Investigation of models for large-scale meteorological prediction experiments

The feasibility of long-range weather prediction through the use of global general circulation models (GCMs) was investigated. A climate model was developed to simulate the monthly mean state of the atmosphere from real global initial data at the beginning of the month. The model contains the same dynamic and physical ingredients as most numerical weather prediction models and GCMs. The model generates a one-day global simulation on the 8 x 10 grid in four minutes (on an IBM 360/95 computer), so that a 30 day forecast can be executed in two hours. The high speed of the model is achieved mainly at the price of its coarse resolution, which requires certain parameterizations of surface boundary conditions, as well as inherent filtering of smaller-scale features of the initial state

Investigation of models for large-scale meteorological prediction experiments

The feasibility of extended and long-range weather prediction by means of global atmospheric models was studied. A number of computer experiments were conducted at GISS with the GISS global general circulation model. Topics discussed include atmospheric response to sea-surface temperature anomalies, and monthly mean forecast experiments with the global model

Investigation of models for large-scale meteorological prediction experiments

Studies are reported of the long term responses of the model atmosphere to anomalies in snow cover and sea surface temperature. An abstract of a previously issued report on the computed response to surface anomalies in a global atmospheric model is presented, and the experiments on the effects of transient sea surface temperature on the Mintz-Arakawa atmospheric model are reported

Some effects of topography, soil moisture, and sea-surface temperature on continental precipitation as computed with the GISS coarse mesh climate model

The effects of terrain elevation, soil moisture, and zonal variations in sea/surface temperature on the mean daily precipitation rates over Australia, Africa, and South America in January were evaluated. It is suggested that evaporation of soil moisture may either increase or decrease the model generated precipitation, depending on the surface albedo. It was found that a flat, dry continent model best simulates the January rainfall over Australia and South America, while over Africa the simulation is improved by the inclusion of surface physics, specifically soil moisture and albedo variations

Experiments in monthly mean simulation of the atmosphere with a coarse-mesh general circulation model

The Hansen atmospheric model was used to compute five monthly forecasts (October 1976 through February 1977). The comparison is based on an energetics analysis, meridional and vertical profiles, error statistics, and prognostic and observed mean maps. The monthly mean model simulations suffer from several defects. There is, in general, no skill in the simulation of the monthly mean sea-level pressure field, and only marginal skill is indicated for the 850 mb temperatures and 500 mb heights. The coarse-mesh model appears to generate a less satisfactory monthly mean simulation than the finer mesh GISS model

Simulations of the monthly mean atmosphere for February 1976 with the GISS model

Monthly mean simulations of the global atmosphere were computed for February 1976 with the GISS model from observed initial conditions. In a replication experiment, two of these computations generated slightly different monthly mean states, apparently due to the schedule of interruptions on the computer. The root-mean-square errors of replication over the Northern Hemisphere were found to be about 2 mb, 20 m, and 1 K for sea-level pressure, 500 mb height, and 850 mb temperature, respectively. The monthly mean 500 mb forecast results for February 1976 over the Northern Hemisphere were consistent with those from earlier GISS model experiments

Spherical harmonic analysis for verfication of a global atmospheric model

Surface spherical harmonics were used to analyze the horizontal fields of various quantities generated by a global climate model. Also, the computed monthly mean forecast fields were compared with the corresponding observed fields

A note on the annual cycles of surface heat balance and temperature over a continent

A surface heating function, defined as the ratio of the time derivative of the mean annual temperature curve to the surface heat balance, is computed from the annual temperature range and heat balance data for the North American continent. An annual cycle of the surface heat balance is then reconstructed from the surface heating function and the annual temperature curve, and an annual cycle of evaporative plus turbulent heat loss is recomputed from the annual cycles of radiation balance and surface heat balance for the continent. The implications of these results for long range weather forecasting are discussed

Atmospheric response to variations in sea surface temperature

An extended range prediction experiment was performed with the GISS atmospheric model on a global data to test the sensitivity of the model to sea surface temperature (SST) variation over a two-week forecast period. The use of an initial observed SST field in place of the climatological monthly mean sea temperatures for surface flux calculations in the model was found to have a significant effect on the predicted precipitation over the ocean, with enhanced convection computed over areas where moderately large warm SST anomalies are found. However, there was no detectable positive effect of the SST anomaly field on forecast quality. The influence of the SST anomalies on the daily predicted fields of pressure and geopotential is relatively insignificant up to about one week compared with the growth of prediction error, and is no greater over a two-week period than that resulting from random errors in the initial meteorological state. The 14-day average fields of sea level pressure and 500-mb height predicted by the model, appear to be similarly insensitive to anomalies of sea surface temperature

The influence of initial and surface boundary conditions on a model-generated January climatology

The influence on a model-generated January climate of various surface boundary conditions, as well as initial conditions, was studied by using the GISS coarse-mesh climate model. Four experiments - two with water planets, one with flat continents, and one with mountains - were used to investigate the effects of initial conditions, and the thermal and dynamical effects of the surface on the model generated-climate. However, climatological mean zonal-symmetric sea surface temperature is used in all four runs over the model oceans. Moreover, zero ground wetness and uniform ground albedo except for snow are used in the last experiments