The thermal and hydrological impacts of soil freezing on the climate system are studied using an atmospheric general circulation model. The difference between runs with and without soil freezing, i. e., including and excluding the latent heat of fusion and the impermeability of frozen soil, shows that the inclusion of soil freezing leads to higher surface temperature in middle and high latitudes over land in summer. This leads to larger water vapor flux and precipitation in Southeast Asia. The higher temperature over land in summer results from lower evaporation caused by lower surface soil moisture. The low surface soil moisture is caused by additional runoff of snowmelt in spring due to the impermeability of frozen soil and low soil liquid water due to underlying frozen ground. Precipitation is lower in the middle of the Eurasian and North American Continents due to the lower evaporation. The sensitivity of temperature change to soil moisture change is high in regions where potential evaporation is high. In winter, deep soil temperature is higher with soil freezing in frozen ground regions due to the latent heat of freezing, but the surface temperature difference is governed more by atmospheric dynamical responses. The signs of the impacts are found to be the same in one-dimensional experiments with various hydrological schemes and parameters.
One of the major sources of the error in estimating precipitable water derived from GPS data is horizontal gradient of the moisture. Several characteristics of the error were investigated in comparison with water-vapor radiometer measurements. The GPS-precipitable water (GPS PW) exhibited good agreement with precipitable water derived from water-vapor radiometer measurements. The correlation coefficient and rms error for this comparison were determined as 0.991 and 1.93mm, respectively. The estimation errors for the GPS PW can be divided into two components based on the time scale of the variation. The first components of the error has low frequency with the time scale of several days, with an amplitude of about 2.5mm. This estimation error was negatively correlated with the north-south component of the GPS-PW gradient derived from GPS data. The GPS PW was overestimated under the condition in which water vapor increased southward. Another component of the error has high frequency with the time scale of several hours, having an amplitude of at most 5.0mm. The high frequency component of the error seems to depend on rapid changes of the GPS-PW gradient.
Observation of snowflake size distribution was carried out on the ground in order to reconsider the past observational results obtained from only a small amount of data. Based on the large quantity of data obtained in our studies, the characteristics of snowflake size distributions and their formation mechanisms are discussed. It was found that averaged size distributions of snowflakes moved parallel to a higher number concentration, maintaining their exponential distributions with increase in snowfall intensity. These characteristics differ from those of Gunn and Marshall (1958), who reported that size distributions became broader with increase in snowfall intensity. A small variation superposed on the averaged size distribution, and changed its slope even under the condition of equal snowfall intensity. The density and riming proportion of snowflakes are shown to be the factor that determines the slope. In other words, the slope of the size distribution becomes more gentle when snowflakes have low density and are not composed of rimed snow crystals.
Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) radiometer brightness temperature data, in the 85GHz channel (T85) reveal distinct local minima (T85min) in a regional map containing a Mesoscale Convective System (MCS). This is because of relatively small footprint size (∼5.5km) and strong extinction properties in this channel of the TMI. A map of surface rain rate for that region, deduced from simultaneous measurements made by the Precipitation Radar (PR) on board the TRMM satellite, reveals that these T85min, produced by scattering, correspond to local PR rain maxima. Utilizing the PR rain rate map as a guide, we infer empirically from TMI data the presence of three different kinds of thunderstorms or Cbs. These Cbs are classified as young, mature, and decaying types, and are assumed to have a scale of about 20km on the average. Two parameters are used to classify these three kinds of Cbs based on the T85 data: a) the magnitude of the scattering depression deduced from local T85min, and b) the mean horizontal gradient of T85 around such minima. Knowing the category of a given Cb, we can estimate the rain rate associated with it. Such estimation is done with the help of relationships linking T85min to rain rate in each Cb type. Similarly, a weak background rain rate in all the areas where T85 is less than 260K is deduced with another relationship linking T85 to rain rate. In our rain retrieval model, this background rain constitutes stratiform rain where the Cbs are absent. Initially, these relationships are optimized or tuned utilizing the PR and TMI data of a few MCS events. After such tuning, the model is applied to independent MCS cases. The areal distribution of light (1-10mmhr-1), moderate (10-20mmhr-1), and intense (≥20mmhr-1) rain rates are retrieved satisfactorily. Accuracy in the estimates of the light, moderate, and intense rain areas and the mean rain rates associated with such areas in these independent MCS cases is on the average about 15%. Taking advantage of this ability of our retrieval method, one could derive the latent heat input into the atmosphere over the 760km wide swath of the TMI radiometer in the tropics.
A new method, named time threshold diagnostics (TTD), is developed for use in discussing long-term global tracer transport as the result of atmospheric motions. The method works for analysis of a large number of parcels' trajectories in numerical tracer experiments. This method considers the motion of every air parcel passing through a given surface and focuses on periods between its passages through the surface. It selects passages that have periods longer than the specified time threshold. Aggregation of all the selected passages makes effective flux of the parcels, which should contribute to the transport through the surface for time scales over the time threshold. The TTD is capable of probing approximately boundaries between mixing regions in the atmosphere and assessing the substantial mass transport through the boundaries. In order to check its advantage, the TTD was applied to the investigation of trajectories of a large number of parcels in the troposphere and lower stratosphere in northern hemisphere winter, simulated in a general circulation model. Meridional effective mass flux through each equal-latitude surface was obtained for a variety of specified time thresholds. Each mid-latitude shows a local minimum in a meridional distribution of the meridional effective flux integrated for the upper troposphere for time thresholds over two days; this suggests that meridional transport for time scales over two days is suppressed in mid-latitudes in the upper troposphere. Stream functions of zonally averaged meridional circulation obtained from net effective meridional fluxes for these time scales show a one-cell circulation in each hemisphere.
This study investigates the relationship between circulation anomalies over India during the month of April, and sea surface temperature (SST) anomalies of the eastern Pacific Ocean (Niño 3 region). It is found that rain over northern parts of India and position of 500hPa ridge at 75°E, respectively, have significant correlation coefficients with subsequent SST anomalies of eastern Pacific Ocean (Niño 3 region). Moreover, these relationships are stronger during El Niño years. Since, during El Niño years, peak warming in SST occurs during October-December months, it could well be assessed with the help of these two parameters with the lead time of six months, once occurrence of an El Niño event is indicated by already existing dynamical models. To predict the peak warming during the El Niño years, data of April rain and position of 500hPa April ridge for eleven El Niño years, (1951, 1953, 1957, 1965, 1969, 1972, 1976, 1982, 1987, 1992, 1997) were subjected to the principal component analysis. First principal component was used to predict the average SST anomalies of October-December months through a simple regression equation using cross validation method. The standard deviation of average SST anomalies of October-December months for these eleven years is 0.96, while the root mean square error of the predicted value is 0.52, which is indicative of the good skill of prediction.
Large-scale vertical motions estimated by various classical kinematic methods are compared with those of NCEP-NCAR and ECMWF reanalyses. The classical kinematic methods include the central difference method, plane fitting method, and spectral method. In addition, a normal mode method is proposed in this study as a new approach to the computation of the vertical motion. In this method, the erroneous high frequency divergence is controlled by filtering the higher order gravity modes while the low-frequency Rossby modes are retained. According to the result, ECMWF reanalysis contains large amount of small-scale eddies, whereas the NCEP-NCAR reanalysis is smoother, reflecting the different spectral truncations. The normal model method provides a reasonable distribution of vertical motion, and the problem in the spectral method over the complex terrain is solved by this method. It is demonstrated that the normal mode method may be useful for the diagnostic studies of the general circulation of the atmosphere.