Revisiting hydrometeorology using cloud and climate observations
We use 620 station years of hourly Canadian Prairie climate data to show the coupling of monthly near-surface climate with opaque cloud, a surrogate for radiation, and precipitation anomalies. While the cloud-climate coupling is strong, we find that precipitation anomalies impact monthly climate for as long as 5 months. The April climate has memory of precipitation anomalies back to freeze-up in November, mostly stored in the snowpack. The summer climate has memory of precipitation anomalies back to the beginning of snow-melt in March. In the warm season, mean temperature is strongly coupled to opaque cloud anomalies, but only weakly to precipitation anomalies. Mixing ratio anomalies are coupled to precipitation, but only weakly to cloud. The diurnal cycle of mixing ratio shifts upwards with increasing precipitation anomalies.
Positive precipitation anomalies are coupled to a lower afternoon lifting condensation level and a higher afternoon equivalent potential temperature; both favor increased convection and precipitation. Regression coefficients on precipitation increase from wet to dry conditions. This is consistent with increased uptake of soil water when monthly precipitation is low, until drought conditions are reached, and also consistent with gravity satellite observations. Regression analysis shows monthly opaque cloud cover is tightly coupled to three climate variables that are routinely observed: diurnal temperature range, mean temperature and mean relative humidity. Our set of coupling coefficients, derived from climate observations, could be used to evaluate the representation of the land-cloud-atmosphere system in both forecast and climate models.
Plain English Discussion
The reflective cloud data at Prairie climate stations tells us how clouds change the surface energy and water balance, and with this the monthly climate. We are able to show that the April climate remembers the precipitation that fell mostly as snow back to freeze-up in November. And the summer climate remembers precipitation back to the March. It appears that the evaporation from crops adjusts to partly compensate for rainy and drought months. Cloud cover and climate are tightly related, and we may be able to improve seasonal forecasts if we can better model cloud cover.