In order to study the energy balance and the cloud radiative forcing (CRF) of the Tibetan Plateau in detail, 2 years of GMS5 satellite data are employed to analyze the monthly mean outgoing longwave radiation (OLR) and CRF. It should be noted that the temporal resolution of GMS5 data is 1 hour, so the data can be used to study the diurnal variations of OLR. First, a method is presented to retrieve the OLR from split‐window channels (10.5–11.5 and 11.5–12.5 μm) and the water vapor channel (6.5–7.0 μm) of GMS5. The method applies the discrete ordinates radiative transfer (DISORT) model together with the radiosonde profiles of the Tibetan Plateau to simulate radiances and fluxes of the three channels. A regression relationship is then developed to calculate the OLR from the observations of the three channels. Since the Tibetan Plateau is located nearly out of the effective observational range of the GMS5 satellite, the regression results of GMS5's split‐window channels and water vapor channel are corrected by using simultaneously retrieved results from TIROS Operational Vertical Sounder (TOVS). The correlation coefficient of GMS5 and TOVS results is 0.8510, which is large enough for 1% significant level. The OLR distributions are calculated for the Tibetan Plateau using 2 years of GMS5 data and the regression and correction methods. The average of the OLR images for the same month and same time gives the monthly mean OLR distribution for each hour. The 24‐hour OLR distributions of the same month are then averaged to yield the monthly mean OLR distribution for that month. Then our monthly mean OLR distributions are compared with the Clouds and the Earth's Radiant Energy System (CERES) results, and they are generally in good agreement with differences of <10% for January and 5% for July. Analyzing the monthly mean OLR distributions for different seasons, we find that during the winter season the OLR distribution exhibits low values over the Tibetan Plateau but high values for areas off the Tibetan Plateau. During the summer season the OLR of the southern part is smaller than that of the northern part. Studying the monthly mean diurnal variations of OLR, we find that the diurnal variations of OLR are affected by diurnal cycles of cloud quantity and surface temperature. The relief of the Tibetan Plateau is very high, and the radiative heating is intense after sunrise. The OLR is greatly influenced by the surface and reaches a maximum value soon after sunrise, but the time the minimum OLR emerges varies. After the OLR distributions of the Tibetan Plateau are obtained, the role of clouds in the climate system is also studied. In order to calculate the CRF the International Satellite Cloud Climatology Project (ISCCP) cloud detection algorithm is used to detect the clear pixels for each image. The clear‐sky components of OLR and albedo for different months and hours are then derived and averaged over a month to obtain the monthly mean clear‐sky OLR and albedo for each hour. Finally, data are averaged over 24 hours to give the monthly mean shortwave CRF (SWCRF), longwave CRF (LWCRF), and CRF. The results show that the CRF over the Tibetan Plateau is negative most of the time. This means the CRF is dominated by cooling effects, and the distribution pattern is mainly determined by the SWCRF component. While the CRFs to the south and the north of the Tibetan Plateau are different, there are obvious annual variations with heating effects in the summer‐autumn season and cooling effects in the winter‐spring season.