Impact of vegetation removal and soil aridation on diurnal temperature range in a semiarid region: Application to the Sahel

Abstract

Increased clouds and precipitation normally decrease the diurnal temperature range (DTR) and thus have commonly been offered as explanation for the trend of reduced DTR observed for many land areas over the last several decades. Observations show, however, that the DTR was reduced most in dry regions and especially in the West African Sahel during a period of unprecedented drought. Furthermore, the negative trend of DTR in the Sahel appears to have stopped and may have reversed after the rainfall began to recover. This study develops a hypothesis with climate model sensitivity studies showing that either a reduction in vegetation cover or a reduction in soil emissivity would reduce the DTR by increasing nighttime temperature through increased soil heating and reduced outgoing longwave radiation. Consistent with empirical analyses of observational data, our results suggest that vegetation removal and soil aridation would act to reduce the DTR during periods of drought and human mismanagement over semiarid regions such as the Sahel and to increase the DTR with more rainfall and better human management. Other mechanisms with similar effects on surface energy balance, such as increased nighttime downward longwave radiation due to increased greenhouse gases, aerosols, and clouds, would also be expected to have a larger impact on DTR over drier regions.drought ͉ surface emissivity ͉ longwave radiation ͉ sensitivity test ͉ surface energy balance T he global mean land surface air temperature has been steadily rising since the 1950s, primarily attributed to increased greenhouse gases, and this rising results largely from nighttime warming over some land areas as minimum temperature (T min ) increased much faster than maximum temperature (T max ) (1). Associated with such asymmetric warming is the reduction of the diurnal temperature range (DTR) (DTR ϭ T max Ϫ T min ) (1). The decrease in DTR has been observed over most locations over land since 1950 (2), but in many parts of the world this decline abated in the early 1980s (3), perhaps coincident with the reversal of global dimming (4). The DTR appears to continue to decrease in some rapidly industrializing locations such as southern China (5).Changes in DTR can result from a number of mechanisms, all connected to the surface energy balance. The most obvious and widely recognized mechanism from a meteorological viewpoint is the reduction of DTR as a consequence of the increase of clouds, precipitation, and soil moisture (6, 7). Clouds, especially low clouds, decrease the daytime surface solar heating and increase nighttime downward longwave radiation. Evapotranspiration associated with soil moisture and precipitation can balance solar heating and further reduce T max . These day-to-day changes in DTR aggregate to seasonal to multidecadal statistical connections between DTR and clouds/precipitation/soil moisture (7).Other mechanisms such as changes in atmospheric circulation, greenhouse gases, aerosols, and land cover/use may also contribute to a decrease of the DTR (6,8,...

Detection and attribution of anthropogenic forcing to diurnal temperature range changes from 1950 to 1999: comparing multi-model simulations with observations

“…In fact, TCC over many regions and P in tropical climates have been observed to be increasing. However, coincident decreasing trends in DTR and TCC are observed over some regions such as China and the Sahel (e.g., Kaiser 1998;Liu et al 2004;Zhou et al 2007) and are seen globally over the ALL simulations, suggesting that the longer term variability/trend has different connections between DTR and TCC/P than the interannual variability. Surface radiation will likely change in a warmer and wetter climate.…”

“…Observational analyses show that there is a strong geographic dependence of trends of DTR and T min on the climatology of precipitation (Zhou et al 2007(Zhou et al , 2008. To test whether the simulated temperatures have similar features, we classified the 499 grid boxes into 7, 11, 15, 19, and 23 precipitation zones, respectively, from dry to wet, in terms of the observed amount of climatological annual precipitation (referred to as P; mm/day) (Chen et al 2001), and then analyzed the spatial dependence of temperature trends on P by precipitation zone, as done in Zhou et al (2008).…”

“…The linear trends are listed and those marked with ''*'' are statistically significant (p \ 0.05). A 5-point (i.e., 5-year) running averaging was applied for visualization purpose only, with the first and last 2 year values applied using a recycling boundary condition (e.g., Zhou et al 2001Zhou et al , 2003Zhou et al , 2007Zhou et al , 2008. Furthermore, given the non-stationary properties of the data involved and the pitfalls associated with use of standard statistical techniques, applications of other advanced statistical techniques are not warranted.…”

“…Due to the limited data coverage over Africa, South America and Antarctica, we classify the 499 boxes into 5 climate zones ( Fig. 1) to represent changes at large scales over different climate zones (instead of continental scales) based on the latest world map of the Koppen-Geiger climate classification (Kottek et al 2006), given the dependence of DTR trends on climate zones (Zhou et al 2007(Zhou et al , 2008. The Koppen-Geiger climate classification is one of the most widely used climate classification systems based on observed temperature and precipitation; it assigns the world climate at any land site to one of five general categories-moist tropic, arid, Among the 12 models in the ALL simulations, GISS-AOM and ECHAM5/MPI-OM considered only anthropogenic forcings (i.e., natural forcings were not applied), while the other 10 models included both anthropogenic and natural forcings.…”

“…Observational analyses have attributed the reduction of DTR to increases primarily of cloud cover and secondarily of precipitation and soil moisture (e.g., Dai et al 1999). The observed DTR trends may be affected by the large-scale effects of increased GHGs and aerosols (Zhou et al 2007(Zhou et al , 2008 and also regional changes in land surface properties (Collatz et al 2000;.…”