US-Baltimore: Lodz-SUEB

NOTE: Results presented here are highly dependent on how models are configured in this experiment and may be subject to variable output formatting errors. Results are not intended to indicate the quality of any individual model, but to help participants better understand and improve modelling approaches in different urban environments.

Submitted metadata

• Baseline
• Detailed

Error metrics

flux	experiment	MAE	MBE	nSD	R	5th	95th	RMSE	cRMSE	AMBE	1-nSD	1-R	nSkewness	nKurtosis	Overlap
SWup	baseline	9.327	5.09618	1.20749	0.964133	0.0672	21.9499	13.1067	0.360097	5.09618	0.207491	0.0358668	0.179663	0.181769	0.107287
SWup	detailed	5.96355	-4.8413	0.965993	0.964133	0.4264	3.2351	10.1321	0.265425	4.8413	0.0340071	0.0358668	0.179663	0.181769	0.0764739
LWup	baseline	20.3597	7.78104	1.35377	0.941429	13.2397	63.8227	30.4483	0.532666	7.78104	0.353766	0.0585706	11.4261	1.04295	0.0942374
LWup	detailed	24.1948	15.6373	1.44107	0.925119	9.0562	85.0313	38.7018	0.640598	15.6373	0.441073	0.0748813	13.8992	1.25369	0.0864671
Qle	baseline	26.4456	-7.05038	0.859138	0.812476	14.5412	37.1554	42.891	0.584859	7.05038	0.140863	0.187524	0.0281225	0.146655	0.373712
Qle	detailed	26.3593	-5.27017	0.884675	0.813926	14.5696	31.0063	42.6634	0.585261	5.27017	0.115325	0.186074	0.0488877	0.209247	0.380523
Qh	baseline	30.9145	1.02851	0.764528	0.851156	23.0967	44.5899	47.1887	0.532013	1.02851	0.235473	0.148844	0.021966	0.046157	0.208961
Qh	detailed	33.284	1.44061	0.6915	0.846312	26.8768	61.4489	49.2129	0.554727	1.44061	0.308501	0.153688	0.0643125	0.11035	0.269156
SoilTemp	baseline	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan
SoilTemp	detailed	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan
Qtau	baseline	0.101358	-0.0498077	0.652657	0.891996	0.00474218	0.267268	0.162838	0.511494	0.0498077	0.347344	0.108004	0.0211244	0.0700592	0.194676
Qtau	detailed	0.146471	0.112326	1.09842	0.874183	0.038773	0.16027	0.197229	0.534869	0.112326	0.0984174	0.125817	0.0311434	0.100331	0.282888

• MAE: mean absolute error (close to 0 is better)
• MBE: mean bias error (close to 0 is better)
• NSD: ratio of model to obs standard deviation (close to 1 is better)
• R: Pearson’s correlation (close to 1 is better)
• all others: closer to 0 is better

Link to variable definitions

subset_SWup_v0-9

out of range: baseline

out of range: detailed

Link to variable definitions