimate of winter ENSO teleconnections in a future climate.

Abstract Changes in the atmospheric response to SST variability in the decade 2065–75 are estimated from time-slice-like experiments using the NCAR Community Atmosphere Model, version 3 (CAM3) AGCM forced by specified SST and external forcing. The current climate is simulated using observed monthly SST and external forcing for 1951–2000. The change in mean SST for the future is represented by the difference between the 2065–75 and 1965–75 decadal mean SST climatologies from coupled model twentieth-century/future climate simulations of the response to external forcing. The change in external forcing is similarly specified as the change of the external forcing concurrent with the SST change. These seasonally varying changes in SST and external forcing are added to the 50-year sequence of 1951–2000 observed SST and external forcings to produce the specified future climate forcings for the AGCM. Changes in the December through February mean ENSO teleconnections are evaluated from the difference between ensemb...

Model Estimates of Land-Driven Predictability in a Changing Climate from CCSM4

AbstractThe climate system model of the National Center for Atmospheric Research is used to examine the predictability arising from the land surface initialization of seasonal climate ensemble forecasts in current, preindustrial, and projected future settings. Predictability is defined in terms of the models ability to predict its own interannual variability. Predictability from the land surface in this model is relatively weak compared to estimates from other climate models but has much of the same spatial and temporal structure found in previous studies. Several factors appear to contribute to the weakness, including a low correlation between surface fluxes and subsurface soil moisture, less soil moisture memory (lagged autocorrelation) than other models or observations, and relative insensitivity of the atmospheric boundary layer to surface flux variations. Furthermore, subseasonal cyclical behavior in plant phenology for tropical grasses introduces spurious unrealistic predictability at low latitudes...

Differing Estimates of Observed Bangladesh Summer Rainfall

Abstract The differences in boreal summer (June–August) monthly-mean rainfall estimates over the Indian Ocean region in five research-quality products are examined for the period 1979–2003. Two products derived from the merged satellite and surface observations are considered: the Climate Prediction Center (CPC) Merged Analysis of Precipitation (CMAP) and the Global Precipitation Climatology Project (GPCP). In addition, three products derived solely from rain gauge observations are considered: the Chen et al. product; the Indian Meteorological Department (IMD) product; and a new, objectively analyzed product based on the Climate Anomaly Monitoring System (CAMS) dataset. Significant discrepancies have been found between the different products across the entire Indian Ocean region, with the greatest disagreement over Burma and neighboring Bangladesh. These differences appear to be primarily due to the absence of reported rain gauge data for Burma and differences in the algorithms used to merge the satellite...

Seasonal Forecasts of Tropical Cyclone Activity in a High-Atmospheric-Resolution Coupled Prediction System*

AbstractSeasonal forecast skill of the basinwide and regional tropical cyclone (TC) activity in an experimental coupled prediction system based on the ECMWF System 4 is assessed. As part of a collaboration between the Center for Ocean–Land–Atmosphere Studies (COLA) and the ECMWF called Project Minerva, the system is integrated at the atmospheric horizontal spectral resolutions of T319, T639, and T1279. Seven-month hindcasts starting from 1 May for the years 1980–2011 are produced at all three resolutions with at least 15 ensemble members. The Minerva system demonstrates statistically significant skill for retrospective forecasts of TC frequency and accumulated cyclone energy (ACE) in the North Atlantic (NA), eastern North Pacific (EP), and western North Pacific. While the highest scores overall are achieved in the North Pacific, the skill in the NA appears to be limited by an overly strong influence of the tropical Pacific variability. Higher model resolution improves skill scores for the ACE and, to a le...

Effects of realistic land surface initializations on subseasonal to seasonal soil moisture and temperature predictability in North America and in changing climate simulated by CCSM4

Fully coupled global climate model experiments are performed using the Community Climate System Model version 4.0 (CCSM4) for preindustrial, present, and future climate to study the effects of realistic land surface initializations on subseasonal to seasonal climate forecasts. Model forecasts are verified against model control simulations (perfect model experiments), thus overcoming to some extent issues of uncertainties in the observations and/or model parameterizations. Findings suggest that realistic land surface initialization is important for climate predictability at subseasonal to seasonal time scales. We found the highest predictability for soil moisture, followed by evapotranspiration, temperature, and precipitation. The predictability is highest for the 16 to 30 days forecast period, and it progressively decreases for the second and third month forecasts. We found significant changes in the spatial distributions of temperature predictability in the present and future climate compared to the preindustrial climate, although the spatial average changes for North America were rather small (<10%). To attribute the potential cause of changes in land-driven temperature predictability, they are correlated with the changes in land related climate metrics. The changes in temperature predictability are positively (0.40), and negatively (−0.35) correlated with the changes in nonrainy days evaporative fraction, and changes in dryness index respectively. From this result, the hypothesis arises that wetter conditions favor higher land-driven temperature predictability in North America. We tested the hypothesis by rearranging the predictability experiment ensembles and found support for the hypothesis in the midlatitude regions and short-term forecasts (16 to 30 days).

Value Added in Regional Climate Modeling: Should One Aim to Improve on the Large Scales as Well?

Expectations various regional climate modelers have expressed as to the impact on large scales are recalled. While some authors do mention the possibility of improvement also at large scales (e.g., Giorgi, J Phys IV France 139:101–118, 2006), the majority clearly accepts the view of “downscaling” as an effort in which the driver global model large scales are hoped to be preserved as much as possible and only small scales improved compared to those of the driver model. Many authors find it even desirable to use the so-called “large-scale nudging” in order to help achieve this objective. Mesinger et al. (Limited area predictability: can “upscaling” also take place? Research activities in atmospheric and oceanic modeling, WMO, Geneva, CAS/JSC WGNE Rep. No. 32, 5.30-5.31, 2002; see also Mesinger, The Eta model: design, history, performance, what lessons have we learned? In: Symposium on the 50th anniversary of operational numerical weather prediction, University of Maryland, College Park, MD, 14–17 June 2004, Preprints CD-ROM, 20pp, 2004) have however argued that various NWP results of the Eta model at NCEP strongly suggest that improvements in the large scales of the global driver model have been taking place more often than not. In addition, there was a four-month nine-member ensemble result of Fennessy and Altshuler in the early 2000s, published recently (Veljovic et al. Meteorol Z 19:237–246, 2010), in which an RCM achieved a dramatic improvement over its driver AGCM in hindcasting the precipitation difference over the central United States between the “flood year” of 1993 and the “drought year” of 1988; which we do not believe could have been possible without a significant improvement in the large scales. If this indeed is so and could be generalized, then large-scale nudging would not only be unnecessary but may also be harmful to the result. It could however be that this holds for some models while not for others. In that case, why so is a question of obvious importance. Given however that claims have even been made that improvements in large scales in regional climate modeling may be impossible for any models, hard evidence of specific large-scale improvements achieved are desirable. The preceding and additional points are discussed as well as more detail given, summarizing the results of perhaps the first comprehensive direct tests of the issue (Veljovic et al. Meteorol Z 19:237–246, 2010). Additional results are shown regarding the impact of the choice of the lateral boundary conditions (LBC) scheme, pointing to the advantage of the Eta (Mesinger, Contrib Atmos Phys 50:200–210, 1977) over the conventional and costlier relaxation scheme. As to the large scales question posed, the results summarized show that driving the Eta by ECMWF 32-day ensemble members the driver model large scales tended to be improved more often than not, giving support for our tenet that improving large scales as well in RCM efforts is possible. We furthermore argue that pursuing this objective should be beneficial for the improvement in smaller scales as well.