A Simple Moisture Advection Model of Specific Humidity
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1NOVEMBER 2016 C HADWICK ET AL. 7613 A Simple Moisture Advection Model of Specific Humidity Change over Land in Response to SST Warming ROBIN CHADWICK,PETER GOOD, AND KATE WILLETT Met Office Hadley Centre, Exeter, United Kingdom (Manuscript received 24 March 2016, in final form 25 July 2016) ABSTRACT A simple conceptual model of surface specific humidity change (Dq) over land is described, based on the effect of increased moisture advection from the oceans in response to sea surface temperature (SST) warming. In this model, future q over land is determined by scaling the present-day pattern of land q by the fractional increase in the oceanic moisture source. Simple model estimates agree well with climate model projections of future Dq (mean spatial correlation coefficient 0.87), so Dq over both land and ocean can be viewed primarily as a thermodynamic process controlled by SST warming. Precipitation change (DP) is also affected by Dq, and the new simple model can be included in a decomposition of tropical precipitation change, where it provides increased physical understanding of the processes that drive DP over land. Confidence in the thermodynamic part of extreme precipitation change over land is increased by this improved understanding, and this should scale approximately with Clausius–Clapeyron oceanic q increases under SST warming. Residuals of actual climate model Dq from simple model estimates are often associated with regions of large circulation change, and can be thought of as the ‘‘dynamical’’ part of specific humidity change. The simple model is used to explore intermodel uncertainty in Dq, and there are substantial contributions to uncertainty from both the thermodynamic (simple model) and dynamical (residual) terms. The largest cause of intermodel uncertainty within the thermodynamic term is uncertainty in the magnitude of global mean SST warming. 1. Introduction the Clausius–Clapeyron equation (Held and Soden 2006). Climate model projections agree well with this pre- Future changes in surface humidity under global diction (Held and Soden 2006; Sherwood et al. 2010; warming could affect human comfort (Willett and O’Gorman and Muller 2010), with only small RH in- Sherwood 2012), labor capacity (Dunne et al. 2013), creases projected over the oceans. Observed and mod- and even, for extreme warming scenarios, the habit- eled trends of historical surface q change over the ability of some land regions (Sherwood and Huber 2010; oceans are also consistent with this Clausius–Clapeyron Pal and Eltahir 2016). Humidity changes are also closely rate of increase (Dai 2006). linked to changes in surface evaporation, transpiration, Over land it is far less obvious how surface humidity soil moisture, mean and extreme precipitation, and clouds will respond to warming, as the moisture supply from the (e.g., Emori and Brown 2005; Fasullo 2012; Sherwood and land surface is often limited, and the energy balance Fu 2014; Byrne and O’Gorman 2015; Chadwick 2016; arguments that apply to oceanic Dq are much less rele- Kamae et al. 2016). vant. Net moisture transport from ocean to land increases Over the oceans, energy balance considerations (de- under warming in future model projections (Zahn and scribed in Held and Soden 2000; Schneider et al. 2010) Allan 2013), but the exact implications of this for hu- suggest that surface specific humidity (q) should in- midity change are unclear. Observed trends from the crease approximately in line with surface air tempera- period of 1973–99 are consistent with a local Clausius– ture under fixed relative humidity (RH), which implies 2 Clapeyron response under fixed RH in many land re- increases of around 7% degree 1 of local warming under gions, but the relationship between local temperature and q change breaks down in drier regions (Dai 2006; Corresponding author address: Robin Chadwick, Met Office Willett et al. 2010). Over the more recent period of Hadley Centre, FitzRoy Rd., Exeter, EX1 3PB, United Kingdom. 1999–2015 there is evidence of significant decreases in E-mail: robin.chadwick@metoffice.gov.uk RH over land (Simmons et al. 2010; Willett et al. 2014, DOI: 10.1175/JCLI-D-16-0241.1 Unauthenticated | Downloaded 09/28/21 10:32 PM UTC 7614 JOURNAL OF CLIMATE VOLUME 29 2015), causing this local Clausius–Clapeyron model to Section 2 describes the climate model data used in this be brought into question. Agreement between the in situ study. Section 3 presents the basic concept of the simple record and reanalyses is good (Willett et al. 2015), but model and applies it to climate model projections, fol- natural variability over the observed period and the lowed by a more detailed derivation. The model as- sparseness of the observational network over many sumptions are considered in detail in section 4. Section 5 land regions means that care must be taken when in- analyses intermodel uncertainty in GCM projections of terpreting these trends. Climate models do not re- future Dq, and relates it to the simple model and its re- produce the observed recent decreases in RH when sidual. Section 6 describes how the new simple model run in coupled atmosphere–ocean configuration over can be integrated into a decomposition of tropical pre- the same period, but do slightly better when forced cipitation change. Finally, a summary and some con- with observed SSTs (R. J. H. Dunn et al. 2016, un- clusions are presented in section 7. published manuscript). In end-of-twenty-first-century climate model projec- tions there is a clear reduction of surface RH over many 2. Data land regions, corresponding to an overall sublocal– Monthly data from the first ensemble members of 28 Clausius–Clapeyron increase in q over land (O’Gorman phase 5 of the Coupled Model Intercomparison Project and Muller 2010). It has been suggested this is due to (CMIP5; Taylor et al. 2012) models were used, listed in the increased land–sea temperature contrast (e.g., Joshi Table 1. The present-day period was taken as a clima- et al. 2008), which outstrips the ability of moisture tological mean over the years 1971–2000 of each model’s supply—originating from the less warm oceans—to historical run, and the future period was a 2071–2100 maintain constant RH over the warmer land surface mean from the high-emissions representative concen- (Rowell and Jones 2006; O’Gorman and Muller 2010; tration pathway 8.5 (RCP8.5) scenario. All model data Simmons et al. 2010). O’Gorman and Muller (2010) were regridded to a common resolution of 2.58 for com- made a rough estimate of how land RH would decrease in parison with one another. response to this enhanced land warming if specific hu- midity change were identical between land and ocean, and this estimate is consistent with GCM projections of 3. A simple model of oceanic moisture the change in global land RH. However, they noted that advection over land this homogenization of Dq between land and ocean does a. Simple model not actually occur, and so more work is needed to understand humidity change over land, particularly on Our simple conceptual model represents the change in regional scales. Berg et al. (2016) demonstrated that land– moisture over land that occurs in response to advection atmosphere feedbacks can substantially alter the change of increased q from the oceans, under SST warming. It in land RH under warming, and so the advection of assumes the circulation remains unchanged, and so can moisture over land is not the only important process in be seen as the thermodynamic component of q change determining changes in relative humidity. over land. It takes the form of a scaling of the present- In the present study we extend these ideas of how day pattern of land q by the fractional increase in the surface q over land might respond to increased q over oceanic moisture source: the oceans. We start from the following principles: 1) on q climate time scales, the vast majority of atmospheric 5 s, f ql, f ql,p, (1) moisture over land originates from the oceans (Simmons qs,p et al. 2010; Gimeno et al. 2010, 2012; Van der Ent and Savenije 2013) and 2) the adjustment time scale of where ql is the time-mean surface (2 m) specific hu- moisture over land in response to transport from the midity at a given point over land, qs is the time-mean oceans is much faster than the warming time scale of surface specific humidity at the oceanic moisture source the surface oceans under climate change. These un- for that land point, and subscripts p and f denote derlying principles are combined with a number of present-day and future climates, respectively. simplifying assumptions to build a simple conceptual From this, we can predict the spatial distribution of ql, f model of how surface specific humidity over land might from the fractional change in qs over the ocean, com- respond under climate change to increased moisture ad- bined with the present-day pattern of ql,p. We need to vection from the oceans, driven by warmer SSTs. The specify which region of ocean we are using to represent simple model is then compared with climate model qs (the oceanic moisture source) for each land point, and projections. we choose to use the time-mean zonal mean of ocean Unauthenticated | Downloaded 09/28/21 10:32 PM UTC 1NOVEMBER 2016 C HADWICK ET AL. 7615 TABLE 1. Skill scores for comparison of CC (DqCC) and simple model (Dqadv) estimates with actual Dq for each CMIP5 model for the 2 2 global pattern of change over land. Correlation coefficient (R), bias (g kg 1), and RMSE (g kg 1) are all shown. Annual climatological means are used.